Douglas F. Levinson, M.D.

All Publications

• Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia. Nature neuroscience Zhu, X. n., Zhou, B. n., Pattni, R. n., Gleason, K. n., Tan, C. n., Kalinowski, A. n., Sloan, S. n., Fiston-Lavier, A. S., Mariani, J. n., Petrov, D. n., Barres, B. A., Duncan, L. n., Abyzov, A. n., Vogel, H. n., Moran, J. V., Vaccarino, F. M., Tamminga, C. A., Levinson, D. F., Urban, A. E. 2021

  Abstract

  Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertions presents a difficult signal-to-noise problem. Using a machine-learning method (RetroSom) and deep whole-genome sequencing, we analyzed L1 and Alu retrotransposition in sorted neurons and glia from human brains. We characterized two brain-specific L1 insertions in neurons and glia from a donor with schizophrenia. There was anatomical distribution of the L1 insertions in neurons and glia across both hemispheres, indicating retrotransposition occurred during early embryogenesis. Both insertions were within the introns of genes (CNNM2 and FRMD4A) inside genomic loci associated with neuropsychiatric disorders. Proof-of-principle experiments revealed these L1 insertions significantly reduced gene expression. These results demonstrate that RetroSom has broad applications for studies of brain development and may provide insight into the possible pathological effects of somatic retrotransposition.

  View details for DOI 10.1038/s41593-020-00767-4

  View details for PubMedID 33432196

• Low C4 Copy Number of Total C4 Gene, C4B Gene and C4BL Gene in Children with Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) Kalinowski, A., Lee, J., Hedlin, H., Pattini, R., Ollila, H., Mignot, E., Levinson, D., Swedo, S., Murphy, T., Chan, A., Thienemann, M., Urban, A., Frankovich, J. WILEY. 2020: 254–55

  View details for Web of Science ID 000542687800145

• Minimal phenotyping yields genome-wide association signals of low specificity for major depression. Nature genetics Cai, N., Revez, J. A., Adams, M. J., Andlauer, T. F., Breen, G., Byrne, E. M., Clarke, T., Forstner, A. J., Grabe, H. J., Hamilton, S. P., Levinson, D. F., Lewis, C. M., Lewis, G., Martin, N. G., Milaneschi, Y., Mors, O., Muller-Myhsok, B., Penninx, B. W., Perlis, R. H., Pistis, G., Potash, J. B., Preisig, M., Shi, J., Smoller, J. W., Streit, F., Tiemeier, H., Uher, R., Van der Auwera, S., Viktorin, A., Weissman, M. M., MDD Working Group of the Psychiatric Genomics Consortium, Kendler, K. S., Flint, J. 2020

  Abstract

  Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

  View details for DOI 10.1038/s41588-020-0594-5

  View details for PubMedID 32231276

• Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank MOLECULAR PSYCHIATRY Coleman, J. I., Peyrot, W. J., Purves, K. L., Davis, K. S., Rayner, C., Choi, S., Hubel, C., Gaspar, H. A., Kan, C., Van der Auwera, S., Adams, M., Lyall, D. M., Choi, K. W., Dunn, E. C., Vassos, E., Danese, A., Maughan, B., Grabe, H. J., Lewis, C. M., O'Reilly, P. F., McIntosh, A. M., Smith, D. J., Wray, N. R., Hotopf, M., Eley, T. C., Breen, G., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. M., Bacanu, S., Baekvad-Hansen, M., Beekman, A. F., Bigdeli, T. B., Binder, E. B., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J., Clarke, T., Coleman, J. I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F., Finucane, H. K., Foo, J. C., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hansen, C., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Howard, D. M., Ising, M., Jansen, R., Jones, I., Jones, L. A., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Kutalik, Z., Li, Y., Lind, P. A., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C., Pedersen, M., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S. I., Sigurdsson, E., Sinnamon, G. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D. I., Cichon, S., Dannlowski, U., de Geus, E. C., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P., Mueller-Myhsok, B., Nordentoft, M., Noethen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Volzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F., Psychiat Genomics Consortium 2020

  Abstract

  Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

  View details for DOI 10.1038/s41380-019-0546-6

  View details for Web of Science ID 000509565100001

  View details for PubMedID 31969693

• Cohort profile: the Australian genetics of depression study. BMJ open Byrne, E. M., Kirk, K. M., Medland, S. E., McGrath, J. J., Colodro-Conde, L. n., Parker, R. n., Cross, S. n., Sullivan, L. n., Statham, D. J., Levinson, D. F., Licinio, J. n., Wray, N. R., Hickie, I. B., Martin, N. G. 2020; 10 (5): e032580

  Abstract

  Depression is the most common psychiatric disorder and the largest contributor to global disability. The Australian Genetics of Depression study was established to recruit a large cohort of individuals who have been diagnosed with depression at some point in their lifetime. The purpose of establishing this cohort is to investigate genetic and environmental risk factors for depression and response to commonly prescribed antidepressants.A total of 20 689 participants were recruited through the Australian Department of Human Services and a media campaign, 75% of whom were female. The average age of participants was 43 years±15 years. Participants completed an online questionnaire that consisted of a compulsory module that assessed self-reported psychiatric history, clinical depression using the Composite Interview Diagnostic Interview Short Form and experiences of using commonly prescribed antidepressants. Further voluntary modules assessed a wide range of traits of relevance to psychopathology. Participants who reported they were willing to provide a DNA sample (75%) were sent a saliva kit in the mail.95% of participants reported being given a diagnosis of depression by a medical practitioner and 88% met the criteria for a lifetime depressive episode. 68% of the sample report having been diagnosed with another psychiatric disorder in addition to depression. In line with findings from clinical trials, only 33% of the sample report responding well to the first antidepressant they were prescribed.A number of analyses to investigate the genetic architecture of depression and common comorbidities will be conducted. The cohort will contribute to the global effort to identify genetic variants that increase risk to depression. Furthermore, a thorough investigation of genetic and psychosocial predictors of antidepressant response and side effects is planned.

  View details for DOI 10.1136/bmjopen-2019-032580

  View details for PubMedID 32461290

• Genomics of major depressive disorder PERSONALIZED PSYCHIATRY Levinson, D. F., Baune, B. T. 2020: 187–200

  View details for DOI 10.1016/B978-0-12-813176-3.00016-X

  View details for Web of Science ID 000533781500017

• Developmental and symptom profiles in early-onset psychosis. Schizophrenia research Giannitelli, M., Levinson, D. F., Cohen, D., Xavier, J., Molecular Genetics of Schizophrenia Collaboration (MGS), Laurent-Levinson, C. 2019

  Abstract

  Psychotic disorders in children are more heterogeneous than is captured by categorical diagnoses. In a new cohort of children and adolescents, we evaluated the relationships among age at onset (AAO), clinical symptoms and developmental impairments. Patients with schizophrenia and other "spectrum" psychotic diagnoses (N = 88; AAO 6-17, mean 12.6) were evaluated with diagnostic interviews, a new clinical scale (Lifetime Dimensions of Psychosis Scale-Child and Adolescent), and neuropsychological and medical evaluations. Key findings were replicated in an adult cohort of 2420 cases, including 127 with retrospective AAO<13. Factor and cluster analyses were carried out to identify clinical profiles. Five clinical factors were identified in each cohort: Positive, Bizarre Positive, Negative/Formal Thought Disorder, Depression and Mania. Earlier AAO predicted severity of bizarre positive symptoms in children and of bizarre and other symptoms in adults. Four clinical clusters in the child cohort were characterized by: more severe bizarre positive symptoms (N = 31); negative symptoms (N = 15); premorbid autism spectrum features and developmental delay (N = 12); and depressive symptoms with heterogeneous diagnoses and mild positive/negative symptoms (N = 25). Previous factor-analytic studies of childhood psychosis did not specifically consider bizarre positive symptoms. Here, bizarre positive symptoms emerged as clinical markers of severe, childhood-onset psychosis similar to adult schizophrenia. The four clusters are clinically meaningful and useful for treatment planning and potentially for biological research. Childhood-onset cases are rare and thus difficult to study, but additional, larger cohorts may be useful in dissecting the biological and developmental heterogeneity of psychotic disorders.

  View details for DOI 10.1016/j.schres.2019.10.028

  View details for PubMedID 31874744

• MACHINE LEARNING REVEALS BILATERAL DISTRIBUTION OF SOMATIC L1 INSERTIONS IN HUMAN NEURONS AND GLIA Zhu, X., Zhou, B., Pattni, R., Gleason, K., Tan, C., Kalinowski, A., Sloan, S., Fiston-Lavier, A., Mariani, J., Vogel, H., Moran, J., Vaccarino, F., Tamminga, C., Levinson, D., Urban, A. ELSEVIER. 2019: S68

  View details for DOI 10.1016/j.euroneuro.2019.07.158

  View details for Web of Science ID 000488216600131

• APPROACHES TO TRANSCRIPTOME ANALYSIS OF HUMAN INDUCED NEURONS IN CO-CULTURE WITH MURINE GLIA TO MODEL FUNCTIONAL SYNAPSES Purmann, C., Zhang, X., Pak, C., Huang, Y., Pattni, R., Grieder, S., Wernig, M., Levinson, D., Aronow, B., Sudhof, T., Urban, A. ELSEVIER. 2019: S172–S173

  View details for DOI 10.1016/j.euroneuro.2019.08.112

  View details for Web of Science ID 000488216600313

• Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Trzaskowski, M., Mehta, D., Peyrot, W. J., Hawkes, D., Davies, D., Howard, D. M., Kemper, K. E., Sidorenko, J., Maier, R., Ripke, S., Mattheisen, M., Baune, B. T., Grabe, H. J., Heath, A. C., Jones, L., Jones, I., Madden, P. F., McIntosh, A. M., Breen, G., Lewis, C. M., Borglum, A. D., Sullivan, P. F., Martin, N. G., Kendler, K. S., Levinson, D. F., Wray, N. R., Major Depress Disorder Working G 2019; 180 (6): 439–47

  View details for DOI 10.1002/ajmg.b.32713

  View details for Web of Science ID 000478086300010

• Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression. Biological psychiatry Glanville, K. P., Coleman, J. R., Hanscombe, K. B., Euesden, J., Choi, S. W., Purves, K. L., Breen, G., Air, T. M., Andlauer, T. F., Baune, B. T., Binder, E. B., Blackwood, D. H., Boomsma, D. I., Buttenschon, H. N., Colodro-Conde, L., Dannlowski, U., Direk, N., Dunn, E. C., Forstner, A. J., de Geus, E. J., Grabe, H. J., Hamilton, S. P., Jones, I., Jones, L. A., Knowles, J. A., Kutalik, Z., Levinson, D. F., Lewis, G., Lind, P. A., Lucae, S., Magnusson, P. K., McGuffin, P., McIntosh, A. M., Milaneschi, Y., Mors, O., Mostafavi, S., Muller-Myhsok, B., Pedersen, N. L., Penninx, B. W., Potash, J. B., Preisig, M., Ripke, S., Shi, J., Shyn, S. I., Smoller, J. W., Streit, F., Sullivan, P. F., Tiemeier, H., Uher, R., Van der Auwera, S., Weissman, M. M., Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, O'Reilly, P. F., Lewis, C. M., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. F., Bacanu, S., Bakvad-Hansen, M., Beekman, A. T., Bigdeli, T. B., Binder, E. B., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J. H., Clarke, T., Coleman, J. R., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Escott-Price, V., Hassan Kiadeh, F. F., Finucane, H. K., Foo, J. C., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hansen, C. S., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Howard, D. M., Ising, M., Jansen, R., Jones, I., Jones, L. A., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Kutalik, Z., Li, Y., Lind, P. A., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C. B., Pedersen, M. G., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S. S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S. I., Sigurdsson, E., Sinnamon, G. C., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S. M., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D. I., Cichon, S., Dannlowski, U., de Geus, E. J., DePaulo, J. R., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. A., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P. B., Muller-Myhsok, B., Nordentoft, M., Nothen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. W., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Volzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F. 2019

  Abstract

  BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression.METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9* 10-6) and a candidate threshold (1.6* 10-4).RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio= 0.98, 95% confidence interval= 0.97-0.99).CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.

  View details for DOI 10.1016/j.biopsych.2019.06.031

  View details for PubMedID 31570195

• Genome-wide Burden of Rare Short Deletions Is Enriched in Major Depressive Disorder in Four Cohorts BIOLOGICAL PSYCHIATRY Zhang, X., Abdellaoui, A., Rucker, J., de Jong, S., Potash, J. B., Weissman, M. M., Shi, J., Knowles, J. A., Pato, C., Pato, M., Sobell, J., Smit, J. H., Hottenga, J., de Geus, E. C., Lewis, C. M., Buttenschon, H. N., Craddock, N., Jones, I., Jones, L., McGuffin, P., Mors, O., Owen, M. J., Preisig, M., Rietschel, M., Rice, J. P., Rivera, M., Uher, R., Gejman, P. V., Sanders, A. R., Boomsma, D., Penninx, B. H., Breen, G., Levinson, D. F. 2019; 85 (12): 1065–73

  View details for DOI 10.1016/j.biopsych.2019.02.022

  View details for Web of Science ID 000469965600016

• Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns NATURE COMMUNICATIONS Czamara, D., Eraslan, G., Page, C. M., Lahti, J., Lahti-Pulkkinen, M., Hamalainen, E., Kajantie, E., Laivuori, H., Villa, P. M., Reynolds, R. M., Nystad, W., Haberg, S. E., London, S. J., O'Donnell, K. J., Garg, E., Meaney, M. J., Entringer, S., Wadhwa, P. D., Buss, C., Jones, M. J., Lin, D. S., MacIsaac, J. L., Kobor, M. S., Koen, N., Zar, H. J., Koenen, K. C., Dalvie, S., Stein, D. J., Kondofersky, I., Mueller, N. S., Theis, F. J., Raikkonen, K., Binder, E. B., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. M., Bacanu, S., Baekvad-Hansen, M., Beekman, A. F., Bigdeli, T. B., Blackwood, D. R., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J., Clarke, T., Coleman, J. R., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F., Finucane, H. K., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hansen, C., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Ising, M., Jansen, R., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Li, Y., Lind, P. A., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C., Pedersen, M., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S., Sigurdsson, E., Sinnamon, G. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D., Cichon, S., Dannlowski, U., de Geus, E. C., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P., Mueller-Myhsok, B., Nordentoft, M., Noethen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Voelzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F., Psychiat Genomics Consortium 2019; 10: 2548

  Abstract

  Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.

  View details for DOI 10.1038/s41467-019-10461-0

  View details for Web of Science ID 000470968400008

  View details for PubMedID 31186427

• Gene expression imputation across multiple brain regions provides insights into schizophrenia risk NATURE GENETICS Huckins, L. M., Dobbyn, A., Ruderfer, D. M., Hoffman, G., Wang, W., Pardinas, A. F., Rajagopal, V. M., Als, T. D., Nguyen, H. T., Girdhar, K., Boocock, J., Roussos, P., Fromer, M., Kramer, R., Domenici, E., Gamazon, E. R., Purcell, S., Demontis, D., Borglum, A. D., Walters, J. R., O'Donovan, M. C., Sullivan, P., Owen, M. J., Devlin, B., Sieberts, S. K., Cox, N. J., Im, H., Sklar, P., Stahl, E. A., Johnson, J. S., Shah, H. R., Klein, L. L., Dang, K. K., Logsdon, B. A., Mahajan, M. C., Mangravite, L. M., Toyoshiba, H., Gur, R. E., Hahn, C., Schadt, E., Lewis, D. A., Haroutunian, V., Peters, M. A., Lipska, B. K., Buxbaum, J. D., Hirai, K., Perumal, T. M., Essioux, L., Rajagopal, V., Mattheisen, M., Grove, J., Werge, T., Mortensen, P., Pedersen, C., Agerbo, E., Pedersen, M., Mors, O., Nordentoft, M., Hougaard, D. M., Bybjerg-Grauholm, J., Baekvad-Hansen, M., Hansen, C., Ripke, S., Neale, B. M., Corvin, A., Farh, K., Holmans, P. A., Lee, P., Bulik-Sullivan, B., Collier, D. A., Huang, H., Pers, T. H., Agartz, I., Albus, M., Alexander, M., Amin, F., Bacanu, S. A., Begemann, M., Belliveau, R. A., Bene, J., Bergen, S. E., Bevilacqua, E., Bigdeli, T. B., Black, D. W., Bruggeman, R., Buccola, N. G., Buckner, R. L., Byerley, W., Cahn, W., Cai, G., Campion, D., Cantor, R. M., Carr, V. J., Carrera, N., Catts, S., Chambert, K. D., Chan, R. K., Chen, R. L., Chen, E. H., Cheng, W., Cheung, E. C., Chong, S., Cloninger, C., Cohen, D., Cohen, N., Cormican, P., Craddock, N., Crowley, J. J., Curtis, D., Davidson, M., Davis, K. L., Degenhardt, F., Del Favero, J., Dikeos, D., Dinan, T., Djurovic, S., Donohoe, G., Drapeau, E., Duan, J., Dudbridge, F., Durmishi, N., Eichhammer, P., Eriksson, J., Escott-Price, V., Essioux, L., Fanous, A. H., Farrell, M. S., Frank, J., Franke, L., Freedman, R., Freimer, N. B., Friedl, M., Friedman, J., Fromer, M., Genovese, G., Georgieva, L., Giegling, I., Giusti-Rodriguez, P., Godard, S., Goldstein, J., Golimbet, V., Gopal, S., Gratten, J., de Haan, L., Hammer, C., Hamshere, M. L., Hansen, M., Hansen, T., Haroutunian, V., Hartmann, A. M., Henskens, F. A., Herms, S., Hirschhorn, J. N., Hoffmann, P., Hofman, A., Hollegaard, M., Ikeda, M., Joa, I., Julia, A., Kahn, R. S., Kalaydjieva, L., Karachanak-Yankova, S., Karjalainen, J., Kavanagh, D., Keller, M. C., Kennedy, J. L., Khrunin, A., Kim, Y., Klovins, J., Knowles, J. A., Konte, B., Kucinskas, V., Kucinskiene, Z., Kuzelova-Ptackova, H., Kahler, A. K., Laurent, C., Keong, J., Lee, S., Legge, S. E., Lerer, B., Li, M., Li, T., Liang, K., Lieberman, J., Limborska, S., Loughland, C. M., Lubinski, J., Lonnqvist, J., Macek, M., Magnusson, P. E., Maher, B. S., Maier, W., Mallet, J., Marsal, S., Mattingsdal, M., McCarley, R. W., McDonald, C., McIntosh, A. M., Meier, S., Meijer, C. J., Melegh, B., Melle, I., Mesholam-Gately, R., Metspalu, A., Michie, P. T., Milani, L., Milanova, V., Mokrab, Y., Morris, D. W., Mors, O., Murphy, K. C., Murray, R. M., Myin-Germeys, I., Muller-Myhsok, B., Nelis, M., Nenadic, I., Nertney, D. A., Nestadt, G., Nicodemus, K. K., Nikitina-Zake, L., Nisenbaum, L., Nordin, A., O'Callaghan, E., O'Dushlaine, C., O'Neill, F., Oh, S., Olincy, A., Olsen, L., Van Os, J., Pantelis, C., Papadimitriou, G. N., Papiol, S., Parkhomenko, E., Pato, M. T., Paunio, T., Pejovic-Milovancevic, M., Perkins, D. O., Pietilainen, O., Pimm, J., Pocklington, A. J., Powell, J., Price, A., Pulver, A. E., Purcell, S. M., Quested, D., Rasmussen, H. B., Reichenberg, A., Reimers, M. A., Richards, A. L., Roffman, J. L., Ruderfer, D. M., Salomaa, V., Sanders, A. R., Schall, U., Schubert, C. R., Schulze, T. G., Schwab, S. G., Scolnick, E. M., Scott, R. J., Seidman, L. J., Shi, J., Sigurdsson, E., Silagadze, T., Silverman, J. M., Sim, K., Slominsky, P., Smoller, J. W., So, H., Spencer, C. A., Stefansson, H., Steinberg, S., Stogmann, E., Straub, R. E., Strengman, E., Strohmaier, J., Stroup, T., Subramaniam, M., Suvisaari, J., Svrakic, D. M., Szatkiewicz, J. P., Soderman, E., Thirumalai, S., Toncheva, D., Tosato, S., Veijola, J., Waddington, J., Walsh, D., Wang, D., Wang, Q., Webb, B. T., Weiser, M., Wildenauer, D. B., Williams, N. M., Williams, S., Witt, S. H., Wolen, A. R., Wong, E. M., Wormley, B. K., Xi, H., Zai, C. C., Zheng, X., Zimprich, F., Wray, N. R., Stefansson, K., Visscher, P. M., Adolfsson, R., Andreassen, O. A., Blackwood, D. R., Bramon, E., Buxbaum, J. D., Borglum, A. D., Cichon, S., Darvasi, A., Domenici, E., Ehrenreich, H., Esko, T., Gejman, P., Gill, M., Gurling, H., Hultman, C. M., Iwata, N., Jablensky, A., Jonsson, E. G., Kendler, K. S., Kirov, G., Knight, J., Lencz, T., Levinson, D. F., Li, Q. S., Liu, J., Malhotra, A. K., McCarroll, S. A., McQuillin, A., Moran, J. L., Mortensen, P. B., Mowry, B. J., Nothen, M. M., Ophoff, R. A., Owen, M. J., Palotie, A., Pato, C. N., Petryshen, T. L., Posthuma, D., Rietschel, M., Riley, B. P., Rujescu, D., Sham, P. C., St Clair, D., Weinberger, D. R., Wendland, J. R., Werge, T., Daly, M. J., Sullivan, P. F., CommonMind Consortium, Psychiat Genomics Consortium, iPSYCH-GEMS Schizophrenia Working 2019; 51 (4): 659-+

  Abstract

  Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

  View details for DOI 10.1038/s41588-019-0364-4

  View details for Web of Science ID 000462767500013

  View details for PubMedID 30911161

• Assessment of Bidirectional Relationships Between Physical Activity and Depression Among Adults A 2-Sample Mendelian Randomization Study JAMA PSYCHIATRY Choi, K. W., Chen, C., Stein, M. B., Klimentidis, Y. C., Wang, M., Koenen, K. C., Smoller, J. W., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T., Andlauer, T. M., Bacanu, S., Baekvad-Hansen, M., Beekman, A. F., Bigdeli, T. B., Binder, E. B., Blackwood, D. R., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Hvarregaard, J., Christensen, J., Clarke, T., Coleman, J. I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F., Finucane, H. K., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hansen, C., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Ising, M., Jansen, R., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W., Krogh, J., Kutalik, Z., Li, Y., Lind, P. A., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Marchini, J., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C., Pedersen, M., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Saeed, S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S. I., Sigurdsson, E., Sinnamon, G. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D. I., Cichon, S., Dannlowski, U., de Geus, E. C., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P., Nordentoft, M., Noethen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Volzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F., Major Depressive Disorder Working 2019; 76 (4): 399–408

  Abstract

  Increasing evidence shows that physical activity is associated with reduced risk for depression, pointing to a potential modifiable target for prevention. However, the causality and direction of this association are not clear; physical activity may protect against depression, and/or depression may result in decreased physical activity.To examine bidirectional relationships between physical activity and depression using a genetically informed method for assessing potential causal inference.This 2-sample mendelian randomization (MR) used independent top genetic variants associated with 2 physical activity phenotypes-self-reported (n = 377 234) and objective accelerometer-based (n = 91 084)-and with major depressive disorder (MDD) (n = 143 265) as genetic instruments from the largest available, nonoverlapping genome-wide association studies (GWAS). GWAS were previously conducted in diverse observational cohorts, including the UK Biobank (for physical activity) and participating studies in the Psychiatric Genomics Consortium (for MDD) among adults of European ancestry. Mendelian randomization estimates from each genetic instrument were combined using inverse variance weighted meta-analysis, with alternate methods (eg, weighted median, MR Egger, MR-Pleiotropy Residual Sum and Outlier [PRESSO]) and multiple sensitivity analyses to assess horizontal pleiotropy and remove outliers. Data were analyzed from May 10 through July 31, 2018.MDD and physical activity.GWAS summary data were available for a combined sample size of 611 583 adult participants. Mendelian randomization evidence suggested a protective relationship between accelerometer-based activity and MDD (odds ratio [OR], 0.74 for MDD per 1-SD increase in mean acceleration; 95% CI, 0.59-0.92; P = .006). In contrast, there was no statistically significant relationship between MDD and accelerometer-based activity (β = -0.08 in mean acceleration per MDD vs control status; 95% CI, -0.47 to 0.32; P = .70). Furthermore, there was no significant relationship between self-reported activity and MDD (OR, 1.28 for MDD per 1-SD increase in metabolic-equivalent minutes of reported moderate-to-vigorous activity; 95% CI, 0.57-3.37; P = .48), or between MDD and self-reported activity (β = 0.02 per MDD in standardized metabolic-equivalent minutes of reported moderate-to-vigorous activity per MDD vs control status; 95% CI, -0.008 to 0.05; P = .15).Using genetic instruments identified from large-scale GWAS, robust evidence supports a protective relationship between objectively assessed-but not self-reported-physical activity and the risk for MDD. Findings point to the importance of objective measurement of physical activity in epidemiologic studies of mental health and support the hypothesis that enhancing physical activity may be an effective prevention strategy for depression.

  View details for DOI 10.1001/jamapsychiatry.2018.4175

  View details for Web of Science ID 000465165700012

  View details for PubMedID 30673066

  View details for PubMedCentralID PMC6450288

• Genome-wide Burden of Rare Short Deletions Is Enriched in Major Depressive Disorder in Four Cohorts. Biological psychiatry Zhang, X., Abdellaoui, A., Rucker, J., de Jong, S., Potash, J. B., Weissman, M. M., Shi, J., Knowles, J. A., Pato, C., Pato, M., Sobell, J., Smit, J. H., Hottenga, J., de Geus, E. J., Lewis, C. M., Buttenschon, H. N., Craddock, N., Jones, I., Jones, L., McGuffin, P., Mors, O., Owen, M. J., Preisig, M., Rietschel, M., Rice, J. P., Rivera, M., Uher, R., Gejman, P. V., Sanders, A. R., Boomsma, D., Penninx, B. W., Breen, G., Levinson, D. F. 2019

  Abstract

  BACKGROUND: Major depressive disorder (MDD) is moderately heritable, with a high prevalence and a presumed high heterogeneity. Copy number variants (CNVs) could contribute to the heritable component of risk, but the two previous genome-wide association studies of rare CNVs did not report significant findings.METHODS: In this meta-analysis of four cohorts (5780 patients and 6626 control subjects), we analyzed the association of MDD to 1) genome-wide burden of rare deletions and duplications, partitioned by length (<100 kb or >100 kb) and other characteristics, and 2) individual rare exonic CNVs and CNV regions.RESULTS: Patients with MDD carried significantly more short deletions than control subjects (p= .0059) but not long deletions or short or long duplications. The confidence interval for long deletions overlapped with that for short deletions, but long deletions were 70% less frequent genome-wide, reducing the power to detect increased burden. The increased burden of short deletions was primarily in intergenic regions. Short deletions in cases were also modestly enriched for high-confidence enhancer regions. No individual CNV achieved thresholds for suggestive or significant association after genome-wide correction. p values < .01 were observed for 15q11.2 duplications (TUBGCP5, CYFIP1, NIPA1, and NIPA2), deletions in or near PRKN or MSR1, and exonic duplications of ATG5.CONCLUSIONS: The increased burden of short deletions in patients with MDD suggests that rare CNVs increase the risk of MDD by disrupting regulatory regions. Results for longer deletions were less clear, but no large effects were observed for long multigenic CNVs (as seen in schizophrenia and autism). Further studies with larger sample sizes are warranted.

  View details for PubMedID 31003785

• Identification of common genetic risk variants for autism spectrum disorder NATURE GENETICS Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., Pallesen, J., Agerbo, E., Andreassen, O. A., Anney, R., Awashti, S., Belliveau, R., Bettella, F., Buxbaum, J. D., Bybjerg-Grauholm, J., Baekvad-Hansen, M., Cerrato, F., Chambert, K., Christensen, J. H., Churchhouse, C., Dellenvall, K., Demontis, D., De Rubeis, S., Devlin, B., Djurovic, S., Dumont, A. L., Goldstein, J., Hansen, C. S., Hauberg, M., Hollegaard, M., Hope, S., Howrigan, D. P., Huang, H., Hultman, C. M., Klei, L., Maller, J., Martin, J., Martin, A. R., Moran, J. L., Nyegaard, M., Naerland, T., Palmer, D. S., Palotie, A., Pedersen, C., Pedersen, M., dPoterba, T., Poulsen, J., St Pourcain, B., Qvist, P., Rehnstrom, K., Reichenberg, A., Reichert, J., Robinson, E. B., Roeder, K., Roussos, P., Saemundsen, E., Sandin, S., Satterstrom, F., Smith, G., Stefansson, H., Steinberg, S., Stevens, C. R., Sullivan, P. F., Turley, P., Walters, G., Xu, X., Stefansson, K., Geschwind, D. H., Nordentoft, M., Hougaard, D. M., Werge, T., Mors, O., Mortensen, P., Neale, B. M., Daly, M. J., Borglum, A. D., Wray, N. R., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Air, T. M., Andlauer, T. M., Bacanu, S., Beekman, A. F., Bigdeli, T. B., Binder, E. B., Blackwood, D. R., Bryois, J., Buttenschon, H. N., Cai, N., Castelao, E., Clarke, T., Coleman, J. R., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F., Finucane, H. K., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Hall, L. S., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Ising, M., Jansen, R., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Li, Y., Lind, P. A., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S., Sigurdsson, E., Sinnamon, G. B., Smit, J. H., Smith, D. J., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van Der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D., Cichon, S., Dannlowski, U., de Geus, E. C., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mueller-Myhsok, B., Noethen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Tiemeier, H., Uher, R., Voelzke, H., Weissman, M. M., Lewis, C. M., Levinson, D. F., Breen, G., Agee, M., Alipanahi, B., Auton, A., Bell, R. K., Bryc, K., Elson, S. L., Fontanillas, P., Furlotte, N. A., Hromatka, B. S., Huber, K. E., Kleinman, A., Litterman, N. K., McIntyre, M. H., Mountain, J. L., Noblin, E. S., Northover, C. M., Pitts, S. J., Sathirapongsasuti, J., Sazonova, O., Shelton, J. F., Shringarpure, S., Tung, J. Y., Vacic, V., Wilson, C. H., Psychiat Genomics Consortium, BUPGEN, 23andMe Res Team 2019; 51 (3): 431-+

  Abstract

  Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.

  View details for DOI 10.1038/s41588-019-0344-8

  View details for Web of Science ID 000459947200012

  View details for PubMedID 30804558

• Genome-wide by environment interaction studies of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland TRANSLATIONAL PSYCHIATRY Arnau-Soler, A., Macdonald-Dunlop, E., Adams, M. J., Clarke, T., MacIntyre, D. J., Milburn, K., Navrady, L., Hayward, C., McIntosh, A. M., Thomson, P. A., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Agerbo, E., Air, T. M., Andlauer, T. M., Bacanu, S., Baekvad-Hansen, M., Beekman, A. F., Bigdeli, T. B., Binder, E. B., Blackwood, D. R., Bryois, J., Buttenscon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J., Coleman, J. R., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Rawford, G. C., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F., Finucane, H. K., Foo, J. C., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hansen, C., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Ising, M., Jansen, R., Jones, I., Jones, L. A., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Li, Y., Lind, P. A., Macintyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C., Pedersen, M., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S., Sigurdsson, E., Sinnamon, G. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D., Cichon, S., Dannlowski, U., de Geus, E. C., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F., Magnusson, P. K., Martin, N. G., Metspalu, A., Mors, O., Mortensen, P., Mueller-Myhsok, B., Nordentoft, M., Noethen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Voelzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F., Generation Scotland, Psychiat Genomics Consortium 2019; 9: 14

  Abstract

  Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population-based cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77 × 10-6). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53-kb downstream PIWIL4; p = 4.95 × 10-9; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46 × 10-8; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00 × 10-8; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77 × 10-6). Polygenic risk scores (PRSs) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91 × 10-3). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.

  View details for DOI 10.1038/s41398-018-0360-y

  View details for Web of Science ID 000459834200001

  View details for PubMedID 30718454

  View details for PubMedCentralID PMC6361928

• Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences NATURE GENETICS Linner, R., Biroli, P., Kong, E., Meddens, F. W., Wedow, R., Fontana, M., Lebreton, M., Tino, S. P., Abdellaoui, A., Hammerschlag, A. R., Nivard, M. G., Okbay, A., Rietveld, C. A., Timshel, P. N., Trzaskowski, M., de Vlaming, R., Zund, C. L., Bao, Y., Buzdugan, L., Caplin, A. H., Chen, C., Eibich, P., Fontanillas, P., Gonzalez, J. R., Joshi, P. K., Karhunen, V., Kleinman, A., Levin, R. Z., Lill, C. M., Meddens, G. A., Muntane, G., Sanchez-Roige, S., van Rooij, F. J., Taskesen, E., Wu, Y., Zhang, F., Agee, M., Alipanahi, B., Bell, R. K., Bryc, K., Elson, S. L., Furlotte, N. A., Huber, K. E., Litterman, N. K., McCreight, J. C., McIntyre, M. H., Mountain, J. L., Northover, C. M., Pitts, S. J., Sathirapongsasuti, J., Sazonova, O. V., Shelton, J. F., Shringarpure, S., Tian, C., Tung, J. Y., Vacic, V., Wilson, C. H., Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Awadalla, P., Battle, A., Beutner, F., Bonder, M., Boomsma, D. I., Christiansen, M., Claringbould, A., Deelen, P., Esko, T., Fave, M., Franke, L., Frayling, T., Gharib, S. A., Gibson, G., Heijmans, B., Hemani, G., Jansen, R., Kahonen, M., Kalnapenkis, A., Kasela, S., Kettunen, J., Kim, Y., Kirsten, H., Kovacs, P., Krohn, K., Kronberg-Guzman, J., Kukushkina, V., Kutalik, Z., Lee, B., Lehtimaki, T., Loeffler, M., Marigorta, U. M., Metspalu, A., Milani, L., Montgomery, G. W., Mueller-Nurasyid, M., Nauck, M., Penninx, B., Perola, M., Pervjakova, N., Pierce, B., Powell, J., Prokisch, H., Psaty, B. M., Raitakari, O., Ring, S., Ripatti, S., Rotzchke, O., Rueger, S., Saha, A., Scholz, M., Schramm, K., Seppala, I., Stumvoll, M., Sullivan, P., Hoen, P., Teumer, A., Thiery, J., Tong, L., Tonjes, A., van Dongen, J., van Meurs, J., Verlouw, J., Visscher, P. M., Voelker, U., Vosa, U., Westra, H., Yaghootkar, H., Yang, J., Zeng, B., Lee, J. J., Pers, T. H., Turley, P., Chen, G., Emilsson, V., Oskarsson, S., Pickrell, J. K., Thom, K., Timshel, P., Ahluwalia, T. S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J. H., Concas, M., Derringer, J., Furlotte, N. A., Galesloot, T. E., Girotto, G., Gupta, R., Hall, L. M., Harris, S. E., Hofer, E., Horikoshi, M., Huffman, J. E., Kaasik, K., Kalafati, I. P., Kong, A., Lahti, J., van der Lee, S. J., de Leeuw, C., Lind, P. A., Lindgren, K., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M. B., van der Most, P. J., Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W. J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K. E., Shi, J., Smith, A. V., Poot, R. A., St Pourcain, B., Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B. Z., Amin, N., Bakshi, A., Baumeister, S. E., Biino, G., Bonnelykke, K., Boyle, P. A., Campbell, H., Cappuccio, F. P., Davies, G., De Neve, J., Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D. M., Faul, J. D., Feitosa, M. F., Forstner, A. J., Gandin, I., Gunnarsson, B., Halldorsson, B. V., Harris, T. B., Heath, A. C., Hocking, L. J., Holliday, E. G., Homuth, G., Horan, M. A., Hottenga, J., de Jager, P. L., Jugessur, A., Kaakinen, M. A., Kahonen, M., Kanoni, S., Keltigangas-Jarvinen, L., Kiemeney, L. M., Kolcic, I., Koskinen, S., Kraja, A. T., Kroh, M., Kutalik, Z., Latvala, A., Launer, L. J., Lebreton, M. P., Levinson, D. F., Lichtenstein, P., Lichtner, P., Liewald, D. M., Loukola, A., Madden, P. A., Magi, R., Maki-Opas, T., Marioni, R. E., Marques-Vidal, P., McMahon, G., Meisinger, C., Meitinger, T., Milaneschi, Y., Milani, L., Montgomery, G. W., Myhre, R., Nelson, C. P., Nyholt, D. R., Ollier, W. R., Palotie, A., Paternoster, L., Pedersen, N. L., Petrovic, K. E., Porteous, D. J., Raikkonen, K., Ring, S. M., Robino, A., Rostapshova, O., Rudan, I., Rustichini, A., Salomaa, V., Sanders, A. R., Sarin, A., Schmidt, H., Scott, R. J., Smith, B. H., Smith, J. A., Staessen, J. A., Steinhagen-Thiessen, E., Strauch, K., Terracciano, A., Tobin, M. D., Ulivi, S., Vaccargiu, S., Quaye, L., Venturini, C., Vinkhuyzen, A. E., Voelker, U., Voelzke, H., Vonk, J. M., Vozzi, D., Waage, J., Ware, E. B., Willemsen, G., Attia, J. R., Bennett, D. A., Berger, K., Bertram, L., Bisgaard, H., Boomsma, D. I., Borecki, I. B., Bultmann, U., Chabris, C. F., Cucca, F., Cusi, D., Deary, J., Dedoussis, G. V., van Duijn, C. M., Eriksson, J. G., Franke, B., Franke, L., Gasparini, P., Gejman, P. V., Gieger, C., Grabe, H., Gratten, J., Gudnason, V., van der Harst, P., Hayward, C., Hinds, D. A., Hoffmann, W., Hypponen, E., Iacono, W. G., Jacobsson, B., Jarvelin, M., Jockel, K., Kaprio, J., Kardia, S. R., Lehtimaki, T., Lehrer, S. F., Magnusson, P. E., Martin, N. G., McGue, M., Metspalu, A., Pendleton, N., Penninx, B., Perola, M., Pirastu, N., Pirastu, M., Polasek, O., Posthuma, D., Power, C., Province, M. A., Samani, N. J., Schlessinger, D., Schmidt, R., Sorensen, T. A., Spector, T. D., Stefansson, K., Thorsteinsdottir, U., Thurik, A., Timpson, N. J., Tiemeier, H., Tung, J. Y., Uitterlinden, A. G., Vitart, V., Vollenweider, P., Weir, D. R., Wilson, J. F., Wright, A. F., Conley, D. C., Krueger, R. F., Smith, G., Laibson, D. I., Medland, S. E., Yang, J., Johannesson, M., Visscher, P. M., Esko, T., Koellinger, P. D., Cesarini, D., Benjamin, D. J., Auton, A., Boardman, J. D., Clark, D. W., Conlin, A., Dolan, C. C., Fischbacher, U., Groenen, P. F., Harris, K., Hasler, G., Hofman, A., Ikram, M. A., Jain, S., Karlsson, R., Kessler, R. C., Kooyman, M., MacKillop, J., Mannikko, M., Morcillo-Suarez, C., McQueen, M. B., Schmidt, K. M., Smart, M. C., Sutter, M., Thurik, A., Uitterlinden, A. G., White, J., de Wit, H., Yang, J., Bertram, L., Boomsma, D. I., Esko, T., Fehr, E., Hinds, D. A., Johannesson, M., Kumari, M., Laibson, D., Magnusson, P. E., Meyer, M. N., Navarro, A., Palmer, A. A., Pers, T. H., Posthuma, D., Schunk, D., Stein, M. B., Svento, R., Tiemeier, H., Timmers, P. J., Turley, P., Ursano, R. J., Wagner, G. G., Wilson, J. F., Gratten, J., Lee, J. J., Cesarini, D., Benjamin, D. J., Koellinger, P. D., Beauchamp, J. P., 23and Me Res Team, eQTLgen Consortium, Int Cannabis Consortium, Soc Sci Genetic Association Con 2019; 51 (2): 245-+

  Abstract

  Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

  View details for DOI 10.1038/s41588-018-0309-3

  View details for Web of Science ID 000457314300011

  View details for PubMedID 30643258

• Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder. American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics Trzaskowski, M., Mehta, D., Peyrot, W. J., Hawkes, D., Davies, D., Howard, D. M., Kemper, K. E., Sidorenko, J., Maier, R., Ripke, S., Mattheisen, M., Baune, B. T., Grabe, H. J., Heath, A. C., Jones, L., Jones, I., Madden, P. A., McIntosh, A. M., Breen, G., Lewis, C. M., Borglum, A. D., Sullivan, P. F., Martin, N. G., Kendler, K. S., Levinson, D. F., Wray, N. R., Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium 2019

  Abstract

  Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between-cohort and between-sex heterogeneity. First, we used genome-wide association study (GWAS) summary statistics to investigate between-cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases=16,823, N controls=25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs. community sources). Second, we evaluated between-sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank, and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD.

  View details for PubMedID 30708398

• TRANSETHNIC ANALYSIS OF HIGH-RESOLUTION HLA ALLELES AND COMPLEMENT 4 STRUCTURAL POLYMORPHISMS IN SCHIZOPHRENIA Ollila, H., Li, M., Mindrinos, M., Wang, C., Fernandez-Vina, M., Kuehn, R., Krishnakumar, S., Wilhelmy, J., Tsuang, M. T., Glatt, S. J., Mignot, E., Levinson, D. F. ELSEVIER SCIENCE BV. 2019: S937

  View details for DOI 10.1016/j.euroneuro.2017.08.278

  View details for Web of Science ID 000462156400407

• Evidence for increased genetic risk load for major depression in patients assigned to electroconvulsive therapy AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Foo, J. C., Streit, F., Frank, J., Witt, S. H., Treutlein, J., Baune, B. T., Moebus, S., Joeckel, K., Forstner, A. J., Noethen, M. M., Rietschel, M., Sartorius, A., Kranaster, L., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. M., Bacanu, S., Baekvad-Hansen, M., Beekman, A. F., Bigdeli, T. B., Binder, E. B., Blackwood, D. R., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J., Clarke, T., Coleman, J. I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F., Finucane, H. K., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hansen, C., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Ising, M., Jansen, R., Jones, I., Jones, L. A., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Li, Y., Lind, P. A., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C., Pedersen, M., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S. I., Sigurdsson, E., Sinnamon, G. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Berger, K., Boomsma, D. I., Cichon, S., Dannlowski, U., de Geus, E. C., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P., Mueller-Myhsok, B., Nordentoft, M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Voelzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F., Major Depressive Disorder Worki 2019; 180 (1): 35–45

  Abstract

  Electroconvulsive therapy (ECT) is the treatment of choice for severe and treatment-resistant depression; disorder severity and unfavorable treatment outcomes are shown to be influenced by an increased genetic burden for major depression (MD). Here, we tested whether ECT assignment and response/nonresponse are associated with an increased genetic burden for major depression (MD) using polygenic risk score (PRS), which summarize the contribution of disease-related common risk variants. Fifty-one psychiatric inpatients suffering from a major depressive episode underwent ECT. MD-PRS were calculated for these inpatients and a separate population-based sample (n = 3,547 healthy; n = 426 self-reported depression) based on summary statistics from the Psychiatric Genomics Consortium MDD-working group (Cases: n = 59,851; Controls: n = 113,154). MD-PRS explained a significant proportion of disease status between ECT patients and healthy controls (p = .022, R2 = 1.173%); patients showed higher MD-PRS. MD-PRS in population-based depression self-reporters were intermediate between ECT patients and controls (n.s.). Significant associations between MD-PRS and ECT response (50% reduction in Hamilton depression rating scale scores) were not observed. Our findings indicate that ECT cohorts show an increased genetic burden for MD and are consistent with the hypothesis that treatment-resistant MD patients represent a subgroup with an increased genetic risk for MD. Larger samples are needed to better substantiate these findings.

  View details for DOI 10.1002/ajmg.b.32700

  View details for Web of Science ID 000454541200004

  View details for PubMedID 30507021

• GWAS of Suicide Attempt in Psychiatric Disorders and Association With Major Depression Polygenic Risk Scores. The American journal of psychiatry Mullins, N. n., Bigdeli, T. B., Børglum, A. D., Coleman, J. R., Demontis, D. n., Mehta, D. n., Power, R. A., Ripke, S. n., Stahl, E. A., Starnawska, A. n., Anjorin, A. n., Corvin, A. n., Sanders, A. R., Forstner, A. J., Reif, A. n., Koller, A. C., Świątkowska, B. n., Baune, B. T., Müller-Myhsok, B. n., Penninx, B. W., Pato, C. n., Zai, C. n., Rujescu, D. n., Hougaard, D. M., Quested, D. n., Levinson, D. F., Binder, E. B., Byrne, E. M., Agerbo, E. n., Streit, F. n., Mayoral, F. n., Bellivier, F. n., Degenhardt, F. n., Breen, G. n., Morken, G. n., Turecki, G. n., Rouleau, G. A., Grabe, H. J., Völzke, H. n., Jones, I. n., Giegling, I. n., Agartz, I. n., Melle, I. n., Lawrence, J. n., Walters, J. T., Strohmaier, J. n., Shi, J. n., Hauser, J. n., Biernacka, J. M., Vincent, J. B., Kelsoe, J. n., Strauss, J. S., Lissowska, J. n., Pimm, J. n., Smoller, J. W., Guzman-Parra, J. n., Berger, K. n., Scott, L. J., Jones, L. A., Azevedo, M. H., Trzaskowski, M. n., Kogevinas, M. n., Rietschel, M. n., Boks, M. n., Ising, M. n., Grigoroiu-Serbanescu, M. n., Hamshere, M. L., Leboyer, M. n., Frye, M. n., Nöthen, M. M., Alda, M. n., Preisig, M. n., Nordentoft, M. n., Boehnke, M. n., O'Donovan, M. C., Owen, M. J., Pato, M. T., Renteria, M. E., Budde, M. n., Weissman, M. M., Wray, N. R., Bass, N. n., Craddock, N. n., Smeland, O. B., Andreassen, O. A., Mors, O. n., Gejman, P. V., Sklar, P. n., McGrath, P. n., Hoffmann, P. n., McGuffin, P. n., Lee, P. H., Mortensen, P. B., Kahn, R. S., Ophoff, R. A., Adolfsson, R. n., Van der Auwera, S. n., Djurovic, S. n., Kloiber, S. n., Heilmann-Heimbach, S. n., Jamain, S. n., Hamilton, S. P., McElroy, S. L., Lucae, S. n., Cichon, S. n., Schulze, T. G., Hansen, T. n., Werge, T. n., Air, T. M., Nimgaonkar, V. n., Appadurai, V. n., Cahn, W. n., Milaneschi, Y. n., Fanous, A. H., Kendler, K. S., McQuillin, A. n., Lewis, C. M. 2019: appiajp201918080957

  Abstract

  More than 90% of people who attempt suicide have a psychiatric diagnosis; however, twin and family studies suggest that the genetic etiology of suicide attempt is partially distinct from that of the psychiatric disorders themselves. The authors present the largest genome-wide association study (GWAS) on suicide attempt, using cohorts of individuals with major depressive disorder, bipolar disorder, and schizophrenia from the Psychiatric Genomics Consortium.The samples comprised 1,622 suicide attempters and 8,786 nonattempters with major depressive disorder; 3,264 attempters and 5,500 nonattempters with bipolar disorder; and 1,683 attempters and 2,946 nonattempters with schizophrenia. A GWAS on suicide attempt was performed by comparing attempters to nonattempters with each disorder, followed by a meta-analysis across disorders. Polygenic risk scoring was used to investigate the genetic relationship between suicide attempt and the psychiatric disorders.Three genome-wide significant loci for suicide attempt were found: one associated with suicide attempt in major depressive disorder, one associated with suicide attempt in bipolar disorder, and one in the meta-analysis of suicide attempt in mood disorders. These associations were not replicated in independent mood disorder cohorts from the UK Biobank and iPSYCH. No significant associations were found in the meta-analysis of all three disorders. Polygenic risk scores for major depression were significantly associated with suicide attempt in major depressive disorder (R2=0.25%), bipolar disorder (R2=0.24%), and schizophrenia (R2=0.40%).This study provides new information on genetic associations and demonstrates that genetic liability for major depression increases risk for suicide attempt across psychiatric disorders. Further collaborative efforts to increase sample size may help to robustly identify genetic associations and provide biological insights into the etiology of suicide attempt.

  View details for DOI 10.1176/appi.ajp.2019.18080957

  View details for PubMedID 31164008

• MACHINE LEARNING ANALYSIS OF ULTRA-DEEP WHOLE-GENOME SEQUENCING IN HUMAN BRAIN REVEALS SOMATIC GENOMIC RETROTRANSPOSITION IN GLIA AS WELL AS IN NEURONS Urban, A., Zhu, X., Zhou, B., Sloan, S., Pattni, R., Fiston-Lavier, A., Snyder, M., Petrov, D., Abyzov, A., Vaccarino, F., Barres, B., Vogel, H., Tamminga, C., Levinson, D. ELSEVIER. 2019: 1240

  View details for DOI 10.1016/j.euroneuro.2018.08.316

  View details for Web of Science ID 000477708400398

• Genetic Correlation Profile of Schizophrenia Mirrors Epidemiological Results and Suggests Link Between Polygenic and Rare Variant (22q11.2) Cases of Schizophrenia SCHIZOPHRENIA BULLETIN Duncan, L. E., Shen, H., Ballon, J. S., Hardy, K. V., Noordsy, D. L., Levinson, D. F. 2018; 44 (6): 1350–61

  View details for DOI 10.1093/schbul/sbx174

  View details for Web of Science ID 000456691800023

• Genome-wide association study of seasonal affective disorder TRANSLATIONAL PSYCHIATRY Ho, K., Han, S., Nielsen, J. V., Jancic, D., Hing, B., Fiedorowicz, J., Weissman, M. M., Levinson, D. F., Potash, J. B. 2018; 8: 190

  Abstract

  Family and twin studies have shown a genetic component to seasonal affective disorder (SAD). A number of candidate gene studies have examined the role of variations within biologically relevant genes in SAD susceptibility, but few genome-wide association studies (GWAS) have been performed to date. The authors aimed to identify genetic risk variants for SAD through GWAS. The authors performed a GWAS for SAD in 1380 cases and 2937 controls of European-American (EA) origin, selected from samples for GWAS of major depressive disorder and of bipolar disorder. Further bioinformatic analyses were conducted to examine additional genomic and biological evidence associated with the top GWAS signals. No susceptibility loci for SAD were identified at a genome-wide significant level. The strongest association was at an intronic variant (rs139459337) within ZBTB20 (odds ratio (OR) = 1.63, p = 8.4 × 10-7), which encodes a transcriptional repressor that has roles in neurogenesis and in adult brain. Expression quantitative trait loci (eQTL) analysis showed that the risk allele "T" of rs139459337 is associated with reduced mRNA expression of ZBTB20 in human temporal cortex (p = 0.028). Zbtb20 is required for normal murine circadian rhythm and for entrainment to a shortened day. Of the 330 human orthologs of murine genes directly repressed by Zbtb20, there were 32 associated with SAD in our sample (at p < 0.05), representing a significant enrichment of ZBTB20 targets among our SAD genetic association signals (fold = 1.93, p = 0.001). ZBTB20 is a candidate susceptibility gene for SAD, based on a convergence of genetic, genomic, and biological evidence. Further studies are necessary to confirm its role in SAD.

  View details for PubMedID 30217971

• 1q21.1 microduplication: large verbal-nonverbal performance discrepancy and ddPCR assays of HYDIN/HYDIN2 copy number NPJ GENOMIC MEDICINE Xavier, J., Zhou, B., Bilan, F., Zhang, X., Gilbert-Dussardier, B., Viaux-Savelon, S., Pattni, R., Ho, S. S., Cohen, D., Levinson, D. F., Urbana, A. E., Laurent-Levinson, C. 2018; 3: 24

  Abstract

  Microduplication of chromosome 1q21.1 is observed in ~0.03% of adults. It has a highly variable, incompletely penetrant phenotype that can include intellectual disability, global developmental delay, specific learning disabilities, autism, schizophrenia, heart anomalies and dysmorphic features. We evaluated a 10-year-old-male with a 1q21.1 duplication by CGH microarray. He presented with major attention deficits, phonological dysphasia, poor fine motor skills, dysmorphia and mild autistic features, but not the typical macrocephaly. Neuropsychiatric evaluation demonstrated a novel phenotype: an unusually large discrepancy between non-verbal capacities (borderline-impaired WISC-IV index scores of 70 for Working Memory and 68 for Processing Speed) vs. strong verbal skills - scores of 126 for Verbal Comprehension (superior) and 111 for Perceptual Reasoning (normal). HYDIN2 has been hypothesized to underlie macrocephaly and perhaps cognitive deficits in this syndrome, but assessment of HYDIN2 copy number by microarray is difficult because of extensive segmental duplications. We performed whole-genome sequencing which supported HYDIN2 duplication (chr1:146,370,001-148,590,000, 2.22 Mb, hg38). To evaluate copy number more rigorously we developed droplet digital PCR assays of HYDIN2 (targeting unique 1 kb and 6 kb insertions) and its paralog HYDIN (targeting a unique 154 bp segment outside the HYDIN2 overlap). In an independent cohort, ddPCR was concordant with previous microarray data. Duplication of HYDIN2 was confirmed in the patient by ddPCR. This case demonstrates that a large discrepancy of verbal and non-verbal abilities can occur in 1q21.1 duplication syndrome, but it remains unclear whether this has a specific genomic basis. These ddPCR assays may be useful for future research on HYDIN2 copy number.

  View details for PubMedID 30155272

• Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals NATURE GENETICS Lee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Tuan Anh Nguyen-Viet, Bowers, P., Sidorenko, J., Linner, R., Fontana, M., Kundu, T., Lee, C., Li, H., Li, R., Royer, R., Timshel, P. N., Walters, R. K., Willoughby, E. A., Yengo, L., Alver, M., Bao, Y., Clark, D. W., Day, F. R., Furlotte, N. A., Joshi, P. K., Kemper, K. E., Kleinman, A., Langenberg, C., Magi, R., Trampush, J. W., Verma, S., Wu, Y., Lam, M., Zhao, J., Zheng, Z., Boardman, J. D., Campbell, H., Freese, J., Harris, K., Hayward, C., Herd, P., Kumari, M., Lencz, T., Luan, J., Malhotra, A. K., Metspalu, A., Milani, L., Ong, K. K., Perry, J. B., Porteous, D. J., Ritchie, M. D., Smart, M. C., Smith, B. H., Tung, J. Y., Wareham, N. J., Wilson, J. F., Beauchamp, J. P., Conley, D. C., Esko, T., Lehrer, S. F., Magnusson, P. E., Oskarsson, S., Pers, T. H., Robinson, M. R., Thom, K., Watson, C., Chabris, C. F., Meyer, M. N., Laibson, D. I., Yang, J., Johannesson, M., Koellinger, P. D., Turley, P., Visscher, P. M., Benjamin, D. J., Cesarini, D., 23Me Res Team, COGENT Cognitive Genomics Consorti, Social Sci Genetic Assoc Consortiu 2018; 50 (8): 1112-+

  Abstract

  Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

  View details for PubMedID 30038396

• Does Childhood Trauma Moderate Polygenic Risk for Depression? A Meta-analysis of 5765 Subjects From the Psychiatric Genomics Consortium BIOLOGICAL PSYCHIATRY Peyrot, W. J., Van der Auwera, S., Milaneschi, Y., Dolan, C. V., Madden, P. F., Sullivan, P. F., Strohmaier, J., Ripke, S., Rietschel, M., Nivard, M. G., Mullins, N., Montgomery, G. W., Henders, A. K., Heat, A. C., Fisher, H. L., Dunn, E. C., Byrne, E. M., Air, T. A., Depressive, M., Baune, B. T., Breen, G., Levinson, D. F., Lewis, C. M., Martin, N. G., Nelson, E. N., Boomsma, D. I., Grabe, H. J., Wray, N. R., Penninx, B. H., Disorder Working Grp Psychiatric G 2018; 84 (2): 138–47

  Abstract

  The heterogeneity of genetic effects on major depressive disorder (MDD) may be partly attributable to moderation of genetic effects by environment, such as exposure to childhood trauma (CT). Indeed, previous findings in two independent cohorts showed evidence for interaction between polygenic risk scores (PRSs) and CT, albeit in opposing directions. This study aims to meta-analyze MDD-PRS × CT interaction results across these two and other cohorts, while applying more accurate PRSs based on a larger discovery sample.Data were combined from 3024 MDD cases and 2741 control subjects from nine cohorts contributing to the MDD Working Group of the Psychiatric Genomics Consortium. MDD-PRS were based on a discovery sample of ∼110,000 independent individuals. CT was assessed as exposure to sexual or physical abuse during childhood. In a subset of 1957 cases and 2002 control subjects, a more detailed five-domain measure additionally included emotional abuse, physical neglect, and emotional neglect.MDD was associated with the MDD-PRS (odds ratio [OR] = 1.24, p = 3.6 × 10-5, R2 = 1.18%) and with CT (OR = 2.63, p = 3.5 × 10-18 and OR = 2.62, p = 1.4 ×10-5 for the two- and five-domain measures, respectively). No interaction was found between MDD-PRS and the two-domain and five-domain CT measure (OR = 1.00, p = .89 and OR = 1.05, p = .66).No meta-analytic evidence for interaction between MDD-PRS and CT was found. This suggests that the previously reported interaction effects, although both statistically significant, can best be interpreted as chance findings. Further research is required, but this study suggests that the genetic heterogeneity of MDD is not attributable to genome-wide moderation of genetic effects by CT.

  View details for PubMedID 29129318

• Catatonia in Children and Adolescents: A High Rate of Genetic Conditions JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY Raffin, M., Consoli, A., Giannitelli, M., Philippe, A., Keren, B., Bodeau, N., Levinson, D. F., Cohen, D., Laurent-Levinson, C. 2018; 57 (7): 518-+

  Abstract

  Pediatric catatonia is a rare and severe neuropsychiatric syndrome. We previously reported, in 58 children and adolescents with catatonia, a high prevalence (up to 20%) of medical conditions, some of which have specific treatments.1 Here we extend the cohort inclusion and report the first systematic molecular genetic data for this syndrome. Among the 89 patients consecutively admitted for catatonia (according to the pediatric catatonia rating scale)2 between 1993 and 2014, we identify 51 patients (57.3%) who had genetic laboratory testing, of whom 37 had single nucleotide polymorphism (SNP) microarray tests for CNVs and 14 had routine genetic explorations (karyotyping and searches for specific chromosomal abnormalities by fluorescence in situ hybridization [FISH]) or a specific diagnosis test based on clinical history. To assess the causality of observed genetic findings in each patient, we used a causality assessment score (CAUS)3 including 5 causality-support criteria on a 3-point scale (0 = absent; 1 = moderate; 2 = high): the existence of similar cases in the literature; the presence of a clinical contributing factor; the presence of a biological contributing factor; the presence of other paraclinical symptoms; and response to a specific treatment related to the suspected genetic or medical condition.

  View details for PubMedID 29960699

• Transdifferentiation of human adult peripheral blood T cells into neurons PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Tanabe, K., Ang, C., Chanda, S., Olmos, V., Haag, D., Levinson, D. F., Sudhof, T. C., Wernig, M. 2018; 115 (25): 6470–75

  View details for DOI 10.1073/pnas.1720273115

  View details for Web of Science ID 000435585200056

• Transdifferentiation of human adult peripheral blood T cells into neurons. Proceedings of the National Academy of Sciences of the United States of America Tanabe, K., Ang, C. E., Chanda, S., Olmos, V. H., Haag, D., Levinson, D. F., Sudhof, T. C., Wernig, M. 2018

  Abstract

  Human cell models for disease based on induced pluripotent stem (iPS) cells have proven to be powerful new assets for investigating disease mechanisms. New insights have been obtained studying single mutations using isogenic controls generated by gene targeting. Modeling complex, multigenetic traits using patient-derived iPS cells is much more challenging due to line-to-line variability and technical limitations of scaling to dozens or more patients. Induced neuronal (iN) cells reprogrammed directly from dermal fibroblasts or urinary epithelia could be obtained from many donors, but such donor cells are heterogeneous, show interindividual variability, and must be extensively expanded, which can introduce random mutations. Moreover, derivation of dermal fibroblasts requires invasive biopsies. Here we show that human adult peripheral blood mononuclear cells, as well as defined purified T lymphocytes, can be directly converted into fully functional iN cells, demonstrating that terminally differentiated human cells can be efficiently transdifferentiated into a distantly related lineage. T cell-derived iN cells, generated by nonintegrating gene delivery, showed stereotypical neuronal morphologies and expressed multiple pan-neuronal markers, fired action potentials, and were able to form functional synapses. These cells were stable in the absence of exogenous reprogramming factors. Small molecule addition and optimized culture systems have yielded conversion efficiencies of up to 6.2%, resulting in the generation of >50,000 iN cells from 1 mL of peripheral blood in a single step without the need for initial expansion. Thus, our method allows the generation of sufficient neurons for experimental interrogation from a defined, homogeneous, and readily accessible donor cell population.

  View details for PubMedID 29866841

• BUILDING A HIGH RESOLUTION HAPLOTYPE DATABASE FOR 11 HUMAN LEUKOCYTE ANTIGEN LOCI FROM FAMILY TRIOS Kountouris, E., Levinson, D., Fernandez-Vina, M. A., Ollila, H., Mignot, E., Tsuang, M., Glatt, S., Li, M., Mindrinos, M. WILEY. 2018: 435–36

  View details for Web of Science ID 000430290800240

• Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression NATURE GENETICS Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. F., Bacanu, S., Baekvad-Hansen, M., Beekman, A. T., Bigdeli, T. B., Binder, E. B., Blackwood, D. H., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J., Clarke, T., Coleman, J. R., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Crowley, C. A., Dashti, H. S., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Eriksson, N., Escott-Price, V., Kiadeh, F., Finucane, H. K., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Giusti-Rodriguez, P., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hannon, E., Hansen, C., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Hu, M., Hyde, C. L., Ising, M., Jansen, R., Jin, F., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Lane, J. M., Li, Y., Li, Y., Lind, P. A., Liu, X., Lu, L., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mill, J., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C., Pedersen, M., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Purcell, S. M., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S., Saxena, R., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S. I., Sigurdsson, E., Sinnamon, G. C., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Stockmeier, C. A., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Tian, C., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D. I., Cichon, S., Dannlowski, U., de Geus, E. J., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Hinds, D. A., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. A., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P., Mueller-Myhsok, B., Nordentoft, M., Noethen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Voelzke, H., Weissman, M. M., Werge, T., Winslow, A. R., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F., EQTLGEN, Major Depressive Disorder Working 2018; 50 (5): 668-+

  Abstract

  Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

  View details for PubMedID 29700475

• Genome-wide gene-environment interaction in depression: A systematic evaluation of candidate genes: The childhood trauma working-group of PGC-MDD AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Van der Auwera, S., Peyrot, W. J., Milaneschi, Y., Hertel, J., Baune, B., Breen, G., Byrne, E., Dunn, E. C., Fisher, H., Homuth, G., Levinson, D., Lewis, C., Mills, N., Mullins, N., Nauck, M., Pistis, G., Preisig, M., Rietschel, M., Ripke, S., Sullivan, P., Teumer, A., Voelzke, H., Boomsma, D. I., Wray, N. R., Penninx, B., Grabe, H., Psychiat Genomics Consortium 2018; 177 (1): 40–49

  Abstract

  Gene by environment (GxE) interaction studies have investigated the influence of a number of candidate genes and variants for major depressive disorder (MDD) on the association between childhood trauma and MDD. Most of these studies are hypothesis driven and investigate only a limited number of SNPs in relevant pathways using differing methodological approaches. Here (1) we identified 27 genes and 268 SNPs previously associated with MDD or with GxE interaction in MDD and (2) analyzed their impact on GxE in MDD using a common approach in 3944 subjects of European ancestry from the Psychiatric Genomics Consortium who had completed the Childhood Trauma Questionnaire. (3) We subsequently used the genome-wide SNP data for a genome-wide case-control GxE model and GxE case-only analyses testing for an enrichment of associated SNPs. No genome-wide significant hits and no consistency among the signals of the different analytic approaches could be observed. This is the largest study for systematic GxE interaction analysis in MDD in subjects of European ancestry to date. Most of the known candidate genes/variants could not be supported. Thus, their impact on GxE interaction in MDD may be questionable. Our results underscore the need for larger samples, more extensive assessment of environmental exposures, and greater efforts to investigate new methodological approaches in GxE models for MDD.

  View details for PubMedID 29159863

• Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder COMMUNICATIONS BIOLOGY de Jong, S., Abdalla Diniz, M., Saloma, A., Gadelha, A., Santoro, M. L., Ota, V. K., Noto, C., Curtis, C., Newhouse, S. J., Patel, H., Hall, L. S., O'Reilly, P. F., Belangero, S., Bressan, R. A., Breen, G., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. M., Bacanu, S., Baekvad-Hansen, M., Beekman, A. F., Bigdeli, T. B., Binder, E. B., Blackwood, D. R., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J., Clarke, T., Coleman, J. R., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F., Finucane, H. K., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Grove, J., Hansen, C., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J., Hougaard, D. M., Ising, M., Jansen, R., Jones, I., Jones, L. A., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Li, Y., Lind, P. A., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., Mcgrath, P., Mcguffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C., Pedersen, M., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S., Schoevers, R., Schulte, E. C., Shen, L., Shyn, S., Sigurdsson, E., Sinnamon, G. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D., Cichon, S., Dannlowski, U., de Geus, E. C., DePaulo, J., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P., Mueller-Myhsok, B., Nordentoft, M., Noethen, M. M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Voelzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Borglum, A. D., Sullivan, P. F., Meier, S., Strauss, J., Xu, W., Vincent, J. B., Matthews, K., Ferreira, M., O'Dushlaine, C., Purcell, S., Raychaudhuri, S., Ruderfer, D. M., Sklar, P., Scott, L. J., Flickinger, M., Burmeister, M., Li, J., Guan, W., Absher, D., Thompson, R. C., Meng, F., Schatzberg, A. F., Bunney, W. E., Barchas, J. D., Watson, S. J., Myers, R. M., Akil, H., Boehnke, M., Chambert, K., Moran, J., Scolnick, E., Djurovic, S., Melle, I., Morken, G., Corvin, A., Anjorin, A., Kandaswamy, R., Lawrence, J., McLean, A. W., Pickard, B. S., Bergen, S. E., Nimgaonkar, V., Landen, M., Schalling, M., Osby, U., Backlund, L., Frisen, L., Langstrom, N., Stahl, E., Dobbyn, A., Jamain, S., Etain, B., Bellivier, F., Leber, M., Maaser, A., Fischer, S. B., Reinbold, C. S., Kittel-Schneider, S., Fullerton, J. M., Oruc, L., Para, J. G., Mayoral, F., Rivas, F., Czerski, P. M., Kammerer-Ciernioch, J., Vedder, H., Borrmann-Hassenbach, M., Pfennig, A., Brennan, P., McKay, J. D., Kogevinas, M., Schwarz, M., Schofield, P. R., Muehleisen, T. W., Schumacher, J., Bauer, M., Wright, A., Mitchell, P. B., Hautzinger, M., Kelsoe, J. R., Greenwood, T. A., Nievergelt, C. M., Shilling, P. D., Smith, E. N., Bloss, C. S., Edenberg, H. J., Koller, D. L., Gershon, E. S., Liu, C., Badner, J. A., Scheftner, W. A., Lawson, W. B., Nwulia, E. A., Hipolito, M., Coryell, W., Rice, J., Byerley, W., McMahon, F. J., Lohoff, F. W., Zandi, P. P., Mahon, P. B., McInnis, M. G., Zollner, S., Zhang, P., Szelinger, S., St Clair, D., Caesar, S., Gordon-Smith, K., Fraser, C., Green, E. K., Grozeva, D., Hamshere, M. L., Kirov, G., Nikolov, I., Collier, D. A., Elkin, A., Williamson, R., Young, A. H., Ferrier, I., Milanova, V., Alda, M., Cervantes, P., Cruceanu, C., Rouleau, G. A., Turecki, G., Paciga, S., Winslow, A. R., Grigoroiu-Serbanescu, M., Ophoff, R., Adolfsson, R., Adolfsson, A., Del-Favero, J., Pato, C., Biernacka, J. M., Frye, M. A., Morris, D., Schork, N. J., Reif, A., Lissowska, J., Hauser, J., Szeszenia-Dabrowska, N., McGhee, K., Quinn, E., Moskvina, V., Holmans, P. A., Farmer, A., Kennedy, J. L., Andreassen, O. A., Mattingsdal, M., Bass, N. J., Gurling, H., McQuillin, A., Breuer, R., Hultman, C., Lichtenstein, P., Huckins, L. M., Leboyer, M., Lathrop, M., Nurnberger, J., Steffens, M., Foroud, T. M., Berrettini, W. H., Craig, D. W., Shi, J., Major Depressive Disorder Bipolar 2018; 1: 163

  Abstract

  Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.

  View details for DOI 10.1038/s42003-018-0155-y

  View details for Web of Science ID 000461126500163

  View details for PubMedID 30320231

  View details for PubMedCentralID PMC6175827

• Polygenic Scores for Major Depressive Disorder and Risk of Alcohol Dependence JAMA PSYCHIATRY Andersen, A. M., Pietrzak, R. H., Kranzler, H. R., Ma, L., Zhou, H., Liu, X., Kramer, J., Kuperman, S., Edenberg, H. J., Nurnberger, J. I., Rice, J. P., Tischfield, J. A., Goate, A., Foroud, T. M., Meyers, J. L., Porjesz, B., Dick, D. M., Hesselbrock, V., Boerwinkle, E., Southwick, S. M., Krystal, J. H., Weissman, M. M., Levinson, D. F., Potash, J. B., Gelernter, J., Han, S. 2017; 74 (11): 1153–60

  Abstract

  Major depressive disorder (MDD) and alcohol dependence (AD) are heritable disorders with significant public health burdens, and they are frequently comorbid. Common genetic factors that influence the co-occurrence of MDD and AD have been sought in family, twin, and adoption studies, and results to date have been promising but inconclusive.To examine whether AD and MDD overlap genetically, using a polygenic score approach.Association analyses were conducted between MDD polygenic risk score (PRS) and AD case-control status in European ancestry samples from 4 independent genome-wide association study (GWAS) data sets: the Collaborative Study on the Genetics of Alcoholism (COGA); the Study of Addiction, Genetics, and Environment (SAGE); the Yale-Penn genetic study of substance dependence; and the National Health and Resilience in Veterans Study (NHRVS). Results from a meta-analysis of MDD (9240 patients with MDD and 9519 controls) from the Psychiatric Genomics Consortium were applied to calculate PRS at thresholds from P < .05 to P ≤ .99 in each AD GWAS data set.Association between MDD PRS and AD.Participants analyzed included 788 cases (548 [69.5%] men; mean [SD] age, 38.2 [10.8] years) and 522 controls (151 [28.9.%] men; age [SD], 43.9 [11.6] years) from COGA; 631 cases (333 [52.8%] men; age [SD], 35.0 [7.7] years) and 756 controls (260 [34.4%] male; age [SD] 36.1 [7.7] years) from SAGE; 2135 cases (1375 [64.4%] men; age [SD], 39.4 [11.5] years) and 350 controls (126 [36.0%] men; age [SD], 43.5 [13.9] years) from Yale-Penn; and 317 cases (295 [93.1%] men; age [SD], 59.1 [13.1] years) and 1719 controls (1545 [89.9%] men; age [SD], 64.5 [13.3] years) from NHRVS. Higher MDD PRS was associated with a significantly increased risk of AD in all samples (COGA: best P = 1.7 × 10-6, R2 = 0.026; SAGE: best P = .001, R2 = 0.01; Yale-Penn: best P = .035, R2 = 0.0018; and NHRVS: best P = .004, R2 = 0.0074), with stronger evidence for association after meta-analysis of the 4 samples (best P = 3.3 × 10-9). In analyses adjusted for MDD status in 3 AD GWAS data sets, similar patterns of association were observed (COGA: best P = 7.6 × 10-6, R2 = 0.023; Yale-Penn: best P = .08, R2 = 0.0013; and NHRVS: best P = .006, R2 = 0.0072). After recalculating MDD PRS using MDD GWAS data sets without comorbid MDD-AD cases, significant evidence was observed for an association between the MDD PRS and AD in the meta-analysis of 3 GWAS AD samples without MDD cases (best P = .007).These results suggest that shared genetic susceptibility contributes modestly to MDD and AD comorbidity. Individuals with elevated polygenic risk for MDD may also be at risk for AD.

  View details for PubMedID 28813562

• AIM 6-LARGE SCALE WGS OF MULTIPLY AFFECTED PEDIGREES Gill, M., Corvin, A., Daly, M., Sullivan, P., Levinson, D. ELSEVIER SCIENCE BV. 2017: S414–S415

  View details for DOI 10.1016/j.euroneuro.2016.09.459

  View details for Web of Science ID 000413847300088

• CLINICALLY RELEVANT GENETIC VARIANTS: MODELS FOR UNDERSTANDING SCHIZOPHRENIA AND OTHER NEUROPSYCHIATRIC DISORDERS DUPLICATIONS AT 15Q11-Q13 IN SCHIZOPHRENIA AND NEURODEVELOPMENTAL DISORDERS Kirov, G., Isles, A., Ingason, A., Lowther, C., Walters, J., Bassett, A., Costain, G., Levinson, D., Gawlick, M., Degenhardt, F., Aleksic, B., Ahn, J., Ogilvie, C., Stefansson, K., Owen, M. ELSEVIER SCIENCE BV. 2017: S277

  View details for Web of Science ID 000413843800336

• GENETICS OF MAJOR DEPRESSION: PROBLEMS, HYPOTHESES, SOLUTIONS Levinson, D., Lewis, C. ELSEVIER SCIENCE BV. 2017: S118–S119

  View details for Web of Science ID 000413843800026

• META-ANALYSIS OF WHOLE BLOOD GENE EXPRESSION IN MAJOR DEPRESSION: IDENTIFYING COHERENT GENE NETWORKS Mostafavi, S., Jansen, R., Battle, A., Zhu, X., Shi, J., Montgomery, S., Urban, A., Weissman, M., Potash, J., van Grootheest, G., Smit, J., Sullivan, P., Levinson, D., Penninx, B. ELSEVIER SCIENCE BV. 2017: S288–S289

  View details for Web of Science ID 000413843800357

• THE SCIENCE OF THE PSYCHIATRIC GENOMICS CONSORTIUM (PART 1) Sullivan, P., Levinson, D., Gill, M. ELSEVIER SCIENCE BV. 2017: S359

  View details for DOI 10.1016/j.euroneuro.2016.09.377

  View details for Web of Science ID 000413847300006

• THE SCIENCE OF THE PSYCHIATRIC GENOMICS CONSORTIUM (PART 2) Sullivan, P., Smoller, J., Levinson, D. ELSEVIER SCIENCE BV. 2017: S414

  View details for DOI 10.1016/j.euroneuro.2016.09.458

  View details for Web of Science ID 000413847300087

• BRIEF ASSESSMENT OF MAJOR DEPRESSION FOR GENETIC STUDIES: VALIDATION OF CIDI-SF SCREENING WITH SCID INTERVIEWS Levinson, D., Potash, J., Mostafavi, S., Battle, A., Zhu, X., Weissman, M. ELSEVIER SCIENCE BV. 2017: S448

  View details for DOI 10.1016/j.euroneuro.2016.09.514

  View details for Web of Science ID 000413847300141

• INSIGHTS INTO THE GENETIC ARCHITECTURE AND MOLECULAR MARKERS OF MAJOR DEPRESSION FROM THE CONVERGE PROJECT Kendler, K., Edwards, A., Levinson, D. ELSEVIER SCIENCE BV. 2017: S114

  View details for Web of Science ID 000413843800017

• An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype BIOLOGICAL PSYCHIATRY Direk, N., Williams, S., Smith, J. A., Ripke, S., Air, T., Amare, A. T., Amin, N., Baune, B. T., Bennett, D. A., Blackwood, D. R., Boomsma, D., Breen, G., Buttenschon, H. N., Byrne, E. M., Borglum, A. D., Castelao, E., Cichon, S., Clarke, T., Cornelis, M. C., Dannlowski, U., De Jager, P. L., Demirkan, A., Domenici, E., van Duijn, C. M., Dunn, E. C., Eriksson, J. G., Esko, T., Faul, J. D., Ferrucci, L., Fornage, M., de Geus, E., Gill, M., Gordon, S. D., Grabe, H., van Grootheest, G., Hamilton, S. P., Hartman, C. A., Heath, A. C., Hek, K., Hofman, A., Homuth, G., Horn, C., Hottenga, J., Kardia, S. R., Kloiber, S., Koenen, K., Kutalik, Z., Ladwig, K., Lahti, J., Levinson, D. F., Lewis, C. M., Lewis, G., Li, Q. S., Llewellyn, D. J., Lucae, S., Lunetta, K. L., MacIntyre, D. J., Madden, P., Martin, N. G., McIntosh, A. M., Metspalu, A., Milaneschi, Y., Montgomery, G. W., Mors, O., Mosley, T. H., Murabito, J. M., Mueller-Myhsok, B., Nothen, M. M., Nyholt, D. R., O'Donovan, M. C., Penninx, B. W., Pergadia, M. L., Perlis, R., Potash, J. B., Preisig, M., Purcell, S. M., Quiroz, J. A., Raikkonen, K., Rice, J. P., Rietschel, M., Rivera, M., Schulze, T. G., Shi, J., Shyn, S., Sinnamon, G. C., Smit, J. H., Smoller, J. W., Snieder, H., Tanaka, T., Tansey, K. E., Teumer, A., Uher, R., Umbricht, D., Van der Auwera, S., Ware, E. B., Weir, D. R., Weissman, M. M., Willemsen, G., Yang, J., Zhao, W., Tiemeier, H., Sullivan, P. F. 2017; 82 (5): 322–29

  Abstract

  The genetics of depression has been explored in genome-wide association studies that focused on either major depressive disorder or depressive symptoms with mostly negative findings. A broad depression phenotype including both phenotypes has not been tested previously using a genome-wide association approach. We aimed to identify genetic polymorphisms significantly associated with a broad phenotype from depressive symptoms to major depressive disorder.We analyzed two prior studies of 70,017 participants of European ancestry from general and clinical populations in the discovery stage. We performed a replication meta-analysis of 28,328 participants. Single nucleotide polymorphism (SNP)-based heritability and genetic correlations were calculated using linkage disequilibrium score regression. Discovery and replication analyses were performed using a p-value-based meta-analysis. Lifetime major depressive disorder and depressive symptom scores were used as the outcome measures.The SNP-based heritability of major depressive disorder was 0.21 (SE = 0.02), the SNP-based heritability of depressive symptoms was 0.04 (SE = 0.01), and their genetic correlation was 1.001 (SE = 0.2). We found one genome-wide significant locus related to the broad depression phenotype (rs9825823, chromosome 3: 61,082,153, p = 8.2 × 10-9) located in an intron of the FHIT gene. We replicated this SNP in independent samples (p = .02) and the overall meta-analysis of the discovery and replication cohorts (1.0 × 10-9).This large study identified a new locus for depression. Our results support a continuum between depressive symptoms and major depressive disorder. A phenotypically more inclusive approach may help to achieve the large sample sizes needed to detect susceptibility loci for depression.

  View details for PubMedID 28049566

• Allele-specific expression reveals interactions between genetic variation and environment. Nature methods Knowles, D. A., Davis, J. R., Edgington, H., Raj, A., Favé, M., Zhu, X., Potash, J. B., Weissman, M. M., Shi, J., Levinson, D. F., Awadalla, P., Mostafavi, S., Montgomery, S. B., Battle, A. 2017

  Abstract

  Identifying interactions between genetics and the environment (GxE) remains challenging. We have developed EAGLE, a hierarchical Bayesian model for identifying GxE interactions based on associations between environmental variables and allele-specific expression. Combining whole-blood RNA-seq with extensive environmental annotations collected from 922 human individuals, we identified 35 GxE interactions, compared with only four using standard GxE interaction testing. EAGLE provides new opportunities for researchers to identify GxE interactions using functional genomic data.

  View details for DOI 10.1038/nmeth.4298

  View details for PubMedID 28530654

• An overview of medical risk factors for childhood psychosis: Implications for research and treatment. Schizophrenia research Giannitelli, M., Consoli, A., Raffin, M., Jardri, R., Levinson, D. F., Cohen, D., Laurent-Levinson, C. 2017

  Abstract

  Psychotic disorders in childhood and early adolescence often progress to chronic schizophrenia, but in many cases there are diagnosable medical and genetic causes or risk factors. We reviewed our clinical experience and the relevant literature to identify these factors and to define their clinical features, appropriate work-up and treatment.We reviewed the results of comprehensive medical evaluations of 160 psychotic children and adolescents in our center. We also searched the Medline database (January 1994 to December 2015) with the following keywords and combinations: early onset schizophrenia, childhood onset schizophrenia, early onset psychosis, first episode psychosis, inborn errors of metabolism (IEM), genetic syndrome, copy number variants, autoimmune disorders, endocrine diseases, nutritional deficiencies, central nervous system infections, movement disorders, and epilepsy.In our center, 12.5% of cases had medical disorders likely to be contributing to psychosis. Based on 66 relevant papers and our experience, we describe the clinical features of multiple genetic syndromes, IEM, and autoimmune, neurological, endocrinological and nutritional disorders that increase the risk of psychotic disorders in childhood and adolescence. We propose an algorithm for systematic laboratory evaluation, informed by clinical examination, emphasizing common and/or treatable factors.In children and early adolescents with psychotic disorders, systematic medical work-up is warranted to identify medical and genetic factors. Not every rare cause can be worked up, thus careful clinical examinations are required to detect medical, neurological and genetic signs. Comprehensive medical evaluation can detect treatable diseases among cases of early-onset psychosis.

  View details for DOI 10.1016/j.schres.2017.05.011

  View details for PubMedID 28526280

• Genetic effects influencing risk for major depressive disorder in China and Europe TRANSLATIONAL PSYCHIATRY Bigdeli, T. B., Ripke, S., Peterson, R. E., Trzaskowski, M., Bacanu, S., Abdellaoui, A., Andlauer, T. F., Beekman, A. T., Berger, K., Blackwood, D. H., Boomsma, D. I., Breen, G., Buttenschon, H. N., Byrne, E. M., Cichon, S., Clarke, T., Couvy-Duchesne, B., Craddock, N., de Geus, E. J., Degenhardt, F., Dunn, E. C., Edwards, A. C., Fanous, A. H., Forstner, A. J., Frank, J., Gill, M., Gordon, S. D., Grabe, H. J., Hamilton, S. P., Hardiman, O., Hayward, C., Heath, A. C., Henders, A. K., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Hottenga, J., Ising, M., Jansen, R., Kloiber, S., Knowles, J. A., Lang, M., Li, Q. S., Lucae, S., MACINTYRE, D. J., Madden, P. A., Martin, N. G., McGrath, P. J., McGuffin, P., McIntosh, A. M., Medland, S. E., Mehta, D., Middeldorp, C. M., Milaneschi, Y., Montgomery, G. W., Mors, O., Mueller-Myhsok, B., Nauck, M., Nyholt, D. R., Noethen, M. M., Owen, M. J., Penninx, B. W., Pergadia, M. L., Perlis, R. H., Peyrot, W. J., Porteous, D. J., Potash, J. B., RICE, J. P., Rietschel, M., Riley, B. P., Rivera, M., Schoevers, R., Schulze, T. G., Shi, J., Shyn, S. I., Smit, J. H., Smoller, J. W., Streit, F., Strohmaier, J., Teumer, A., Treutlein, J., Van der Auwera, S., van Grootheest, G., van Hemert, A. M., Voelzke, H., Webb, B. T., Weissman, M. M., Wellmann, J., Willemsen, G., Witt, S. H., Levinson, D. F., Lewis, C. M., Wray, N. R., Flint, J., Sullivan, P. F., Kendler, K. S. 2017; 7

  Abstract

  Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

  View details for DOI 10.1038/tp.2016.292

  View details for Web of Science ID 000397770800004

  View details for PubMedID 28350396

• Genome-wide Association for Major Depression Through Age at Onset Stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium BIOLOGICAL PSYCHIATRY Power, R. A., Tansey, K. E., Buttenschon, H. N., Cohen-Woods, S., Bigdeli, T., Hall, L. S., Kutalik, Z., Lee, S. H., Ripke, S., Steinberg, S., Teumer, A., Viktorin, A., Wray, N. R., Arolt, V., Baune, B. T., Boomsma, D. I., Borglum, A. D., Byrne, E. M., Castelao, E., Craddock, N., Craig, I. W., Dannlowski, U., Deary, I. J., Degenhardt, F., Forstner, A. J., Gordon, S. D., Grabe, H. J., Grove, J., Hamilton, S. P., Hayward, C., Heath, A. C., Hocking, L. J., Homuth, G., Hottenga, J. J., Kloiber, S., Krogh, J., Landen, M., Lang, M., Levinson, D. F., Lichtenstein, P., Lucae, S., MacIntyre, D. J., Madden, P., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Middeldorp, C. M., Milaneschi, Y., Montgomery, G. W., Mors, O., Muller-Myhsok, B., Nyholt, D. R., Oskarsson, H., Owen, M. J., Padmanabhan, S., Penninx, B. W., Pergadia, M. L., Porteous, D. J., Potash, J. B., Preisig, M., Rivera, M., Shi, J., Shyn, S. I., Sigurdsson, E., Smit, J. H., Smith, B. H., Stefansson, H., Stefansson, K., Strohmaier, J., Sullivan, P. F., Thomson, P., Thorgeirsson, T. E., Van der Auwera, S., Weissman, M. M., Breen, G., Lewis, C. M. 2017; 81 (4): 325-335

  Abstract

  Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset.Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer's disease, and coronary artery disease.We identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11-1.21, p = 5.2 × 10(-11)). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD.We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder.

  View details for DOI 10.1016/j.biopsych.2016.05.010

  View details for Web of Science ID 000397013500012

• Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects NATURE GENETICS Marshall, C. R., Marshall, C. R., Howrigan, D. P., Merico, D., Thiruvahindrapuram, B., Wu, W., Greer, D. S., Antaki, D., Shetty, A., Holmans, P. A., Pinto, D., Gujral, M., Brandler, W. M., Malhotra, D., Wang, Z., Fajarado, K. V., Maile, M. S., Ripke, S., Agartz, I., Albus, M., Alexander, M., Amin, F., Atkins, J., Bacanu, S. A., Belliveau, R. A., Bergen, S. E., Ertalan, M., Bevilacqua, E., Bigdeli, T. B., Black, D. W., Bruggeman, R., Buccola, N. G., Buckner, R. L., Bulik-Sullivan, B., Byerley, W., Cahn, W., Cai, G., Cairns, M. J., Campion, D., Cantor, R. M., Carr, V. J., Carrera, N., Catts, S. V., Chambert, K. D., Cheng, W., Cloninger, C. R., Cohen, D., Cormican, P., Craddock, N., Crespo-Facorro, B., Crowley, J. J., Curtis, D., Davidson, M., Davis, K. L., Degenhardt, F., Del Favero, J., DeLisi, L. E., Dikeos, D., Dinan, T., Djurovic, S., Donohoe, G., Drapeau, E., Duan, J., Dudbridge, F., Eichhammer, P., Eriksson, J., Escott-Price, V., Essioux, L., Fanous, A. H., Farh, K., Farrell, M. S., Frank, J., Franke, L., Freedman, R., Freimer, N. B., Friedman, J. I., Forstner, A. J., Fromer, M., Genovese, G., Georgieva, L., Gershon, E. S., Giegling, I., Giusti-Rodriguez, P., Godard, S., Goldstein, J. I., Gratten, J., de Haan, L., Hamshere, M. L., Hansen, M., Hansen, T., Haroutunian, V., Hartmann, A. M., Henskens, F. A., Herms, S., Hirschhorn, J. N., Hoffinann, P., Hofman, A., Huang, H., Ikeda, M., Joa, I., Kahler, A. K., Kahn, R. S., Kalaydjieva, L., Karjalainen, J., Kavanagh, D., Keller, M. C., Kelly, B. J., Kennedy, J. L., Kim, Y., Knowles, J. A., Konte, B., Laurent, C., Lee, P., Lee, S. H., Legge, S. E., Lerer, B., Levy, D. L., Liang, K., Lieberman, J., Lonnqvist, J., Loughland, C. M., Magnusson, P. K., Maher, B. S., Maier, W., Mallet, J., Mattheisen, M., Mattingsdal, M., McCarley, R. W., McDonald, C., McIntosh, A. M., Meier, S., Meijer, C. J., Melle, I., Mesholam-Gately, R. I., Metspalu, A., Michie, P. T., Milani, L., Milanova, V., Mokrab, Y., Morris, D. W., Muller-Myhsok, B., Murphy, K. C., Murray, R. M., Myin-Germeys, I., Nenadic, I., Nertney, D. A., Nestadt, G., Nicodemus, K. K., Nisenbaum, L., Nordin, A., O'Callaghan, E., O'Dushlaine, C., Oh, S., Olincy, A., Olsen, L., O'Neill, F. A., van Os, J., Pantelis, C., Papadimitriou, G. N., Parkhomenko, E., Pato, M. T., Paunio, T., Perkins, D. O., Pers, T. H., Pietilainen, O., Pimm, J., Pocklington, A. J., Powell, J., Price, A., Pulver, A. E., Purcell, S. M., Quested, D., Rasmussen, H. B., Reichenberg, A., Reimers, M. A., Richards, A. L., Roffman, J. L., Roussos, P., Ruderfer, D. M., Salomaa, V., Sanders, A. R., Savitz, A., Schall, U., Schulze, T. G., Schwab, S. G., Scolnick, E. M., Scott, R. J., Seidman, L. J., Shi, J., Silverman, J. M., Smoller, J. W., Soderman, E., Spencer, C. C., Stahl, E. A., Strengman, E., Strohmaier, J., Stroup, T. S., Suvisaari, J., Svrakic, D. M., Szatkiewicz, J. P., Thirumalai, S., Tooney, P. A., Veijola, J., Visscher, P. M., Waddington, J., Walsh, D., Webb, B. T., Weiser, M., Wildenauer, D. B., Williams, N. M., Williams, S., Witt, S. H., Wolen, A. R., Wormley, B. K., Wray, N. R., Wu, J. Q., Zai, C. C., Adolfsson, R., Andreassen, O. A., Blackwood, D. H., Bramon, E., Buxbaum, J. D., Cichon, S., Collier, D. A., Corvin, A., Daly, M. J., Darvasi, A., Domenici, E., Esko, T., Gejman, P. V., Gill, M., Gurling, H., Hultman, C. M., Iwata, N., Jablensky, A. V., Jonsson, E. G., Kendler, K. S., Kirov, G., Knight, J., Levinson, D. F., Li, Q. S., McCarroll, S. A., McQuillin, A., Moran, J. L., Mowry, B. J., Nothen, M. M., Ophoff, R. A., Owen, M. J., Palotie, A., Pato, C. N., Petryshen, T. L., Posthuma, D., Rietschel, M., Riley, B. P., Rujescu, D., Sklar, P., St Clair, D., Walters, J. T., Werge, T., Siillivan, P. F., O'Donovan, M. C., Scherer, S. W., Neale, B. M., Sebat, J. 2017; 49 (1): 27-35

  Abstract

  Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10(-15)), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10(-6)). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10(-11)) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10(-5)). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

  View details for DOI 10.1038/ng.3725

  View details for PubMedID 27869829

• Genetic Correlation Profile of Schizophrenia Mirrors Epidemiological Results and Suggests Link Between Polygenic and Rare Variant (22q11.2) Cases of Schizophrenia. Schizophrenia bulletin Duncan, L. E., Shen, H. n., Ballon, J. S., Hardy, K. V., Noordsy, D. L., Levinson, D. F. 2017

  Abstract

  New methods in genetics research, such as linkage disequilibrium score regression (LDSR), quantify overlap in the common genetic variants that influence diverse phenotypes. It is becoming clear that genetic effects often cut across traditional diagnostic boundaries. Here, we introduce genetic correlation analysis (using LDSR) to a nongeneticist audience and report transdisciplinary discoveries about schizophrenia. This analytical study design used publically available genome wide association study (GWAS) data from approximately 1.5 million individuals. Genetic correlations between schizophrenia and 172 medical, psychiatric, personality, and metabolomic phenotypes were calculated using LDSR, as implemented in LDHub in order to identify known and new genetic correlations. Consistent with previous research, the strongest genetic correlation was with bipolar disorder. Positive genetic correlations were also found between schizophrenia and all other psychiatric phenotypes tested, the personality traits of neuroticism and openness to experience, and cigarette smoking. Novel results were found with medical phenotypes: schizophrenia was negatively genetically correlated with serum citrate, positively correlated with inflammatory bowel disease, and negatively correlated with BMI, hip, and waist circumference. The serum citrate finding provides a potential link between rare cases of schizophrenia (strongly influenced by 22q11.2 deletions) and more typical cases of schizophrenia (with polygenic influences). Overall, these genetic correlation findings match epidemiological findings, suggesting that common variant genetic effects are part of the scaffolding underlying phenotypic comorbidity. The "genetic correlation profile" is a succinct report of shared genetic effects, is easily updated with new information (eg, from future GWAS), and should become part of basic disease knowledge about schizophrenia.

  View details for PubMedID 29294133

• Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data PLOS GENETICS Shi, J., Park, J., Duan, J., Berndt, S. T., Moy, W., Yu, K., Song, L., Wheeler, W., Hua, X., Silverman, D., Garcia-Closas, M., Hsiung, C. A., Figueroa, J. D., Cortessis, V. K., Malats, N., Karagas, M. R., Vineis, P., Chang, I., Lin, D., Zhou, B., Seow, A., Matsuo, K., Hong, Y., Caporaso, N. E., Wolpin, B., Jacobs, E., Petersen, G. M., Klein, A. P., Li, D., Risch, H., Sanders, A. R., Hsu, L., Schoen, R. E., Brenner, H., Stolzenberg-Solomon, R., Gejman, P., Lan, Q., Rothman, N., Amundadottir, L. T., Landi, M. T., Levinson, D. F., Chanock, S. J., Chatterjee, N. 2016; 12 (12)

  Abstract

  Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

  View details for DOI 10.1371/journal.pgen.1006493

  View details for PubMedID 28036406

• Impact of the X Chromosome and sex on regulatory variation GENOME RESEARCH Kukurba, K. R., Parsana, P., Balliu, B., Smith, K. S., Zappala, Z., Knowles, D. A., Fave, M., Davis, J. R., Li, X., Zhu, X., Potash, J. B., Weissman, M. M., Shi, J., Kundaje, A., Levinson, D. F., Awadalla, P., Mostafavi, S., Battle, A., Montgomery, S. B. 2016; 26 (6): 768-777

  Abstract

  The X Chromosome, with its unique mode of inheritance, contributes to differences between the sexes at a molecular level, including sex-specific gene expression and sex-specific impact of genetic variation. Improving our understanding of these differences offers to elucidate the molecular mechanisms underlying sex-specific traits and diseases. However, to date, most studies have either ignored the X Chromosome or had insufficient power to test for the sex-specific impact of genetic variation. By analyzing whole blood transcriptomes of 922 individuals, we have conducted the first large-scale, genome-wide analysis of the impact of both sex and genetic variation on patterns of gene expression, including comparison between the X Chromosome and autosomes. We identified a depletion of expression quantitative trait loci (eQTL) on the X Chromosome, especially among genes under high selective constraint. In contrast, we discovered an enrichment of sex-specific regulatory variants on the X Chromosome. To resolve the molecular mechanisms underlying such effects, we generated chromatin accessibility data through ATAC-sequencing to connect sex-specific chromatin accessibility to sex-specific patterns of expression and regulatory variation. As sex-specific regulatory variants discovered in our study can inform sex differences in heritable disease prevalence, we integrated our data with genome-wide association study data for multiple immune traits identifying several traits with significant sex biases in genetic susceptibilities. Together, our study provides genome-wide insight into how genetic variation, the X Chromosome, and sex shape human gene regulation and disease.

  View details for DOI 10.1101/gr.197897.115

  View details for PubMedID 27197214

• Genome-wide association study identifies 74 loci associated with educational attainment NATURE Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G., Emilsson, V., Meddens, S. F., Oskarsson, S., Pickrell, J. K., Thom, K., Timshel, P., de Vlaming, R., Abdellaoui, A., Ahluwalia, T. S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J. H., Concas, M. P., Derringer, J., Furlotte, N. A., Galesloot, T. E., Girotto, G., Gupta, R., Hall, L. M., Harris, S. E., Hofer, E., Horikoshi, M., Huffman, J. E., Kaasik, K., Kalafati, I. P., Karlsson, R., Kong, A., Lahti, J., van der Lee, S. J., de Leeuw, C., Lind, P. A., Lindgren, K., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M. B., van der Most, P. J., Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W. J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K. E., Shi, J., Smith, A. V., Poot, R. A., St Pourcain, B., Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B. Z., Amin, N., Bakshi, A., Baumeister, S. E., Biino, G., Bonnelykke, K., Boyle, P. A., Campbell, H., Cappuccio, F. P., Davies, G., De Neve, J., Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D. M., Faul, J. D., Feitosa, M. F., Forstner, A. J., Gandin, I., Gunnarsson, B., Halldorsson, B. V., Harris, T. B., Heath, A. C., Hocking, L. J., Holliday, E. G., Homuth, G., Horan, M. A., Hottenga, J., De Jager, P. L., Joshi, P. K., Jugessur, A., Kaakinen, M. A., Kahonen, M., Kanoni, S., Keltigangas-Jarvinen, L., Kiemeney, L. A., Kolcic, I., Koskinen, S., Kraja, A. T., Kroh, M., Kutalik, Z., Latvala, A., Launer, L. J., Lebreton, M. P., Levinson, D. F., Lichtenstein, P., Lichtner, P., Liewald, D. C., Loukola, A., Madden, P. A., Magi, R., Maki-Opas, T., Marioni, R. E., Marques-Vidal, P., Meddens, G. A., McMahon, G., Meisinger, C., Meitinger, T., Milaneschi, Y., Milani, L., Montgomery, G. W., Myhre, R., Nelson, C. P., Nyholt, D. R., Ollier, W. E., Palotie, A., Paternoster, L., Pedersen, N. L., Petrovic, K. E., Porteous, D. J., Raikkonen, K., Ring, S. M., Robino, A., Rostapshova, O., Rudan, I., Rustichini, A., Salomaa, V., Sanders, A. R., Sarin, A., Schmidt, H., Scott, R. J., Smith, B. H., Smith, J. A., Staessen, J. A., Steinhagen-Thiessen, E., Strauch, K., Terracciano, A., Tobin, M. D., Ulivi, S., Vaccargiu, S., Quaye, L., van Rooij, F. J., Venturini, C., Vinkhuyzen, A. A., Volker, U., Volzke, H., Vonk, J. M., Vozzi, D., Waage, J., Ware, E. B., Willemsen, G., Attia, J. R., Bennett, D. A., Berger, K., Bertram, L., Bisgaard, H., Boomsma, D. I., Borecki, I. B., Bultmann, U., Chabris, C. F., Cucca, F., Cusi, D., Deary, I. J., Dedoussis, G. V., van Duijn, C. M., Eriksson, J. G., Franke, B., Franke, L., Gasparini, P., Gejman, P. V., Gieger, C., Grabe, H., Gratten, J., Groenen, P. J., Gudnason, V., van der Harst, P., Hayward, C., Hinds, D. A., Hoffmann, W., Hyppnen, E., Iacono, W. G., Jacobsson, B., Jarvelin, M., Jockel, K., Kaprio, J., Kardia, S. L., Lehtimaki, T., Lehrer, S. F., Magnusson, P. K., Martin, N. G., McGue, M., Metspalu, A., Pendleton, N., Penninx, B. W., Perola, M., Pirastu, N., Pirastu, M., Polasek, O., Posthuma, D., Power, C., Province, M. A., Samani, N. J., Schlessinger, D., Schmidt, R., Sorensen, T. I., Spector, T. D., Stefansson, K., Thorsteinsdottir, U., Thurik, A. R., Timpson, N. J., Tiemeier, H., Tung, J. Y., Uitterlinden, A. G., Vitart, V., Vollenweider, P., Weir, D. R., Wilson, J. F., Wright, A. F., Conley, D. C., Krueger, R. F., Smith, G. D., Hofman, A., Laibson, D. I., Medland, S. E., Meyer, M. N., Yang, J., Johannesson, M., Visscher, P. M., Esko, T., Koellinger, P. D., Cesarini, D., Benjamin, D. J. 2016; 533 (7604): 539-?

  Abstract

  Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

  View details for DOI 10.1038/nature17671

  View details for PubMedID 27225129

• Genome-wide Association for Major Depression Through Age at Onset Stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. Biological psychiatry Power, R. A., Tansey, K. E., Buttenschøn, H. N., Cohen-Woods, S., Bigdeli, T., Hall, L. S., Kutalik, Z., Lee, S. H., Ripke, S., Steinberg, S., Teumer, A., Viktorin, A., Wray, N. R., Arolt, V., Baune, B. T., Boomsma, D. I., Børglum, A. D., Byrne, E. M., Castelao, E., Craddock, N., Craig, I. W., Dannlowski, U., Deary, I. J., Degenhardt, F., Forstner, A. J., Gordon, S. D., Grabe, H. J., Grove, J., Hamilton, S. P., Hayward, C., Heath, A. C., Hocking, L. J., Homuth, G., Hottenga, J. J., Kloiber, S., Krogh, J., Landén, M., Lang, M., Levinson, D. F., Lichtenstein, P., Lucae, S., MacIntyre, D. J., Madden, P., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Middeldorp, C. M., Milaneschi, Y., Montgomery, G. W., Mors, O., Müller-Myhsok, B., Nyholt, D. R., Oskarsson, H., Owen, M. J., Padmanabhan, S., Penninx, B. W., Pergadia, M. L., Porteous, D. J., Potash, J. B., Preisig, M., Rivera, M., Shi, J., Shyn, S. I., Sigurdsson, E., Smit, J. H., Smith, B. H., Stefansson, H., Stefansson, K., Strohmaier, J., Sullivan, P. F., Thomson, P., Thorgeirsson, T. E., Van der Auwera, S., Weissman, M. M., Breen, G., Lewis, C. M. 2016

  Abstract

  Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset.Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer's disease, and coronary artery disease.We identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11-1.21, p = 5.2 × 10(-11)). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD.We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder.

  View details for DOI 10.1016/j.biopsych.2016.05.010

  View details for PubMedID 27519822

• Parental Origin of Interstitial Duplications at 15q11.2-q13.3 in Schizophrenia and Neurodevelopmental Disorders PLOS GENETICS Isles, A. R., Ingason, A., Lowther, C., Walters, J., Gawlick, M., Stoeber, G., Rees, E., Martin, J., Little, R. B., Potter, H., Georgieva, L., Pizzo, L., Ozaki, N., Aleksic, B., Kushima, I., Ikeda, M., Iwata, N., Levinson, D. F., Gejman, P. V., Shi, J., Sanders, A. R., Duan, J., Willis, J., Sisodiya, S., Costain, G., Werge, T. M., Degenhardt, F., Giegling, I., Rujescu, D., Hreidarsson, S. J., Saemundsen, E., Ahn, J. W., Ogilvie, C., Girirajan, S. D., Stefansson, H., Stefansson, K., O'Donovan, M. C., Owen, M. J., Bassett, A., Kirov, G. 2016; 12 (5)

  Abstract

  Duplications at 15q11.2-q13.3 overlapping the Prader-Willi/Angelman syndrome (PWS/AS) region have been associated with developmental delay (DD), autism spectrum disorder (ASD) and schizophrenia (SZ). Due to presence of imprinted genes within the region, the parental origin of these duplications may be key to the pathogenicity. Duplications of maternal origin are associated with disease, whereas the pathogenicity of paternal ones is unclear. To clarify the role of maternal and paternal duplications, we conducted the largest and most detailed study to date of parental origin of 15q11.2-q13.3 interstitial duplications in DD, ASD and SZ cohorts. We show, for the first time, that paternal duplications lead to an increased risk of developing DD/ASD/multiple congenital anomalies (MCA), but do not appear to increase risk for SZ. The importance of the epigenetic status of 15q11.2-q13.3 duplications was further underlined by analysis of a number of families, in which the duplication was paternally derived in the mother, who was unaffected, whereas her offspring, who inherited a maternally derived duplication, suffered from psychotic illness. Interestingly, the most consistent clinical characteristics of SZ patients with 15q11.2-q13.3 duplications were learning or developmental problems, found in 76% of carriers. Despite their lower pathogenicity, paternal duplications are less frequent in the general population with a general population prevalence of 0.0033% compared to 0.0069% for maternal duplications. This may be due to lower fecundity of male carriers and differential survival of embryos, something echoed in the findings that both types of duplications are de novo in just over 50% of cases. Isodicentric chromosome 15 (idic15) or interstitial triplications were not observed in SZ patients or in controls. Overall, this study refines the distinct roles of maternal and paternal interstitial duplications at 15q11.2-q13.3, underlining the critical importance of maternally expressed imprinted genes in the contribution of Copy Number Variants (CNVs) at this interval to the incidence of psychotic illness. This work will have tangible benefits for patients with 15q11.2-q13.3 duplications by aiding genetic counseling.

  View details for DOI 10.1371/journal.pgen.1005993

  View details for PubMedID 27153221

• FEASIBILITY OF GENETIC ASSOCIATION STUDIES WITH THE HIGH THROUGHPUT MIA FORA NGS ASSAY Wang, C., Li, M., Krishnakumar, S., Sargsyan, O., Gaule, A., Thorstenson, Y., Simonovich, J., Munoz, A., Draina, E., Fukushima, M., Babrzadeh, F., Kuehn, R., Abraham, E., Bugtong, K., Fernandez-Vina, M., Mignot, E., Ollila, H., Levinson, D., Mindrinos, M. WILEY-BLACKWELL. 2016: 284–85

  View details for Web of Science ID 000383951500206

• NEXT GENERATION SEQUENCING REVEALS HLA GENOMIC AND HAPLOTYPE DIVERSITY IN AN US POPULATION OF NORTHERN EUROPEAN ANCESTRY Creary, L. E., Krishnakumar, S., Wang, C., Li, M., Sanchez-Mazas, A., Nunes, J. M., Levinson, D., Mindrinos, M. N., Fernandez-Vina, M. A. WILEY-BLACKWELL. 2016: 298

  View details for Web of Science ID 000383951500241

• AN ACCURATE GENOTYPING METHOD FOR HUMAN LEUKOCYTE ANTIGEN BASED ON NEXT GENERATION SEQUENCING TECHNOLOGY Li, M., Mindrinos, M., Wang, C., Sargsyan, O., Thorstenson, Y., Babrzaeh, F., Mignot, E., Ollila, H., Vina, M., Levinson, D. WILEY-BLACKWELL. 2016: 280–81

  View details for Web of Science ID 000383951500196

• Polygenic interactions with environmental adversity in the aetiology of major depressive disorder. Psychological medicine Mullins, N., Power, R. A., Fisher, H. L., Hanscombe, K. B., Euesden, J., Iniesta, R., Levinson, D. F., Weissman, M. M., Potash, J. B., Shi, J., Uher, R., Cohen-Woods, S., Rivera, M., Jones, L., Jones, I., Craddock, N., Owen, M. J., Korszun, A., Craig, I. W., Farmer, A. E., McGuffin, P., Breen, G., Lewis, C. M. 2016; 46 (4): 759-770

  Abstract

  Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene-environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD.The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them.PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10-6). SLEs and CT were also associated with MDD status (p = 2.19 × 10-4 and p = 5.12 × 10-20, respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples.CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene-environment interactions in complex traits.

  View details for DOI 10.1017/S0033291715002172

  View details for PubMedID 26526099

  View details for PubMedCentralID PMC4754832

• VALIDATION OF GENOTYPING METHOD FOR HUMAN LEUKOCYTE ANTIGEN BASED ON NEXT GENERATION SEQUENCING TECHNOLOGY Li, M., Mindrinos, M., Wang, C., Drainas, E., Babrzadeh, F., Vina, M., Mignot, E., Ollila, H., Levinson, D. ELSEVIER SCIENCE INC. 2016: 118

  View details for DOI 10.1016/j.humimm.2016.07.174

  View details for Web of Science ID 000383313500163

• NEXT GENERATION SEQUENCING REVEALS HLA GENOMIC AND HAPLOTYPE DIVERSITY IN US POPULATIONS OF EUROPEAN AND AFRICAN ANCESTRY Creary, L. E., Krishnakumar, S., Wang, C., Li, M., Sanchez-Mazas, A., Nunes, J. M., Levinson, D. F., Mindrinos, M. N., Fernandez-Vina, M. A. ELSEVIER SCIENCE INC. 2016: 70

  View details for DOI 10.1016/j.humimm.2016.07.106

  View details for Web of Science ID 000383313500095

• The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study. PLoS genetics Winkler, T. W., Justice, A. E., Graff, M., Barata, L., Feitosa, M. F., Chu, S., Czajkowski, J., Esko, T., Fall, T., Kilpeläinen, T. O., Lu, Y., Mägi, R., Mihailov, E., Pers, T. H., Rüeger, S., Teumer, A., Ehret, G. B., Ferreira, T., Heard-Costa, N. L., Karjalainen, J., Lagou, V., Mahajan, A., Neinast, M. D., Prokopenko, I., Simino, J., Teslovich, T. M., Jansen, R., Westra, H., White, C. C., Absher, D., Ahluwalia, T. S., Ahmad, S., Albrecht, E., Alves, A. C., Bragg-Gresham, J. L., de Craen, A. J., Bis, J. C., Bonnefond, A., Boucher, G., Cadby, G., Cheng, Y., Chiang, C. W., Delgado, G., Demirkan, A., Dueker, N., Eklund, N., Eiriksdottir, G., Eriksson, J., Feenstra, B., Fischer, K., Frau, F., Galesloot, T. E., Geller, F., Goel, A., Gorski, M., Grammer, T. B., Gustafsson, S., Haitjema, S., Hottenga, J., Huffman, J. E., Jackson, A. U., Jacobs, K. B., Johansson, Å., Kaakinen, M., Kleber, M. E., Lahti, J., Mateo Leach, I., Lehne, B., Liu, Y., Lo, K. S., Lorentzon, M., Luan, J., Madden, P. A., Mangino, M., McKnight, B., Medina-Gomez, C., Monda, K. L., Montasser, M. E., Müller, G., Müller-Nurasyid, M., Nolte, I. M., Panoutsopoulou, K., Pascoe, L., Paternoster, L., Rayner, N. W., Renström, F., Rizzi, F., Rose, L. M., Ryan, K. A., Salo, P., Sanna, S., Scharnagl, H., Shi, J., Smith, A. V., Southam, L., Stancáková, A., Steinthorsdottir, V., Strawbridge, R. J., Sung, Y. J., Tachmazidou, I., Tanaka, T., Thorleifsson, G., Trompet, S., Pervjakova, N., Tyrer, J. P., Vandenput, L., van der Laan, S. W., van der Velde, N., van Setten, J., van Vliet-Ostaptchouk, J. V., Verweij, N., Vlachopoulou, E., Waite, L. L., Wang, S. R., Wang, Z., Wild, S. H., Willenborg, C., Wilson, J. F., Wong, A., Yang, J., Yengo, L., Yerges-Armstrong, L. M., Yu, L., Zhang, W., Zhao, J. H., Andersson, E. A., Bakker, S. J., Baldassarre, D., Banasik, K., Barcella, M., Barlassina, C., Bellis, C., Benaglio, P., Blangero, J., Blüher, M., Bonnet, F., Bonnycastle, L. L., Boyd, H. A., Bruinenberg, M., Buchman, A. S., Campbell, H., Chen, Y. I., Chines, P. S., Claudi-Boehm, S., Cole, J., Collins, F. S., de Geus, E. J., de Groot, L. C., Dimitriou, M., Duan, J., Enroth, S., Eury, E., Farmaki, A., Forouhi, N. G., Friedrich, N., Gejman, P. V., Gigante, B., Glorioso, N., Go, A. S., Gottesman, O., Gräßler, J., Grallert, H., Grarup, N., Gu, Y., Broer, L., Ham, A. C., Hansen, T., Harris, T. B., Hartman, C. A., Hassinen, M., Hastie, N., Hattersley, A. T., Heath, A. C., Henders, A. K., Hernandez, D., Hillege, H., Holmen, O., Hovingh, K. G., Hui, J., Husemoen, L. L., Hutri-Kähönen, N., Hysi, P. G., Illig, T., De Jager, P. L., Jalilzadeh, S., Jørgensen, T., Jukema, J. W., Juonala, M., Kanoni, S., Karaleftheri, M., Khaw, K. T., Kinnunen, L., Kittner, S. J., Koenig, W., Kolcic, I., Kovacs, P., Krarup, N. T., Kratzer, W., Krüger, J., Kuh, D., Kumari, M., Kyriakou, T., Langenberg, C., Lannfelt, L., Lanzani, C., Lotay, V., Launer, L. J., Leander, K., Lindström, J., Linneberg, A., Liu, Y., Lobbens, S., Luben, R., Lyssenko, V., Männistö, S., Magnusson, P. K., McArdle, W. L., Menni, C., Merger, S., Milani, L., Montgomery, G. W., Morris, A. P., Narisu, N., Nelis, M., Ong, K. K., Palotie, A., Pérusse, L., Pichler, I., Pilia, M. G., Pouta, A., Rheinberger, M., Ribel-Madsen, R., Richards, M., Rice, K. M., Rice, T. K., Rivolta, C., Salomaa, V., Sanders, A. R., Sarzynski, M. A., Scholtens, S., Scott, R. A., Scott, W. R., Sebert, S., Sengupta, S., Sennblad, B., Seufferlein, T., Silveira, A., Slagboom, P. E., Smit, J. H., Sparsø, T. H., Stirrups, K., Stolk, R. P., Stringham, H. M., Swertz, M. A., Swift, A. J., Syvänen, A., Tan, S., Thorand, B., Tönjes, A., Tremblay, A., Tsafantakis, E., van der Most, P. J., Völker, U., Vohl, M., Vonk, J. M., Waldenberger, M., Walker, R. W., Wennauer, R., Widén, E., Willemsen, G., Wilsgaard, T., Wright, A. F., Zillikens, M. C., van Dijk, S. C., van Schoor, N. M., Asselbergs, F. W., de Bakker, P. I., Beckmann, J. S., Beilby, J., Bennett, D. A., Bergman, R. N., Bergmann, S., Böger, C. A., Boehm, B. O., Boerwinkle, E., Boomsma, D. I., Bornstein, S. R., Bottinger, E. P., Bouchard, C., Chambers, J. C., Chanock, S. J., Chasman, D. I., Cucca, F., Cusi, D., Dedoussis, G., Erdmann, J., Eriksson, J. G., Evans, D. A., de Faire, U., Farrall, M., Ferrucci, L., Ford, I., Franke, L., Franks, P. W., Froguel, P., Gansevoort, R. T., Gieger, C., Grönberg, H., Gudnason, V., Gyllensten, U., Hall, P., Hamsten, A., van der Harst, P., Hayward, C., Heliövaara, M., Hengstenberg, C., Hicks, A. A., Hingorani, A., Hofman, A., Hu, F., Huikuri, H. V., Hveem, K., James, A. L., Jordan, J. M., Jula, A., Kähönen, M., Kajantie, E., Kathiresan, S., Kiemeney, L. A., Kivimaki, M., Knekt, P. B., Koistinen, H. A., Kooner, J. S., Koskinen, S., Kuusisto, J., Maerz, W., Martin, N. G., Laakso, M., Lakka, T. A., Lehtimäki, T., Lettre, G., Levinson, D. F., Lind, L., Lokki, M., Mäntyselkä, P., Melbye, M., Metspalu, A., Mitchell, B. D., Moll, F. L., Murray, J. C., Musk, A. W., Nieminen, M. S., Njølstad, I., Ohlsson, C., Oldehinkel, A. J., Oostra, B. A., Palmer, L. J., Pankow, J. S., Pasterkamp, G., Pedersen, N. L., Pedersen, O., Penninx, B. W., Perola, M., Peters, A., Polašek, O., Pramstaller, P. P., Psaty, B. M., Qi, L., Quertermous, T., Raitakari, O. T., Rankinen, T., Rauramaa, R., Ridker, P. M., Rioux, J. D., Rivadeneira, F., Rotter, J. I., Rudan, I., Den Ruijter, H. M., Saltevo, J., Sattar, N., Schunkert, H., Schwarz, P. E., Shuldiner, A. R., Sinisalo, J., Snieder, H., Sørensen, T. I., Spector, T. D., Staessen, J. A., Stefania, B., Thorsteinsdottir, U., Stumvoll, M., Tardif, J., Tremoli, E., Tuomilehto, J., Uitterlinden, A. G., Uusitupa, M., Verbeek, A. L., Vermeulen, S. H., Viikari, J. S., Vitart, V., Völzke, H., Vollenweider, P., Waeber, G., Walker, M., Wallaschofski, H., Wareham, N. J., Watkins, H., Zeggini, E., Chakravarti, A., Clegg, D. J., Cupples, L. A., Gordon-Larsen, P., Jaquish, C. E., Rao, D. C., Abecasis, G. R., Assimes, T. L., Barroso, I., Berndt, S. I., Boehnke, M., Deloukas, P., Fox, C. S., Groop, L. C., Hunter, D. J., Ingelsson, E., Kaplan, R. C., McCarthy, M. I., Mohlke, K. L., O'Connell, J. R., Schlessinger, D., Strachan, D. P., Stefansson, K., van Duijn, C. M., Hirschhorn, J. N., Lindgren, C. M., Heid, I. M., North, K. E., Borecki, I. B., Kutalik, Z., Loos, R. J. 2015; 11 (10)

  Abstract

  Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

  View details for DOI 10.1371/journal.pgen.1005378

  View details for PubMedID 26426971

• EIF3G is associated with narcolepsy across ethnicities EUROPEAN JOURNAL OF HUMAN GENETICS Holm, A., Lin, L., Faraco, J., Mostafavi, S., Battle, A., Zhu, X., Levinson, D. F., Han, F., Gammeltoft, S., Jennum, P., Mignot, E., Kornum, B. R. 2015; 23 (11): 1573-1580

  Abstract

  Type 1 narcolepsy, an autoimmune disease affecting hypocretin (orexin) neurons, is strongly associated with HLA-DQB1*06:02. Among polymorphisms associated with the disease is single-nucleotide polymorphism rs2305795 (c.*638G>A) located within the P2RY11 gene. P2RY11 is in a region of synteny conserved in mammals and zebrafish containing PPAN, EIF3G and DNMT1 (DNA methyltransferase 1). As mutations in DNMT1 cause a rare dominant form of narcolepsy in association with deafness, cerebellar ataxia and dementia, we questioned whether the association with P2RY11 in sporadic narcolepsy could be secondary to linkage disequilibrium with DNMT1. Based on genome-wide association data from two cohorts of European and Chinese ancestry, we found that the narcolepsy association signal drops sharply between P2RY11/EIF3G and DNMT1, suggesting that the association with narcolepsy does not extend into the DNMT1 gene region. Interestingly, using transethnic mapping, we identified a novel single-nucleotide polymorphism rs3826784 (c.596-260A>G) in the EIF3G gene also associated with narcolepsy. The disease-associated allele increases EIF3G mRNA expression. EIF3G is located in the narcolepsy risk locus and EIF3G expression correlates with PPAN and P2RY11 expression. This suggests shared regulatory mechanisms that might be affected by the polymorphism and are of relevance to narcolepsy.

  View details for DOI 10.1038/ejhg.2015.4

  View details for PubMedID 25669430

• The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study PLOS GENETICS Winkler, T. W., Justice, A. E., Graff, M., Barata, L., Feitosa, M. F., Chu, S., Czajkowski, J., Esko, T., Fall, T., Kilpelainen, T. O., Lu, Y., Magi, R., Mihailov, E., Pers, T. H., Rueeger, S., Teumer, A., Ehret, G. B., Ferreira, T., Heard-Costa, N. L., Karjalainen, J., Lagou, V., Mahajan, A., Neinast, M. D., Prokopenko, I., Simino, J., Teslovich, T. M., Jansen, R., Westra, H., White, C. C., Absher, D., Ahluwalia, T. S., Ahmad, S., Albrecht, E., Alves, A. C., Bragg-Gresham, J. L., de Craen, A. J., Bis, J. C., Bonnefond, A., Boucher, G., Cadby, G., Cheng, Y., Chiang, C. W., Delgado, G., Demirkan, A., Dueker, N., Eklund, N., Eiriksdottir, G., Eriksson, J., Feenstra, B., Fischer, K., Frau, F., Galesloot, T. E., Geller, F., Goel, A., Gorski, M., Grammer, T. B., Gustafsson, S., Haitjema, S., Hottenga, J., Huffman, J. E., Jackson, A. U., Jacobs, K. B., Johansson, A., Kaakinen, M., Kleber, M. E., Lahti, J., Leach, I. M., Lehne, B., Liu, Y., Lo, K. S., Lorentzon, M., Luan, J., Madden, P. A., Mangino, M., McKnight, B., Medina-Gomez, C., Monda, K. L., Montasser, M. E., Mueller, G., Mueller-Nurasyid, M., Nolte, I. M., Panoutsopoulou, K., Pascoe, L., Paternoster, L., Rayner, N. W., Renstrom, F., Rizzi, F., Rose, L. M., Ryan, K. A., Salo, P., Sanna, S., Scharnagl, H., Shi, J., Smith, A. V., Southam, L., Stancakova, A., Steinthorsdottir, V., Strawbridge, R. J., Sung, Y. J., Tachmazidou, I., Tanaka, T., Thorleifsson, G., Trompet, S., Pervjakova, N., Tyrer, J. P., Vandenput, L., van der Laan, S. W., van der Velde, N., van Setten, J., van Vliet-Ostaptchouk, J. V., Verweij, N., Vlachopoulou, E., Waite, L. L., Wang, S. R., Wang, Z., Wild, S. H., Willenborg, C., Wilson, J. F., Wong, A., Yang, J., Yengo, L., Yerges-Armstrong, L. M., Yu, L., Zhang, W., Zhao, J. H., Andersson, E. A., Bakker, S. J., Baldassarre, D., Banasik, K., Barcella, M., Barlassina, C., Bellis, C., Benaglio, P., Blangero, J., Blueher, M., Bonnet, F., Bonnycastle, L. L., Boyd, H. A., Bruinenberg, M., Buchman, A. S., Campbell, H., Chen, Y. I., Chines, P. S., Claudi-Boehm, S., Cole, J., Collins, F. S., de Geus, E. J., de Groot, L. C., Dimitriou, M., Duan, J., Enroth, S., Eury, E., Farmaki, A., Forouhi, N. G., Friedrich, N., Gejman, P. V., Gigante, B., Glorioso, N., Go, A. S., Gottesman, O., Graessler, J., Grallert, H., Grarup, N., Gu, Y., Broer, L., Ham, A. C., Hansen, T., Harris, T. B., Hartman, C. A., Hassinen, M., Hastie, N., Hattersley, A. T., Heath, A. C., Henders, A. K., Hernandez, D., Hillege, H., Holmen, O., Hovingh, K. G., Hui, J., Husemoen, L. L., Hutri-Kahonen, N., Hysi, P. G., Illig, T., De Jager, P. L., Jalilzadeh, S., Jorgensen, T., Jukema, J. W., Juonala, M., Kanoni, S., Karaleftheri, M., Khaw, K. T., Kinnunen, L., Kittner, S. J., Koenig, W., Kolcic, I., Kovacs, P., Krarup, N. T., Kratzer, W., Krueger, J., Kuh, D., Kumari, M., Kyriakou, T., Langenberg, C., Lannfelt, L., Lanzani, C., Lotay, V., Launer, L. J., Leander, K., Lindstrom, J., Linneberg, A., Liu, Y., Lobbens, S., Luben, R., Lyssenko, V., Mannisto, S., Magnusson, P. K., McArdle, W. L., Menni, C., Merger, S., Milani, L., Montgomery, G. W., Morris, A. P., Narisu, N., Nelis, M., Ong, K. K., Palotie, A., Perusse, L., Pichler, I., Pilia, M. G., Pouta, A., Rheinberger, M., Ribel-Madsen, R., Richards, M., Rice, K. M., Rice, T. K., Rivolta, C., Salomaa, V., Sanders, A. R., Sarzynski, M. A., Scholtens, S., Scott, R. A., Scott, W. R., Sebert, S., Sengupta, S., Sennblad, B., Seufferlein, T., Silveira, A., Slagboom, P. E., Smit, J. H., Sparso, T. H., Stirrups, K., Stolk, R. P., Stringham, H. M., Swertz, M. A., Swift, A. J., Syvanen, A., Tan, S., Thorand, B., Toenjes, A., Tremblay, A., Tsafantakis, E., van der Most, P. J., Voelker, U., Vohl, M., Vonk, J. M., Waldenberger, M., Walker, R. W., Wennauer, R., Widen, E., Willemsen, G., Wilsgaard, T., Wright, A. F., Zillikens, M. C., van Dijk, S. C., van Schoor, N. M., Asselbergs, F. W., de Bakker, P. I., Beckmann, J. S., Beilby, J., Bennett, D. A., Bergman, R. N., Bergmann, S., Boeger, C. A., Boehm, B. O., Boerwinkle, E., Boomsma, D. I., Bornstein, S. R., Bottinger, E. P., Bouchard, C., Chambers, J. C., Chanock, S. J., Chasman, D. I., Cucca, F., Cusi, D., Dedoussis, G., Erdmann, J., Eriksson, J. G., Evans, D. A., de Faire, U., Farrall, M., Ferrucci, L., Ford, I., Franke, L., Franks, P. W., Froguel, P., Gansevoort, R. T., Gieger, C., Gronberg, H., Gudnason, V., Gyllensten, U., Hall, P., Hamsten, A., van der Harst, P., Hayward, C., Heliovaara, M., Hengstenberg, C., Hicks, A. A., Hingorani, A., Hofman, A., Hu, F., Huikuri, H. V., Hveem, K., James, A. L., Jordan, J. M., Jula, A., Kaehoenen, M., Kajantie, E., Kathiresan, S., Kiemeney, L. A., Kivimaki, M., Knekt, P. B., Koistinen, H. A., Kooner, J. S., Koskinen, S., Kuusisto, J., Maerz, W., Martin, N. G., Laakso, M., Lakka, T. A., Lehtimaki, T., Lettre, G., Levinson, D. F., Lind, L., Lokki, M., Mantyselka, P., Melbye, M., Metspalu, A., Mitchell, B. D., Moll, F. L., Murray, J. C., Musk, A. W., Nieminen, M. S., Njolstad, I., Ohlsson, C., Oldehinkel, A. J., Oostra, B. A., Palmer, L. J., Pankow, J. S., Pasterkamp, G., Pedersen, N. L., Pedersen, O., Penninx, B. W., Perola, M., Peters, A., Polasek, O., Pramstaller, P. P., Psaty, B. M., Qi, L., Quertermous, T., Raitakari, O. T., Rankinen, T., Rauramaa, R., Ridker, P. M., Rioux, J. D., Rivadeneira, F., Rotter, J. I., Rudan, I., Den Ruijter, H. M., Saltevo, J., Sattar, N., Schunkert, H., Schwarz, P. E., Shuldiner, A. R., Sinisalo, J., Snieder, H., Sorensen, T. I., Spector, T. D., Staessen, J. A., Stefania, B., Thorsteinsdottir, U., Stumvoll, M., Tardif, J., Tremoli, E., Tuomilehto, J., Uitterlinden, A. G., Uusitupa, M., Verbeek, A. L., Vermeulen, S. H., Viikari, J. S., Vitart, V., Voelzke, H., Vollenweider, P., Waeber, G., Walker, M., Wallaschofski, H., Wareham, N. J., Watkins, H., Zeggini, E., Chakravarti, A., Clegg, D. J., Cupples, L. A., Gordon-Larsen, P., Jaquish, C. E., Rao, D. C., Abecasis, G. R., Assimes, T. L., Barroso, I., Berndt, S. I., Boehnke, M., Deloukas, P., Fox, C. S., Groop, L. C., Hunter, D. J., Ingelsson, E., Kaplan, R. C., McCarthy, M. I., Mohlke, K. L., O'Connell, J. R., Schlessinger, D., Strachan, D. P., Stefansson, K., van Duijn, C. M., Hirschhorn, J. N., Lindgren, C. M., Heid, I. M., North, K. E., Borecki, I. B., Kutalik, Z., Loos, R. J. 2015; 11 (10)

  View details for DOI 10.1371/journal.pgen.1005378

  View details for Web of Science ID 000364401600002

  View details for PubMedID 26426971

• Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders NEURON Arloth, J., Bogdan, R., Weber, P., Frishman, G., Menke, A., Wagner, K. V., Balsevich, G., Schmidt, M. V., Karbalai, N., Czamara, D., Altmann, A., Truembach, D., Wurst, W., Mehta, D., Uhr, M., Klengel, T., Erhardt, A., Carey, C. E., Conley, E. D., Ruepp, A., Mueller-Myhsok, B., Hariri, A. R., Binder, E. B. 2015; 86 (5): 1189-1202

  Abstract

  Depression risk is exacerbated by genetic factors and stress exposure; however, the biological mechanisms through which these factors interact to confer depression risk are poorly understood. One putative biological mechanism implicates variability in the ability of cortisol, released in response to stress, to trigger a cascade of adaptive genomic and non-genomic processes through glucocorticoid receptor (GR) activation. Here, we demonstrate that common genetic variants in long-range enhancer elements modulate the immediate transcriptional response to GR activation in human blood cells. These functional genetic variants increase risk for depression and co-heritable psychiatric disorders. Moreover, these risk variants are associated with inappropriate amygdala reactivity, a transdiagnostic psychiatric endophenotype and an important stress hormone response trigger. Network modeling and animal experiments suggest that these genetic differences in GR-induced transcriptional activation may mediate the risk for depression and other psychiatric disorders by altering a network of functionally related stress-sensitive genes in blood and brain.

  View details for DOI 10.1016/j.neuron.2015.05.034

  View details for Web of Science ID 000355666400011

  View details for PubMedID 26050039

  View details for PubMedCentralID PMC4490780

• The association between lower educational attainment and depression owing to shared genetic effects? Results in similar to 25 000 subjects MOLECULAR PSYCHIATRY Peyrot, W. J., Lee, S. H., Milaneschi, Y., Abdellaoui, A., Byrne, E. M., Esko, T., de Geus, E. J., Hemani, G., Hottenga, J. J., Kloiber, S., Levinson, D. F., Lucae, S., Martin, N. G., Medland, S. E., Metspalu, A., Milani, L., Noethen, M. M., Potash, J. B., Rietschel, M., Rietveld, C. A., Ripke, S., Shi, J., Willemsen, G., Zhu, Z., Boomsma, D. I., Wray, N. R., Penninx, B. W. 2015; 20 (6): 735-743

  Abstract

  An association between lower educational attainment (EA) and an increased risk for depression has been confirmed in various western countries. This study examines whether pleiotropic genetic effects contribute to this association. Therefore, data were analyzed from a total of 9662 major depressive disorder (MDD) cases and 14,949 controls (with no lifetime MDD diagnosis) from the Psychiatric Genomics Consortium with additional Dutch and Estonian data. The association of EA and MDD was assessed with logistic regression in 15,138 individuals indicating a significantly negative association in our sample with an odds ratio for MDD 0.78 (0.75-0.82) per standard deviation increase in EA. With data of 884,105 autosomal common single-nucleotide polymorphisms (SNPs), three methods were applied to test for pleiotropy between MDD and EA: (i) genetic profile risk scores (GPRS) derived from training data for EA (independent meta-analysis on ~120,000 subjects) and MDD (using a 10-fold leave-one-out procedure in the current sample), (ii) bivariate genomic-relationship-matrix restricted maximum likelihood (GREML) and (iii) SNP effect concordance analysis (SECA). With these methods, we found (i) that the EA-GPRS did not predict MDD status, and MDD-GPRS did not predict EA, (ii) a weak negative genetic correlation with bivariate GREML analyses, but this correlation was not consistently significant, (iii) no evidence for concordance of MDD and EA SNP effects with SECA analysis. To conclude, our study confirms an association of lower EA and MDD risk, but this association was not because of measurable pleiotropic genetic effects, which suggests that environmental factors could be involved, for example, socioeconomic status.

  View details for DOI 10.1038/mp.2015.50

  View details for Web of Science ID 000354890200012

  View details for PubMedID 25917368

• EXTENDED COVERAGE BY NEXT GENERATION SEQUENCING METHODS REFINES THE CHARACTERIZATION OF THE COMMON AND WELL DOCUMENTED HLA ALLELES Fernandez-Vina, M. A., Wang, C., Krishnakumar, S., Levinson, D. F., Davis, R. W., Mindrinos, M. ELSEVIER SCIENCE INC. 2015: 226

  View details for DOI 10.1016/j.humimm.2015.01.051

  View details for Web of Science ID 000352749400023

• Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia, Bipolar Disorder, and Major Depressive Disorder AMERICAN JOURNAL OF HUMAN GENETICS Maier, R., Moser, G., Chen, G., Ripke, S., Coryell, W., Potash, J. B., Scheftner, W. A., Shi, J., Weissman, M. M., Hultman, C. M., Landen, M., Levinson, D. F., Kendler, K. S., Smoller, J. W., Wray, N. R., Lee, S. H. 2015; 96 (2): 283-294

  Abstract

  Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.

  View details for DOI 10.1016/j.ajhg.2014.12.006

  View details for PubMedID 25640677

• Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways NATURE NEUROSCIENCE O'Dushlaine, C., Rossin, L., Lee, P. H., Duncan, L., Parikshak, N. N., Newhouse, S., Ripke, S., Neale, B. M., Purcell, S. M., Posthuma, D., Nurnberger, J. I., Lee, S. H., Faraone, S. V., Perlis, R. H., Mowry, B. J., Thapar, A., Goddard, M. E., Witte, J. S., Absher, D., Agartz, I., Akil, H., Amin, F., Andreassen, O. A., Anjorin, A., Anney, R., Anttila, V., Arking, D. E., Asherson, P., Azevedo, M. H., Backlund, L., Badner, J. A., Bailey, A. J., Banaschewski, T., Barchas, J. D., Barnes, M. R., Barrett, T. B., Bass, N., Battaglia, A., Bauer, M., Bayes, M., Bellivier, F., Bergen, S. E., Berrettini, W., Betancur, C., Bettecken, T., Biederman, J., Binder, E. B., Black, D. W., Blackwood, D. H., Bloss, C. S., Boehnke, M., Boomsma, D. I., Breuer, R., Bruggeman, R., Cormican, P., Buccola, N. G., Buitelaar, J. K., Bunney, W. E., Buxbaum, J. D., Byerley, W. F., Byrne, E. M., Caesar, S., Cahn, W., Cantor, R. M., Casas, M., Chakravarti, A., Chambert, K., Choudhury, K., Cichon, S., Mattheisen, M., Cloninger, C. R., Collier, D. A., Cook, E. H., Coon, H., Cormand, B., Corvin, A., Coryell, W. H., Craig, D. W., Craig, I. W., Crosbie, J., Cuccaro, M. L., Curtis, D., Czamara, D., Datta, S., Dawson, G., Day, R., de Geus, E. J., Degenhardt, F., Djurovic, S., Donohoe, G. J., Doyle, A. E., Duan, J., Dudbridge, F., Duketis, E., Ebstein, R. P., Edenberg, H. J., Elia, J., Ennis, S., Etain, B., Fanous, A., Farmer, A. E., Ferrier, I. N., Flicldnger, M., Fombonne, E., Foroud, T., Frank, J., Franke, B., Fraser, C., Freedman, R., Freimer, N. B., Freitag, C. M., Friedl, M., Frisen, L., Gailagher, L., Gejman, P. V., Georgieva, L., Gershon, E. S., Giegling, I., Gill, M., Gordon, S. D., Gordon-Smith, K., Green, E. K., Greenwood, T. A., Grice, D. E., Gross, M., Grozeva, D., Guan, W., Gurling, H., de Haan, L., Haines, J. L., Hakonarson, H., Hallmayer, J., Hamilton, S. P., Hamshere, M. L., Hansen, T. F., Hartmann, A. M., Hautzinger, M., Heath, A. C., Henders, A. K., Herms, S., Hickie, I. B., Hipolito, M., Hoefels, S., Holsboer, F., Hoogendijk, W. J., Hottenga, J., Hultman, C. M., Hus, V., Ingason, A., Ising, M., Jamain, S., Jones, E. G., Jones, I., Jones, L., Tzeng, J., Kaehler, A. K., Kahn, R. S., Kandaswamy, R., Keller, M. C., Kennedy, J. L., Kenny, E., Kent, L., Kim, Y., Kirov, G. K., Klauck, S. M., Klei, L., Knowles, J. A., Kohli, M. A., Koller, D. L., Konte, B., Korszun, A., Krabbendam, L., Krasucki, R., Kuntsi, J., Kwan, P., Landen, M., Laengstroem, N., Lathrop, M., Lawrence, J., Lawson, W. B., Leboyer, M., Ledbetter, D. H., Lencz, T., Lesch, K., Levinson, D. F., Lewis, C. M., Li, J., Lichtenstein, P., Lieberman, J. A., Lin, D., Linszen, D. H., Liu, C., Lohoff, F. W., Loo, S. K., Lord, C., Lowe, J. K., Lucae, S., MacIntyre, D. J., Madden, P. A., Maestrini, E., Magnusson, P. K., Mahon, P. B., Maier, W., Malhotra, A. K., Mane, S. M., Martin, C. L., Martin, N. G., Matthews, K., Mattingsdal, M., McCarroll, S. A., McGhee, K. A., McGough, J. J., McGrath, P. J., McGuffin, P., McInnis, M. G., McIntosh, A., McKinney, R., McLean, A. W., McMahon, F. J., McMahon, W. M., McQuillin, A., Medeiros, H., Medland, S. E., Meier, S., Melle, I., Meng, F., Meyer, J., Middeldorp, C. M., Middleton, L., Milanova, V., Miranda, A., Monaco, A. P., Montgomery, G. W., Moran, J. L., Moreno-De-Luca, D., Morken, G., Morris, D. W., Morrow, E. M., Moskvina, V., Muglia, P., Muehleisen, T. W., Muir, W. J., Mueller-Myhsok, B., Murtha, M., Myers, R. M., Myin-Germeys, I., Neale, M. C., Nelson, S. F., Nievergelt, C. M., Nikolov, I., Nimgaonkar, V., Nolen, W. A., Noethen, M. M., Nwulia, E. A., Nyholt, D. R., Oades, R. D., Olincy, A., Oliveira, G., Olsen, L., Ophoff, R. A., Osby, U., Owen, M. J., Palotie, A., Parr, J. R., Paterson, A. D., Pato, C. N., Pato, M. T., Penninx, B. W., Pergadia, M. L., Pericak-Vance, M. A., Pickard, B. S., Pimm, J., Piven, J., Potash, J. B., Poustka, F., Propping, P., Puri, V., Quested, D. J., Quinn, E. M., Ramos-Quiroga, J. A., Rasmussen, H. B., Raychaudhuri, S., Rehnstroem, K., Reif, A., Ribases, M., Rice, J. P., Rietschel, M., Roeder, K., Roeyers, H., Rothenberger, A., Rouleau, G., Ruderfer, D., Rujescu, D., Sanders, A. R., Sanders, S. J., Santangelo, S. L., Sergeant, J. A., Schachar, R., Schalling, M., Schatzberg, A. F., Scheftner, W. A., Schellenberg, G. D., Scherer, S. W., Schork, N. J., Schulze, T. G., Schumacher, J., Schwarz, M., Scolnick, E., Scott, L. J., Shi, J., Shilling, P. D., Shyn, S. I., Silverman, J. M., Slager, S. L., Smalley, S. L., Smit, J. H., Smith, E. N., Sonuga-Barke, E. J., Cair, D. S., State, M., Steffens, M., Steinhausen, H., Strauss, J. S., Strohmaier, J., Stroup, T. S., Sutdiffe, J. S., Szatmari, P., Szelinger, S., Thirumalai, S., Thompson, R. C., Todorov, A. A., Tozzi, F., Treutlein, J., Uhr, M., van den Oord, E. J., Van Grootheest, G., van Os, J., Vicente, A. M., Vieland, V. J., Vincent, J. B., Visscher, P. M., Walsh, C. A., Wassink, T. H., Watson, S. J., Weissman, M. M., Werge, T., Wienker, T. F., Wijsman, E. M., Willemsen, G., Williams, N., Willsey, A. J., Witt, S. H., Xu, W., Young, A. H., Yu, T. W., Zammit, S., Zandi, P. P., Zhang, P., Zitman, F. G., Zoellner, S., Devlin, B., Kelsoe, J. R., Sklar, P., Daly, M. J., O'Donovan, M. C., Craddock, N., Kendler, K. S., Weiss, L. A., Wray, N. R., Zhao, Z., Geschwind, D. H., Sullivan, P. F., Smoller, J. W., Holmans, P. A., Breen, G. 2015; 18 (2): 199-209

  Abstract

  Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

  View details for DOI 10.1038/nn.3922

  View details for Web of Science ID 000348631800010

  View details for PubMedID 25599223

  View details for PubMedCentralID PMC4378867

• A Rare Functional Noncoding Variant at the GWAS-Implicated MIR137/MIR2682 Locus Might Confer Risk to Schizophrenia and Bipolar Disorder AMERICAN JOURNAL OF HUMAN GENETICS Duan, J., Shi, J., Fiorentino, A., Leites, C., Chen, X., Moy, W., Chen, J., Alexandrov, B. S., Usheva, A., He, D., Freda, J., O'Brien, N. L., McQuillin, A., Sanders, A. R., Gershon, E. S., DeLisi, L. E., Bishop, A. R., Gurling, H. M., Pato, M. T., Levinson, D. F., Kendler, K. S., Pato, C. N., Gejman, P. V. 2014; 95 (6): 744-753

  Abstract

  Schizophrenia (SZ) genome-wide association studies (GWASs) have identified common risk variants in >100 susceptibility loci; however, the contribution of rare variants at these loci remains largely unexplored. One of the strongly associated loci spans MIR137 (miR137) and MIR2682 (miR2682), two microRNA genes important for neuronal function. We sequenced ∼6.9 kb MIR137/MIR2682 and upstream regulatory sequences in 2,610 SZ cases and 2,611 controls of European ancestry. We identified 133 rare variants with minor allele frequency (MAF) <0.5%. The rare variant burden in promoters and enhancers, but not insulators, was associated with SZ (p = 0.021 for MAF < 0.5%, p = 0.003 for MAF < 0.1%). A rare enhancer SNP, 1:g.98515539A>T, presented exclusively in 11 SZ cases (nominal p = 4.8 × 10(-4)). We further identified its risk allele T in 2 of 2,434 additional SZ cases, 11 of 4,339 bipolar (BP) cases, and 3 of 3,572 SZ/BP study controls and 1,688 population controls; yielding combined p values of 0.0007, 0.0013, and 0.0001 for SZ, BP, and SZ/BP, respectively. The risk allele T of 1:g.98515539A>T reduced enhancer activity of its flanking sequence by >50% in human neuroblastoma cells, predicting lower expression of MIR137/MIR2682. Both empirical and computational analyses showed weaker transcription factor (YY1) binding by the risk allele. Chromatin conformation capture (3C) assay further indicated that 1:g.98515539A>T influenced MIR137/MIR2682, but not the nearby DPYD or LOC729987. Our results suggest that rare noncoding risk variants are associated with SZ and BP at MIR137/MIR2682 locus, with risk alleles decreasing MIR137/MIR2682 expression.

  View details for DOI 10.1016/j.ajhg.2014.11.001

  View details for PubMedID 25434007

• Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing MOLECULAR PSYCHIATRY Mostafavi, S., Battle, A., Zhu, X., Potash, J. B., Weissman, M. M., Shi, J., Beckman, K., Haudenschild, C., McCormick, C., Mei, R., Gameroff, M. J., Gindes, H., Adams, P., Goes, F. S., Mondimore, F. M., MacKinnon, D. F., Notes, L., Schweizer, B., Furman, D., Montgomery, S. B., Urban, A. E., Koller, D., Levinson, D. F. 2014; 19 (12): 1267-1274

  View details for DOI 10.1038/mp.2013.161

  View details for Web of Science ID 000345423500004

• Family-based association study of common variants, raremutation study and epistatic interaction detection in HDAC genes in schizophrenia SCHIZOPHRENIA RESEARCH Kebir, O., Chaumette, B., Fatjo-Vilas, M., Ambalavanan, A., Ramoz, N., Xiong, L., Mouaffak, F., Millet, B., Jaafari, N., DeLisi, L. E., Levinson, D., Joober, R., Fananas, L., Rouleau, G., Dubertret, C., Krebs, M. 2014; 160 (1-3): 97-103

  Abstract

  Histone deacetylases (HDACs) are key enzymes of histone acetylation, and abnormalities in histone modifications and in the level of HDAC proteins have been reported in schizophrenia. The objective of the present study was to systematically test the HDAC genes for its association with schizophrenia.A family-based genetic association study (951 Caucasian subjects in 313 nuclear families) using 601 tag-single nucleotide polymorphisms in HDAC genes was conducted followed by a replication study of top-ranked markers in a sample of 1427 Caucasian subjects from 241 multiplex families and 176 trios. Epistasis interaction was tested by using the pedigree-based generalized multifactor dimensionality reduction (GMDR). Furthermore, we analyzed exome sequencing data of 1134 subjects for detection of rare mutations in HDAC genomic regions.In the exploratory study, ten markers were in significant association with schizophrenia (P<0.01). One maker rs14251 (HDAC3) was replicated (P=0.04) and remained significant in the whole sample (P=0.004). GMDR identified that a significant three-locus interaction model was detected involving rs17265596 (HDAC9), rs7290710 (HDAC10) and rs7634112 (HDAC11) with a good testing accuracy (0.58). No rare mutations were found associated with schizophrenia.This first exploratory systematic study of the HDAC genes provides consistent support for the involvement of the HDAC3 gene in the etiology of schizophrenia. A statistical epistatic interaction between HDAC9, HDAC10, and HDAC11 was detected and seems biologically plausible.

  View details for DOI 10.1016/j.schres.2014.09.029

  View details for PubMedID 25445625

• Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing. Molecular psychiatry Mostafavi, S., Battle, A., Zhu, X., Potash, J. B., Weissman, M. M., Shi, J., Beckman, K., Haudenschild, C., McCormick, C., Mei, R., Gameroff, M. J., Gindes, H., Adams, P., Goes, F. S., Mondimore, F. M., MacKinnon, D. F., Notes, L., Schweizer, B., Furman, D., Montgomery, S. B., Urban, A. E., Koller, D., Levinson, D. F. 2014; 19 (12): 1267-1274

  Abstract

  A study of genome-wide gene expression in major depressive disorder (MDD) was undertaken in a large population-based sample to determine whether altered expression levels of genes and pathways could provide insights into biological mechanisms that are relevant to this disorder. Gene expression studies have the potential to detect changes that may be because of differences in common or rare genomic sequence variation, environmental factors or their interaction. We recruited a European ancestry sample of 463 individuals with recurrent MDD and 459 controls, obtained self-report and semi-structured interview data about psychiatric and medical history and other environmental variables, sequenced RNA from whole blood and genotyped a genome-wide panel of common single-nucleotide polymorphisms. We used analytical methods to identify MDD-related genes and pathways using all of these sources of information. In analyses of association between MDD and expression levels of 13 857 single autosomal genes, accounting for multiple technical, physiological and environmental covariates, a significant excess of low P-values was observed, but there was no significant single-gene association after genome-wide correction. Pathway-based analyses of expression data detected significant association of MDD with increased expression of genes in the interferon α/β signaling pathway. This finding could not be explained by potentially confounding diseases and medications (including antidepressants) or by computationally estimated proportions of white blood cell types. Although cause-effect relationships cannot be determined from these data, the results support the hypothesis that altered immune signaling has a role in the pathogenesis, manifestation, and/or the persistence and progression of MDD.Molecular Psychiatry advance online publication, 3 December 2013; doi:10.1038/mp.2013.161.

  View details for DOI 10.1038/mp.2013.161

  View details for PubMedID 24296977

• Genetic studies of major depressive disorder: why are there no genome-wide association study findings and what can we do about it? Biological psychiatry Levinson, D. F., Mostafavi, S., Milaneschi, Y., Rivera, M., Ripke, S., Wray, N. R., Sullivan, P. F. 2014; 76 (7): 510-512

  View details for DOI 10.1016/j.biopsych.2014.07.029

  View details for PubMedID 25201436

• Genetic testing of children for predisposition to mood disorders: anticipating the clinical issues. Journal of genetic counseling Erickson, J. A., Kuzmich, L., Ormond, K. E., Gordon, E., Christman, M. F., Cho, M. K., Levinson, D. F. 2014; 23 (4): 566-577

  Abstract

  Large-scale sequencing information may provide a basis for genetic tests for predisposition to common disorders. In this study, participants in the Coriell Personalized Medicine Collaborative (N = 53) with a personal and/or family history of Major Depressive Disorder or Bipolar Disorder were interviewed based on the Health Belief Model around hypothetical intention to test one's children for probability of developing a mood disorder. Most participants (87 %) were interested in a hypothetical test for children that had high ("90 %") positive predictive value, while 51 % of participants remained interested in a modestly predictive test ("20 %"). Interest was driven by beliefs about effects of test results on parenting behaviors and on discrimination. Most participants favored testing before adolescence (64 %), and were reluctant to share results with asymptomatic children before adulthood. Participants anticipated both positive and negative effects of testing on parental treatment and on children's self-esteem. Further investigation will determine whether these findings will generalize to other complex disorders for which early intervention is possible but not clearly demonstrated to improve outcomes. More information is also needed about the effects of childhood genetic testing and sharing of results on parent-child relationships, and about the role of the child in the decision-making process.

  View details for DOI 10.1007/s10897-014-9710-y

  View details for PubMedID 24651919

• Biological insights from 108 schizophrenia-associated genetic loci NATURE Ripke, S., Neale, B. M., Corvin, A., Walters, J. T., Farh, K., Holmans, P. A., Lee, P., Bulik-Sullivan, B., Collier, D. A., Huang, H., Pers, T. H., Agartz, I., Agerbo, E., Albus, M., Alexander, M., Amin, F., Bacanu, S. A., Begemann, M., Belliveau, R. A., Bene, J., Bergen, S. E., Bevilacqua, E., Bigdeli, T. B., Black, D. W., Bruggeman, R., Buccola, N. G., Buckner, R. L., Byerley, W., Cahn, W., Cai, G., Campion, D., Cantor, R. M., Carr, V. J., Carrera, N., Catts, S. V., Chambert, K. D., Chan, R. C., Chen, R. Y., Chen, E. Y., Cheng, W., Cheung, E. F., Chong, S. A., Cloninger, C. R., Cohen, D., Cohen, N., Cormican, P., Craddock, N., Crowley, J. J., Curtis, D., Davidson, M., Davis, K. L., Degenhardt, F., Del Favero, J., Demontis, D., Dikeos, D., Dinan, T., Djurovic, S., Donohoe, G., Drapeau, E., Duan, J., Dudbridge, F., Durmishi, N., Eichhammer, P., Eriksson, J., Escott-Price, V., Essioux, L., Fanous, A. H., Farrell, M. S., Frank, J., Franke, L., Freedman, R., Freimer, N. B., Friedl, M., Friedman, J. I., Fromer, M., Genovese, G., Georgieva, L., Giegling, I., Giusti-Rodriguez, P., Godard, S., Goldstein, J. I., Golimbet, V., Gopal, S., Gratten, J., de Haan, L., Hammer, C., Hamshere, M. L., Hansen, M., Hansen, T., Haroutunian, V., Hartmann, A. M., Henskens, F. A., Herms, S., Hirschhorn, J. N., Hoffmann, P., Hofman, A., Hollegaard, M. V., Hougaard, D. M., Ikeda, M., Joa, I., Julia, A., Kahn, R. S., Kalaydjieva, L., Karachanak-Yankova, S., Karjalainen, J., Kavanagh, D., Keller, M. C., Kennedy, J. L., Khrunin, A., Kim, Y., Klovins, J., Knowles, J. A., Konte, B., Kucinskas, V., Kucinskiene, Z. A., Kuzelova-Ptackova, H., Kahler, A. K., Laurent, C., Keong, J. L., Lee, S. H., Legge, S. E., Lerer, B., Li, M., Li, T., Liang, K., Lieberman, J., Limborska, S., Loughland, C. M., Lubinski, J., Lonnqvist, J., Macek, M., Magnusson, P. K., Maher, B. S., Maier, W., Mallet, J., Marsal, S., Mattheisen, M., Mattingsdal, M., McCarley, R. W., McDonald, C., McIntosh, A. M., Meier, S., Meijer, C. J., Melegh, B., Melle, I., Mesholam-Gately, R. I., Metspalu, A., Michie, P. T., Milani, L., Milanova, V., Mokrab, Y., Morris, D. W., Mors, O., Murphy, K. C., Murray, R. M., Myin-Germeys, I., Mueller-Myhsok, B., Nelis, M., Nenadic, I., Nertney, D. A., Nestadt, G., Nicodemus, K. K., Nikitina-Zake, L., Nisenbaum, L., Nordin, A., O'Callaghan, E., O'Dushlaine, C., O'Neill, F. A., Oh, S., Olincy, A., Olsen, L., van Os, J., Pantelis, C., Papadimitriou, G. N., Papiol, S., Parkhomenko, E., Pato, M. T., Paunio, T., Pejovic-Milovancevic, M., Perkins, D. O., Pietilainen, O., Pimm, J., Pocklington, A. J., Powell, J., Price, A., Pulver, A. E., Purcell, S. M., Quested, D., Rasmussen, H. B., Reichenberg, A., Reimers, M. A., Richards, A. L., Roffman, J. L., Roussos, P., Ruderfer, D. M., Salomaa, V., Sanders, A. R., Schall, U., Schubert, C. R., Schulze, T. G., Schwab, S. G., Scolnick, E. M., Scott, R. J., Seidman, L. J., Shi, J., Sigurdsson, E., Silagadze, T., Silverman, J. M., Sim, K., Slominsky, P., Smoller, J. W., So, H., Spencer, C. C., Stahl, E. A., Stefansson, H., Steinberg, S., Stogmann, E., Straub, R. E., Strengman, E., Strohmaier, J., Stroup, T. S., Subramaniam, M., Suvisaari, J., Svrakic, D. M., Szatkiewicz, J. P., Soderman, E., Thirumalai, S., Toncheva, D., Tosato, S., Veijola, J., Waddington, J., Walsh, D., Wang, D., Wang, Q., Webb, B. T., Weiser, M., Wildenauer, D. B., Williams, N. M., Williams, S., Witt, S. H., Wolen, A. R., Wong, E. H., Wormley, B. K., Xi, H. S., Zai, C. C., Zheng, X., Zimprich, F., Wray, N. R., Stefansson, K., Visscher, P. M., Adolfsson, R., Andreassen, O. A., Blackwood, D. H., Bramon, E., Buxbaum, J. D., Borglum, A. D., Cichon, S., Darvasi, A., Domenici, E., Ehrenreich, H., Esko, T., Gejman, P. V., Gill, M., Gurling, H., Hultman, C. M., Iwata, N., Jablensky, A. V., Jonsson, E. G., Kendler, K. S., Kirov, G., Knight, J., Lencz, T., Levinson, D. F., Li, Q. S., Liu, J., Malhotra, A. K., McCarroll, S. A., McQuillin, A., Moran, J. L., Mortensen, P. B., Mowry, B. J., Noethen, M. M., Ophoff, R. A., Owen, M. J., Palotie, A., Pato, C. N., Petryshen, T. L., Posthuma, D., Rietschel, M., Riley, B. P., Rujescu, D., Sham, P. C., Sklar, P., St Clair, D., Weinberger, D. R., Wendland, J. R., Werge, T., Daly, M. J., Sullivan, P. F., O'Donovan, M. C. 2014; 511 (7510): 421-?

  Abstract

  Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

  View details for DOI 10.1038/nature13595

  View details for Web of Science ID 000339335700037

  View details for PubMedCentralID PMC4112379

• EXTENDED COVERAGE BY NEXT GENERATION SEQUENCING METHODS REFINES THE CHARACTERIZATION OF THE COMMON AND WELL DOCUMENTED HLA ALLELES Fernandez-Vina, M. A., Wang, C., Krishnakumar, S., Levinson, D., Davis, R. W., Mindrinos, M. N. WILEY-BLACKWELL. 2014: 27–28

  View details for Web of Science ID 000337546000054

• CNV analysis in a large schizophrenia sample implicates deletions at 16p12.1 and SLC1A1 and duplications at 1p36.33 and CGNL1 HUMAN MOLECULAR GENETICS Rees, E., Walters, J. T., Chambert, K. D., O'Dushlaine, C., Szatkiewicz, J., Richards, A. L., Georgieva, L., Mahoney-Davies, G., Legge, S. E., Moran, J. L., Genovese, G., Levinson, D., Morris, D. W., Cormican, P., Kendler, K. S., O'Neill, F. A., Riley, B., Gill, M., Corvin, A., Sklar, P., Hultman, C., Pato, C., Pato, M., Sullivan, P. F., Gejman, P. V., McCarroll, S. A., O'Donovan, M. C., Owen, M. J., Kirov, G. 2014; 23 (6): 1669-1676

  Abstract

  Large and rare copy number variants (CNVs) at several loci have been shown to increase risk for schizophrenia. Aiming to discover novel susceptibility CNV loci, we analyzed 6882 cases and 11 255 controls genotyped on Illumina arrays, most of which have not been used for this purpose before. We identified genes enriched for rare exonic CNVs among cases, and then attempted to replicate the findings in additional 14 568 cases and 15 274 controls. In a combined analysis of all samples, 12 distinct loci were enriched among cases with nominal levels of significance (P < 0.05); however, none would survive correction for multiple testing. These loci include recurrent deletions at 16p12.1, a locus previously associated with neurodevelopmental disorders (P = 0.0084 in the discovery sample and P = 0.023 in the replication sample). Other plausible candidates include non-recurrent deletions at the glutamate transporter gene SLC1A1, a CNV locus recently suggested to be involved in schizophrenia through linkage analysis, and duplications at 1p36.33 and CGNL1. A burden analysis of large (>500 kb), rare CNVs showed a 1.2% excess in cases after excluding known schizophrenia-associated loci, suggesting that additional susceptibility loci exist. However, even larger samples are required for their discovery.

  View details for DOI 10.1093/hmg/ddt540

  View details for Web of Science ID 000332044300023

  View details for PubMedID 24163246

  View details for PubMedCentralID PMC3929090

• Reciprocal duplication of the williams-beuren syndrome deletion on chromosome 7q11.23 is associated with schizophrenia. Biological psychiatry Mulle, J. G., Pulver, A. E., McGrath, J. A., Wolyniec, P. S., Dodd, A. F., Cutler, D. J., Sebat, J., Malhotra, D., Nestadt, G., Conrad, D. F., Hurles, M., Barnes, C. P., Ikeda, M., Iwata, N., Levinson, D. F., Gejman, P. V., Sanders, A. R., Duan, J., Mitchell, A. A., Peter, I., Sklar, P., O'Dushlaine, C. T., Grozeva, D., O'Donovan, M. C., Owen, M. J., Hultman, C. M., Kähler, A. K., Sullivan, P. F., Kirov, G., Warren, S. T. 2014; 75 (5): 371-377

  Abstract

  Several copy number variants (CNVs) have been implicated as susceptibility factors for schizophrenia (SZ). Some of these same CNVs also increase risk for autism spectrum disorders, suggesting an etiologic overlap between these conditions. Recently, de novo duplications of a region on chromosome 7q11.23 were associated with autism spectrum disorders. The reciprocal deletion of this region causes Williams-Beuren syndrome.We assayed an Ashkenazi Jewish cohort of 554 SZ cases and 1014 controls for genome-wide CNV. An excess of large rare and de novo CNVs were observed, including a 1.4 Mb duplication on chromosome 7q11.23 identified in two unrelated patients. To test whether this 7q11.23 duplication is also associated with SZ, we obtained data for 14,387 SZ cases and 28,139 controls from seven additional studies with high-resolution genome-wide CNV detection. We performed a meta-analysis, correcting for study population of origin, to assess whether the duplication is associated with SZ.We found duplications at 7q11.23 in 11 of 14,387 SZ cases with only 1 in 28,139 control subjects (unadjusted odds ratio 21.52, 95% confidence interval: 3.13-922.6, p value 5.5 × 10(-5); adjusted odds ratio 10.8, 95% confidence interval: 1.46-79.62, p value .007). Of three SZ duplication carriers with detailed retrospective data, all showed social anxiety and language delay premorbid to SZ onset, consistent with both human studies and animal models of the 7q11.23 duplication.We have identified a new CNV associated with SZ. Reciprocal duplication of the Williams-Beuren syndrome deletion at chromosome 7q11.23 confers an approximately tenfold increase in risk for SZ.

  View details for DOI 10.1016/j.biopsych.2013.05.040

  View details for PubMedID 23871472

• Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals GENOME RESEARCH Battle, A., Mostafavi, S., Zhu, X., Potash, J. B., Weissman, M. M., McCormick, C., Haudenschild, C. D., Beckman, K. B., Shi, J., Mei, R., Urban, A. E., Montgomery, S. B., Levinson, D. F., Koller, D. 2014; 24 (1): 14-24

  Abstract

  Understanding the consequences of regulatory variation in the human genome remains a major challenge, with important implications for understanding gene regulation and interpreting the many disease-risk variants that fall outside of protein-coding regions. Here, we provide a direct window into the regulatory consequences of genetic variation by sequencing RNA from 922 genotyped individuals. We present a comprehensive description of the distribution of regulatory variation-by the specific expression phenotypes altered, the properties of affected genes, and the genomic characteristics of regulatory variants. We detect variants influencing expression of over ten thousand genes, and through the enhanced resolution offered by RNA-sequencing, for the first time we identify thousands of variants associated with specific phenotypes including splicing and allelic expression. Evaluating the effects of both long-range intra-chromosomal and trans (cross-chromosomal) regulation, we observe modularity in the regulatory network, with three-dimensional chromosomal configuration playing a particular role in regulatory modules within each chromosome. We also observe a significant depletion of regulatory variants affecting central and critical genes, along with a trend of reduced effect sizes as variant frequency increases, providing evidence that purifying selection and buffering have limited the deleterious impact of regulatory variation on the cell. Further, generalizing beyond observed variants, we have analyzed the genomic properties of variants associated with expression and splicing and developed a Bayesian model to predict regulatory consequences of genetic variants, applicable to the interpretation of individual genomes and disease studies. Together, these results represent a critical step toward characterizing the complete landscape of human regulatory variation.

  View details for DOI 10.1101/gr.155192.113

  View details for PubMedID 24092820

• Evidence that duplications of 22q11.2 protect against schizophrenia MOLECULAR PSYCHIATRY Rees, E., Kirov, G., Sanders, A., Walters, J. T., Chambert, K. D., Shi, J., Szatkiewicz, J., O'Dushlaine, C., Richards, A. L., Green, E. K., Jones, I., Davies, G., Legge, S. E., Moran, J. L., Pato, C., Pato, M., Genovese, G., Levinson, D., Duan, J., MOY, W., Goering, H. H., Morris, D., Cormican, P., Kendler, K. S., O'Neill, F. A., Riley, B., Gill, M., Corvin, A., Craddock, N., Sklar, P., Hultman, C., Sullivan, P. F., GEJMAN, P. V., McCarroll, S. A., O'Donovan, M. C., Owen, M. J. 2014; 19 (1): 37-40

  Abstract

  A number of large, rare copy number variants (CNVs) are deleterious for neurodevelopmental disorders, but large, rare, protective CNVs have not been reported for such phenotypes. Here we show in a CNV analysis of 47 005 individuals, the largest CNV analysis of schizophrenia to date, that large duplications (1.5-3.0 Mb) at 22q11.2--the reciprocal of the well-known, risk-inducing deletion of this locus--are substantially less common in schizophrenia cases than in the general population (0.014% vs 0.085%, OR=0.17, P=0.00086). 22q11.2 duplications represent the first putative protective mutation for schizophrenia.

  View details for DOI 10.1038/mp.2013.156

  View details for Web of Science ID 000328964700010

  View details for PubMedID 24217254

  View details for PubMedCentralID PMC3873028

• POSTTRAUMATIC STRESS DISORDER INCREASES RISK FOR SUICIDE ATTEMPT IN ADULTS WITH RECURRENT MAJOR DEPRESSION DEPRESSION AND ANXIETY Stevens, D., Wilcox, H. C., MacKinnon, D. F., Mondimore, F. M., Schweizer, B., Jancic, D., Coryell, W. H., Weissman, M. M., Levinson, D. F., Potash, J. B. 2013; 30 (10): 940-946

  Abstract

  Genetics of Recurrent Early-Onset Depression study (GenRED II) data were used to examine the relationship between posttraumatic stress disorder (PTSD) and attempted suicide in a population of 1,433 individuals with recurrent early-onset major depressive disorder (MDD). We tested the hypothesis that PTSD resulting from assaultive trauma increases risk for attempted suicide among individuals with recurrent MDD.Data on lifetime trauma exposures and clinical symptoms were collected using the Diagnostic Interview for Genetic Studies version 3.0 and best estimate diagnoses of MDD, PTSD, and other DSM-IV Axis I disorders were reported with best estimated age of onset.The lifetime prevalence of suicide attempt in this sample was 28%. Lifetime PTSD was diagnosed in 205 (14.3%) participants. We used discrete time-survival analyses to take into account timing in the PTSD-suicide attempt relationship while adjusting for demographic variables (gender, race, age, and education level) and comorbid diagnoses prior to trauma exposure. PTSD was an independent predictor of subsequent suicide attempt (HR = 2.5, 95% CI: 1.6, 3.8; P < .0001). Neither assaultive nor nonassaultive trauma without PTSD significantly predicted subsequent suicide attempt after Bonferroni correction. The association between PTSD and subsequent suicide attempt was driven by traumatic events involving assaultive violence (HR = 1.7, 95% CI: 1.3, 2.2; P< .0001).Among those with recurrent MDD, PTSD appears to be a vulnerability marker of maladaptive responses to traumatic events and an independent risk factor for attempted suicide. Additional studies examining differences between those with and without PTSD on biological measures might shed light on this potential vulnerability.

  View details for DOI 10.1002/da.22160

  View details for Web of Science ID 000325481400008

  View details for PubMedID 23893768

• Additive Genetic Variation in Schizophrenia Risk Is Shared by Populations of African and European Descent AMERICAN JOURNAL OF HUMAN GENETICS de Candia, T. R., Lee, S. H., Yang, J., Browning, B. L., Gejman, P. V., Levinson, D. F., Mowry, B. J., Hewitt, J. K., Goddard, M. E., O'Donovan, M. C., Purcell, S. M., Posthuma, D., Visscher, P. M., Wray, N. R., Keller, M. C. 2013; 93 (3): 463-470

  Abstract

  To investigate the extent to which the proportion of schizophrenia's additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control genome-wide association study (GWAS) data set available, the Molecular Genetics of Schizophrenia (MGS) data set. We show how a method that uses genomic similarities at measured SNPs to estimate the additive genetic correlation (SNP correlation [SNP-rg]) between traits can be extended to estimate SNP-rg for the same trait between ethnicities. We estimated SNP-rg for schizophrenia between the MGS ED and MGS AD samples to be 0.66 (SE = 0.23), which is significantly different from 0 (p(SNP-rg = 0) = 0.0003), but not 1 (p(SNP-rg = 1) = 0.26). We re-estimated SNP-rg between an independent ED data set (n = 6,665) and the MGS AD sample to be 0.61 (SE = 0.21, p(SNP-rg = 0) = 0.0003, p(SNP-rg = 1) = 0.16). These results suggest that many schizophrenia risk alleles are shared across ethnic groups and predate African-European divergence.

  View details for DOI 10.1016/j.ajhg.2013.07.007

  View details for Web of Science ID 000330268900005

  View details for PubMedID 23954163

  View details for PubMedCentralID PMC3845872

• Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs NATURE GENETICS Lee, S. H., Ripke, S., Neale, B. M., Faraone, S. V., Purcell, S. M., Perlis, R. H., Mowry, B. J., Thapar, A., Goddard, M. E., Witte, J. S., Absher, D., Agartz, I., Akil, H., Amin, F., Andreassen, O. A., Anjorin, A., Anney, R., Anttila, V., Arking, D. E., Asherson, P., Azevedo, M. H., Backlund, L., Badner, J. A., Bailey, A. J., Banaschewski, T., Barchas, J. D., Barnes, M. R., Barrett, T. B., Bass, N., Battaglia, A., Bauer, M., Bayes, M., Bellivier, F., Bergen, S. E., Berrettini, W., Betancur, C., Bettecken, T., Biederman, J., Binder, E. B., Black, D. W., Blackwood, D. H., Bloss, C. S., Boehnke, M., Boomsma, D. I., Breen, G., Breuer, R., Bruggeman, R., Cormican, P., Buccola, N. G., Buitelaar, J. K., Bunney, W. E., Buxbaum, J. D., Byerley, W. F., Byrne, E. M., Caesar, S., Cahn, W., Cantor, R. M., Casas, M., Chakravarti, A., Chambert, K., Choudhury, K., Cichon, S., Cloninger, C. R., Collier, D. A., Cook, E. H., Coon, H., Cormand, B., Corvin, A., Coryell, W. H., Craig, D. W., Craig, I. W., Crosbie, J., Cuccaro, M. L., Curtis, D., Czamara, D., Datta, S., Dawson, G., Day, R., de Geus, E. J., Degenhardt, F., Djurovic, S., Donohoe, G. J., Doyle, A. E., Duan, J., Dudbridge, F., Duketis, E., Ebstein, R. P., Edenberg, H. J., Elia, J., Ennis, S., Etain, B., Fanous, A., Farmer, A. E., Ferrier, I. N., Flickinger, M., Fombonne, E., Foroud, T., Frank, J., Franke, B., Fraser, C., Freedman, R., Freimer, N. B., Freitag, C. M., Friedl, M., Frisen, L., Gallagher, L., Gejman, P. V., Georgieva, L., Gershon, E. S., Geschwind, D. H., Giegling, I., Gill, M., Gordon, S. D., Gordon-Smith, K., Green, E. K., Greenwood, T. A., Grice, D. E., Gross, M., Grozeva, D., Guan, W., Gurling, H., de Haan, L., Haines, J. L., Hakonarson, H., Hallmayer, J., Hamilton, S. P., Hamshere, M. L., Hansen, T. F., Hartmann, A. M., Hautzinger, M., Heath, A. C., Henders, A. K., Herms, S., Hickie, I. B., Hipolito, M., Hoefels, S., Holmans, P. A., Holsboer, F., Hoogendijk, W. J., Hottenga, J., Hultman, C. M., Hus, V., Ingason, A., Ising, M., Jamain, S., Jones, E. G., Jones, I., Jones, L., Tzeng, J., Kaehler, A. K., Kahn, R. S., Kandaswamy, R., Keller, M. C., Kennedy, J. L., Kenny, E., Kent, L., Kim, Y., Kirov, G. K., Klauck, S. M., Klei, L., Knowles, J. A., Kohli, M. A., Koller, D. L., Konte, B., Korszun, A., Krabbendam, L., Krasucki, R., Kuntsi, J., Kwan, P., Landen, M., Langstrom, N., Lathrop, M., Lawrence, J., Lawson, W. B., Leboyer, M., Ledbetter, D. H., Lee, P. H., Lencz, T., Lesch, K., Levinson, D. F., Lewis, C. M., Li, J., Lichtenstein, P., Lieberman, J. A., Lin, D., Linszen, D. H., Liu, C., Lohoff, F. W., Loo, S. K., Lord, C., Lowe, J. K., Lucae, S., MacIntyre, D. J., Madden, P. A., Maestrini, E., Magnusson, P. K., Mahon, P. B., Maier, W., Malhotra, A. K., Mane, S. M., Martin, C. L., Martin, N. G., Mattheisen, M., Matthews, K., Mattingsdal, M., McCarroll, S. A., McGhee, K. A., McGough, J. J., McGrath, P. J., McGuffin, P., McInnis, M. G., McIntosh, A., McKinney, R., McLean, A. W., McMahon, F. J., McMahon, W. M., McQuillin, A., Medeiros, H., Medland, S. E., Meier, S., Melle, I., Meng, F., Meyer, J., Middeldorp, C. M., Middleton, L., Milanova, V., Miranda, A., Monaco, A. P., Montgomery, G. W., Moran, J. L., Moreno-De-Luca, D., Morken, G., Morris, D. W., Morrow, E. M., Moskvina, V., Muglia, P., Muehleisen, T. W., Muir, W. J., Mueller-Myhsok, B., Murtha, M., Myers, R. M., Myin-Germeys, I., Neale, M. C., Nelson, S. F., Nievergelt, C. M., Nikolov, I., Nimgaonkar, V., Nolen, W. A., Noethen, M. M., Nurnberger, J. I., Nwulia, E. A., Nyholt, D. R., O'Dushlaine, C., Oades, R. D., Olincy, A., Oliveira, G., Olsen, L., Ophoff, R. A., Osby, U., Owen, M. J., Palotie, A., Parr, J. R., Paterson, A. D., Pato, C. N., Pato, M. T., Penninx, B. W., Pergadia, M. L., Pericak-Vance, M. A., Pickard, B. S., Pimm, J., Piven, J., Posthuma, D., Potash, J. B., Poustka, F., Propping, P., Puri, V., Quested, D. J., Quinn, E. M., Antoni Ramos-Quiroga, J., Rasmussen, H. B., Raychaudhuri, S., Rehnstroem, K., Reif, A., Ribases, M., Rice, J. P., Rietschel, M., Roeder, K., Roeyers, H., Rossin, L., Rothenberger, A., Rouleau, G., Ruderfer, D., Rujescu, D., Sanders, A. R., Sanders, S. J., Santangelo, S. L., Sergeant, J. A., Schachar, R., Schalling, M., Schatzberg, A. F., Scheftner, W. A., Schellenberg, G. D., Scherer, S. W., Schork, N. J., Schulze, T. G., Schumacher, J., Schwarz, M., Scolnick, E., Scott, L. J., Shi, J., Shilling, P. D., Shyn, S. I., Silverman, J. M., Slager, S. L., Smalley, S. L., Smit, J. H., Smith, E. N., Sonuga-Barke, E. J., St Clair, D., State, M., Steffens, M., Steinhausen, H., Strauss, J. S., Strohmaier, J., Stroup, T. S., Sutcliffe, J. S., Szatmari, P., Szelinger, S., Thirumalai, S., Thompson, R. C., Todorov, A. A., Tozzi, F., Treutlein, J., Uhr, M., van den Oord, E. J., Van Grootheest, G., van Os, J., Vicente, A. M., Vieland, V. J., Vincent, J. B., Visscher, P. M., Walsh, C. A., Wassink, T. H., Watson, S. J., Weissman, M. M., Werge, T., Wienker, T. F., Wijsman, E. M., Willemsen, G., Williams, N., Willsey, A. J., Witt, S. H., Xu, W., Young, A. H., Yu, T. W., Zammit, S., Zandi, P. P., Zhang, P., Zitman, F. G., Zoellner, S., Devlin, B., Kelsoe, J. R., Sklar, P., Daly, M. J., O'Donovan, M. C., Craddock, N., Sullivan, P. F., Smoller, J. W., Kendler, K. S., Wray, N. R. 2013; 45 (9): 984-?

  Abstract

  Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

  View details for DOI 10.1038/ng.2711

  View details for Web of Science ID 000323748200007

  View details for PubMedID 23933821

  View details for PubMedCentralID PMC3800159

• Genotyping serotonin transporter polymorphisms 5-HTTLPR and rs25531 in European- and African-American subjects from the National Institute of Mental Health's Collaborative Center for Genomic Studies TRANSLATIONAL PSYCHIATRY Odgerel, Z., Talati, A., Hamilton, S. P., Levinson, D. F., Weissman, M. M. 2013; 3

  Abstract

  A number of studies have suggested DNA sequence variability in the serotonin transporter gene (SLC6A4) between European-American (EA) and African-American (AA) populations, which could be clinically important, given the central role SLC6A4 has in serotonin transmission. However, these studies have had relatively small samples, used self-reported measures of race, and have only tested the promoter-linked polymorphism 5-HTTLPR. Here we genotype 5-HTTLPR and rs25531, a neighboring functional polymorphism, in 954 AA and 2622EA subjects from a National Institute of Mental Health repository sample. Genotyping was performed using fragment analysis by capillary electrophoresis. AA, as compared with EA, groups had lower frequencies of the S allele (0.25 vs 0.43) and SS genotype (0.06 vs 0.19) at 5-HTTLPR, and higher rates of the G allele at rs25531 (0.21 vs 0.075). A rare xL variant at 5-HTTLPR was also more common among AAs (0.017 vs 0.008). When the polymorphisms were redefined into a high- and low-transcription haplotypes, the AA group showed significantly fewer low-transcription variants (χ(2)=4.8, P=0.03). No genotypes were associated with major depression, any anxiety disorder, or neuroticism in either EA or AA populations. This is the largest study to show SLC6A4 genotype differences between EA and AA populations, and the first to include rs25531. Lack of associations with clinical outcomes may reflect untested moderating environmental influences.

  View details for DOI 10.1038/tp.2013.80

  View details for Web of Science ID 000327472300010

  View details for PubMedID 24064711

  View details for PubMedCentralID PMC3784769

• Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nature genetics Berndt, S. I., Gustafsson, S., Mägi, R., Ganna, A., Wheeler, E., Feitosa, M. F., Justice, A. E., Monda, K. L., Croteau-Chonka, D. C., Day, F. R., Esko, T., Fall, T., Ferreira, T., Gentilini, D., Jackson, A. U., Luan, J., Randall, J. C., Vedantam, S., Willer, C. J., Winkler, T. W., Wood, A. R., Workalemahu, T., Hu, Y., Lee, S. H., Liang, L., Lin, D., Min, J. L., Neale, B. M., Thorleifsson, G., Yang, J., Albrecht, E., Amin, N., Bragg-Gresham, J. L., Cadby, G., den Heijer, M., Eklund, N., Fischer, K., Goel, A., Hottenga, J., Huffman, J. E., Jarick, I., Johansson, A., Johnson, T., Kanoni, S., Kleber, M. E., König, I. R., Kristiansson, K., Kutalik, Z., Lamina, C., Lecoeur, C., Li, G., Mangino, M., McArdle, W. L., Medina-Gomez, C., Müller-Nurasyid, M., Ngwa, J. S., Nolte, I. M., Paternoster, L., Pechlivanis, S., Perola, M., Peters, M. J., Preuss, M., Rose, L. M., Shi, J., Shungin, D., Smith, A. V., Strawbridge, R. J., Surakka, I., Teumer, A., Trip, M. D., Tyrer, J., van Vliet-Ostaptchouk, J. V., Vandenput, L., Waite, L. L., Zhao, J. H., Absher, D., Asselbergs, F. W., Atalay, M., Attwood, A. P., Balmforth, A. J., Basart, H., Beilby, J., Bonnycastle, L. L., Brambilla, P., Bruinenberg, M., Campbell, H., Chasman, D. I., Chines, P. S., Collins, F. S., Connell, J. M., Cookson, W. O., de Faire, U., de Vegt, F., Dei, M., Dimitriou, M., Edkins, S., Estrada, K., Evans, D. M., Farrall, M., Ferrario, M. M., Ferrières, J., Franke, L., Frau, F., Gejman, P. V., Grallert, H., Grönberg, H., Gudnason, V., Hall, A. S., Hall, P., Hartikainen, A., Hayward, C., Heard-Costa, N. L., Heath, A. C., Hebebrand, J., Homuth, G., Hu, F. B., Hunt, S. E., Hyppönen, E., Iribarren, C., Jacobs, K. B., Jansson, J., Jula, A., Kähönen, M., Kathiresan, S., Kee, F., Khaw, K., Kivimäki, M., Koenig, W., Kraja, A. T., Kumari, M., Kuulasmaa, K., Kuusisto, J., Laitinen, J. H., Lakka, T. A., Langenberg, C., Launer, L. J., Lind, L., Lindström, J., Liu, J., Liuzzi, A., Lokki, M., Lorentzon, M., Madden, P. A., Magnusson, P. K., Manunta, P., Marek, D., März, W., Mateo Leach, I., McKnight, B., Medland, S. E., Mihailov, E., Milani, L., Montgomery, G. W., Mooser, V., Mühleisen, T. W., Munroe, P. B., Musk, A. W., Narisu, N., Navis, G., Nicholson, G., Nohr, E. A., Ong, K. K., Oostra, B. A., Palmer, C. N., Palotie, A., Peden, J. F., Pedersen, N., Peters, A., Polasek, O., Pouta, A., Pramstaller, P. P., Prokopenko, I., Pütter, C., Radhakrishnan, A., Raitakari, O., Rendon, A., Rivadeneira, F., Rudan, I., Saaristo, T. E., Sambrook, J. G., Sanders, A. R., Sanna, S., Saramies, J., Schipf, S., Schreiber, S., Schunkert, H., Shin, S., Signorini, S., Sinisalo, J., Skrobek, B., Soranzo, N., Stancáková, A., Stark, K., Stephens, J. C., Stirrups, K., Stolk, R. P., Stumvoll, M., Swift, A. J., Theodoraki, E. V., Thorand, B., Tregouet, D., Tremoli, E., van der Klauw, M. M., van Meurs, J. B., Vermeulen, S. H., Viikari, J., Virtamo, J., Vitart, V., Waeber, G., Wang, Z., Widén, E., Wild, S. H., Willemsen, G., Winkelmann, B. R., Witteman, J. C., Wolffenbuttel, B. H., Wong, A., Wright, A. F., Zillikens, M. C., Amouyel, P., Boehm, B. O., Boerwinkle, E., Boomsma, D. I., Caulfield, M. J., Chanock, S. J., Cupples, L. A., Cusi, D., Dedoussis, G. V., Erdmann, J., Eriksson, J. G., Franks, P. W., Froguel, P., Gieger, C., Gyllensten, U., Hamsten, A., Harris, T. B., Hengstenberg, C., Hicks, A. A., Hingorani, A., Hinney, A., Hofman, A., Hovingh, K. G., Hveem, K., Illig, T., Jarvelin, M., Jöckel, K., Keinanen-Kiukaanniemi, S. M., Kiemeney, L. A., Kuh, D., Laakso, M., Lehtimäki, T., Levinson, D. F., Martin, N. G., Metspalu, A., Morris, A. D., Nieminen, M. S., Njølstad, I., Ohlsson, C., Oldehinkel, A. J., Ouwehand, W. H., Palmer, L. J., Penninx, B., Power, C., Province, M. A., Psaty, B. M., Qi, L., Rauramaa, R., Ridker, P. M., Ripatti, S., Salomaa, V., Samani, N. J., Snieder, H., Sørensen, T. I., Spector, T. D., Stefansson, K., Tönjes, A., Tuomilehto, J., Uitterlinden, A. G., Uusitupa, M., van der Harst, P., Vollenweider, P., Wallaschofski, H., Wareham, N. J., Watkins, H., Wichmann, H., Wilson, J. F., Abecasis, G. R., Assimes, T. L., Barroso, I., Boehnke, M., Borecki, I. B., Deloukas, P., Fox, C. S., Frayling, T., Groop, L. C., Haritunian, T., Heid, I. M., Hunter, D., Kaplan, R. C., Karpe, F., Moffatt, M. F., Mohlke, K. L., O'Connell, J. R., Pawitan, Y., Schadt, E. E., Schlessinger, D., Steinthorsdottir, V., Strachan, D. P., Thorsteinsdottir, U., van Duijn, C. M., Visscher, P. M., Di Blasio, A. M., Hirschhorn, J. N., Lindgren, C. M., Morris, A. P., Meyre, D., Scherag, A., McCarthy, M. I., Speliotes, E. K., North, K. E., Loos, R. J., Ingelsson, E. 2013; 45 (5): 501-512

  Abstract

  Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

  View details for DOI 10.1038/ng.2606

  View details for PubMedID 23563607

  View details for PubMedCentralID PMC3973018

• A mega-analysis of genome-wide association studies for major depressive disorder MOLECULAR PSYCHIATRY Sullivan, P. F., Daly, M. J., Ripke, S., Lewis, C. M., Lin, D., Wray, N. R., Neale, B., Levinson, D. F., Breen, G., Byrne, E. M., Wray, N. R., Levinson, D. F., Rietschel, M., Hoogendijk, W., Ripke, S., Sullivan, P. F., Hamilton, S. P., Levinson, D. F., Ripke, S., Weissman, M. M., Wray, N. R., Breuer, R., Cichon, S., Degenhardt, F., Frank, J., Gross, M., Herms, S., Hoefels, S., Maier, W., Mattheisen, M., Noeethen, M. M., Rietschel, M., Schulze, T. G., Steffens, M., Treutlein, J., Boomsma, D. I., de Geus, E. J., Hoogendijk, W., Hottenga, J. J., Jung-Ying, T., Lin, D., Middeldorp, C. M., Nolen, W. A., Penninx, B. P., Smit, J. H., Sullivan, P. F., Van Grootheest, G., Willemsen, G., Zitman, F. G., Coryell, W. H., Knowles, J. A., Lawson, W. B., Levinson, D. F., Potash, J. B., Scheftner, W. A., Shi, J., Weissman, M. M., Holsboer, F., Muglia, P., Tozzi, F., Blackwood, D. H., Boomsma, D. I., de Geus, E. J., Hottenga, J. J., MacIntyre, D. J., McIntosh, A., McLean, A., Middeldorp, C. M., Nolen, W. A., Penninx, B. P., Ripke, S., Smit, J. H., Sullivan, P. F., Van Grootheest, G., Willemsen, G., Zitman, F. G., van den Oord, E. J., Holsboer, F., Lucae, S., Binder, E., Mueller-Myhsok, B., Ripke, S., Czamara, D., Kohli, M. A., Ising, M., Uhr, M., Bettecken, T., Barnes, M. R., Breen, G., Craig, I. W., Farmer, A. E., McGuffin, P., Muglia, P., Byrne, E., Gordon, S. D., Heath, A. C., Henders, A. K., Hickie, I. B., Madden, P. A., Martin, N. G., Montgomery, G. M., Nyholt, D. R., Pergadia, M. L., Wray, N. R., Hamilton, S. P., McGrath, P. J., Shyn, S. I., Slager, S. L., Oskarsson, H., Sigurdsson, E., Stefansson, H., Stefansson, K., Steinberg, S., Thorgeirsson, T., Levinson, D. F., Potash, J. B., Shi, J., Weissman, M. M., Guipponi, M., Lewis, G., O'Donovan, M., Tansey, K. E., Uher, R., Coryell, W. H., Knowles, J. A., Lawson, W. B., Levinson, D. F., Potash, J. B., Scheftner, W. A., Shi, J., Weissman, M. M., Castro, V. M., Churchill, S. E., Fava, M., Gainer, V. S., Gallagher, P. J., Goryachev, S., Iosifescu, D. V., Kohane, I. S., Murphy, S. N., Perlis, R. H., Smoller, J. W., Weilburg, J. B., Kutalik, Z., Preisig, M., Grabe, H. J., Nauck, M., Schulz, A., Teumer, A., Voelzke, H., Landen, M., Lichtenstein, P., Magnusson, P., Pedersen, N., Viktorin, A. 2013; 18 (4): 497-511

  Abstract

  Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

  View details for DOI 10.1038/mp.2012.21

  View details for Web of Science ID 000316568600016

  View details for PubMedCentralID PMC3837431

• Implication of a Rare Deletion at Distal 16p11.2 in Schizophrenia JAMA PSYCHIATRY Guha, S., Rees, E., Darvasi, A., Ivanov, D., Ikeda, M., Bergen, S. E., Magnusson, P. K., Cormican, P., Morris, D., Gill, M., Cichon, S., Rosenfeld, J. A., Lee, A., Gregersen, P. K., Kane, J. M., Malhotra, A. K., Rietschel, M., Noethen, M. M., Degenhardt, F., Priebe, L., Breuer, R., Strohmaier, J., Ruderfer, D. M., Moran, J. L., Chambert, K. D., Sanders, A. R., Shi, J., Kendler, K., Riley, B., O'Neill, T., Walsh, D., Malhotra, D., Corvin, A., Purcell, S., Sklar, P., Iwata, N., Hultman, C. M., Sullivan, P. F., Sebat, J., McCarthy, S., Gejman, P. V., Levinson, D. F., Owen, M. J., O'Donovan, M. C., Lencz, T., Kirov, G. 2013; 70 (3): 253-260

  Abstract

  Large genomic copy number variations have been implicated as strong risk factors for schizophrenia. However, the rarity of these events has created challenges for the identification of further pathogenic loci, and extremely large samples are required to provide convincing replication.To detect novel copy number variations that increase the susceptibility to schizophrenia by using 2 ethnically homogeneous discovery cohorts and replication in large samples.Genetic association study of microarray data.Samples of DNA were collected at 9 sites from different countries.Two discovery cohorts consisted of 790 cases with schizophrenia and schizoaffective disorder and 1347 controls of Ashkenazi Jewish descent and 662 parent-offspring trios from Bulgaria, of which the offspring had schizophrenia or schizoaffective disorder. Replication data sets consisted of 12,398 cases and 17,945 controls.Statistically increased rate of specific copy number variations in cases vs controls.One novel locus was implicated: a deletion at distal 16p11.2, which does not overlap the proximal 16p11.2 locus previously reported in schizophrenia and autism. Deletions at this locus were found in 13 of 13,850 cases (0.094%) and 3 of 19,954 controls (0.015%) (odds ratio, 6.25 [95% CI, 1.78-21.93]; P = .001, Fisher exact test).Deletions at distal 16p11.2 have been previously implicated in developmental delay and obesity. The region contains 9 genes, several of which are implicated in neurological diseases, regulation of body weight, and glucose homeostasis. A telomeric extension of the deletion, observed in about half the cases but no controls, potentially implicates an additional 8 genes. Our findings add a new locus to the list of copy number variations that increase the risk for development of schizophrenia.

  View details for DOI 10.1001/2013.jamapsychiatry.71

  View details for Web of Science ID 000316730300002

  View details for PubMedID 23325106

• Normalizing RNA-Sequencing Data by Modeling Hidden Covariates with Prior Knowledge. PloS one Mostafavi, S., Battle, A., Zhu, X., Urban, A. E., Levinson, D., Montgomery, S. B., Koller, D. 2013; 8 (7)

  View details for DOI 10.1371/journal.pone.0068141

  View details for PubMedID 23874524

• Normalizing RNA-sequencing data by modeling hidden covariates with prior knowledge. PloS one Mostafavi, S., Battle, A., Zhu, X., Urban, A. E., Levinson, D., Montgomery, S. B., Koller, D. 2013; 8 (7)

  Abstract

  Transcriptomic assays that measure expression levels are widely used to study the manifestation of environmental or genetic variations in cellular processes. RNA-sequencing in particular has the potential to considerably improve such understanding because of its capacity to assay the entire transcriptome, including novel transcriptional events. However, as with earlier expression assays, analysis of RNA-sequencing data requires carefully accounting for factors that may introduce systematic, confounding variability in the expression measurements, resulting in spurious correlations. Here, we consider the problem of modeling and removing the effects of known and hidden confounding factors from RNA-sequencing data. We describe a unified residual framework that encapsulates existing approaches, and using this framework, present a novel method, HCP (Hidden Covariates with Prior). HCP uses a more informed assumption about the confounding factors, and performs as well or better than existing approaches while having a much lower computational cost. Our experiments demonstrate that accounting for known and hidden factors with appropriate models improves the quality of RNA-sequencing data in two very different tasks: detecting genetic variations that are associated with nearby expression variations (cis-eQTLs), and constructing accurate co-expression networks.

  View details for DOI 10.1371/journal.pone.0068141

  View details for PubMedID 23874524

• Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010 LANCET Murray, C. J., Vos, T., Lozano, R., Naghavi, M., Flaxman, A. D., Michaud, C., Ezzati, M., Shibuya, K., Salomon, J. A., Abdalla, S., Aboyans, V., Abraham, J., Ackerman, I., Aggarwal, R., Ahn, S. Y., Ali, M. K., Alvarado, M., Anderson, H. R., Anderson, L. M., Andrews, K. G., Atkinson, C., Baddour, L. M., Bahalim, A. N., Barker-Collo, S., Barrero, L. H., Bartels, D. H., Basanez, M., Baxter, A., Bell, M. L., Benjamin, E. J., Bennett, D., Bernabe, E., Bhalla, K., Bhandari, B., Bikbov, B., Bin Abdulhak, A., Birbeck, G., Black, J. A., Blencowe, H., Blore, J. D., Blyth, F., Bolliger, I., Bonaventure, A., Boufous, S. A., Bourne, R., Boussinesq, M., Braithwaite, T., Brayne, C., Bridgett, L., Brooker, S., Brooks, P., Brugha, T. S., Bryan-Hancock, C., Bucello, C., Buchbinder, R., Buckle, G., Budke, C. M., Burch, M., Burney, P., Burstein, R., Calabria, B., Campbell, B., Canter, C. E., Carabin, H., Carapetis, J., Carmona, L., Cella, C., Charlson, F., Chen, H., Cheng, A. T., Chou, D., Chugh, S. S., Coffeng, L. E., Colan, S. D., Colquhoun, S., Colson, K. E., Condon, J., Connor, M. D., Cooper, L. T., Corriere, M., Cortinovis, M., de Vaccaro, K. C., Couser, W., Cowie, B. C., Criqui, M. H., Cross, M., Dabhadkar, K. C., Dahiya, M., Dahodwala, N., Damsere-Derry, J., Danaei, G., Davis, A., De Leo, D., Degenhardt, L., Dellavalle, R., Delossantos, A., Denenberg, J., Derrett, S., Des Jarlais, D. C., Dharmaratne, S. D., Dherani, M., Diaz-Torne, C., Dolk, H., Dorsey, E. R., Driscoll, T., Duber, H., Ebel, B., Edmond, K., Elbaz, A., Ali, S. E., Erskine, H., Erwin, P. J., Espindola, P., Ewoigbokhan, S. E., Farzadfar, F., Feigin, V., Felson, D. T., Ferrari, A., Ferri, C. P., Fevre, E. M., Finucane, M. M., Flaxman, S., Flood, L., Foreman, K., Forouzanfar, M. H., Fowkes, F. G., Fransen, M., Freeman, M. K., Gabbe, B. J., Gabriel, S. E., Gakidou, E., Ganatra, H. A., Garcia, B., Gaspari, F., Gillum, R. F., Gmel, G., Gonzalez-Medina, D., Gosselin, R., Grainger, R., Grant, B., Groeger, J., Guillemin, F., Gunnell, D., Gupta, R., Haagsma, J., Hagan, H., Halasa, Y. A., Hall, W., Haring, D., Maria Haro, J., Harrison, J. E., Havmoeller, R., Hay, R. J., Higashi, H., Hill, C., Hoen, B., Hoffman, H., Hotez, P. J., Hoy, D., Huang, J. J., Ibeanusi, S. E., Jacobsen, K. H., James, S. L., Jarvis, D., Jasrasaria, R., Jayaraman, S., Johns, N., Jonas, J. B., Karthikeyan, G., Kassebaum, N., Kawakami, N., Keren, A., Khoo, J., King, C. H., Knowlton, L. M., Kobusingye, O., Koranteng, A., Krishnamurthi, R., Laden, F., Lalloo, R., Laslett, L. L., Lathlean, T., Leasher, J. L., Lee, Y. Y., Leigh, J., Levinson, D., Lim, S. S., Limb, E., Lin, J. K., Lipnick, M., Lipshultz, S. E., Liu, W., Loane, M., Ohno, S. L., Lyons, R., Mabweijano, J., MacIntyre, M. F., Malekzadeh, R., Mallinger, L., Manivannan, S., Marcenes, W., March, L., Margolis, D. J., Marks, G. B., Marks, R., Matsumori, A., Matzopoulos, R., Mayosi, B. M., McAnulty, J. H., McDermott, M. M., McGill, N., McGrath, J., Elena Medina-Mora, M., Meltzer, M., Mensah, G. A., Merriman, T. R., Meyer, A., Miglioli, V., Miller, M., Miller, T. R., Mitchell, P. B., Mock, C., Mocumbi, A. O., Moffitt, T. E., Mokdad, A. A., Monasta, L., Montico, M., Moradi-Lakeh, M., Moran, A., Morawska, L., Mori, R., Murdoch, M. E., Mwaniki, M. K., Naidoo, K., Nair, M. N., Naldi, L., Narayan, K. M., Nelson, P. K., Nelson, R. G., Nevitt, M. C., Newton, C. R., Nolte, S., Norman, P., Norman, R., O'Donnell, M., O'Hanlon, S., Olives, C., Omer, S. B., Ortblad, K., Osborne, R., Ozgediz, D., Page, A., Pahari, B., Pandian, J. D., Panozo Rivero, A., Patten, S. B., Pearce, N., Perez Padilla, R., Perez-Ruiz, F., Perico, N., Pesudovs, K., Phillips, D., Phillips, M. R., Pierce, K., Pion, S., Polanczyk, G. V., Polinder, S., Pope, C. A., Popova, S., Porrini, E., Pourmalek, F., Prince, M., Pullan, R. L., Ramaiah, K. D., Ranganathan, D., Razavi, H., Regan, M., Rehm, J. T., Rein, D. B., Remuzzi, G., Richardson, K., Rivara, F. P., Roberts, T., Robinson, C., Rodriguez De Leon, F., Ronfani, L., Room, R., Rosenfeld, L. C., Rushton, L., Sacco, R. L., Saha, S., Sampson, U., Sanchez-Riera, L., Sanman, E., Schwebel, D. C., Scott, J. G., Segui-Gomez, M., Shahraz, S., Shepard, D. S., Shin, H., Shivakoti, R., Singh, D., Singh, G. M., Singh, J. A., Singleton, J., Sleet, D. A., Sliwa, K., Smith, E., Smith, J. L., Stapelberg, N. J., Steer, A., Steiner, T., Stolk, W. A., Stovner, L. J., Sudfeld, C., Syed, S., Tamburlini, G., Tavakkoli, M., Taylor, H. R., Taylor, J. A., Taylor, W. J., Thomas, B., Thomson, W. M., Thurston, G. D., Tleyjeh, I. M., Tonelli, M., Towbin, J. R., Truelsen, T., Tsilimbaris, M. K., Ubeda, C., Undurraga, E. A., Van der Werf, M. J., van Os, J., Vavilala, M. S., Venketasubramanian, N., Wang, M., Wang, W., Watt, K., Weatherall, D. J., Weinstock, M. A., Weintraub, R., Weisskopf, M. G., Weissman, M. M., White, R. A., Whiteford, H., Wiebe, N., Wiersma, S. T., Wilkinson, J. D., Williams, H. C., Williams, S. R., Witt, E., Wolfe, F., Woolf, A. D., Wulf, S., Yeh, P., Zaidi, A. K., Zheng, Z., Zonies, D., Lopez, A. D. 2012; 380 (9859): 2197-2223

  Abstract

  Measuring disease and injury burden in populations requires a composite metric that captures both premature mortality and the prevalence and severity of ill-health. The 1990 Global Burden of Disease study proposed disability-adjusted life years (DALYs) to measure disease burden. No comprehensive update of disease burden worldwide incorporating a systematic reassessment of disease and injury-specific epidemiology has been done since the 1990 study. We aimed to calculate disease burden worldwide and for 21 regions for 1990, 2005, and 2010 with methods to enable meaningful comparisons over time.We calculated DALYs as the sum of years of life lost (YLLs) and years lived with disability (YLDs). DALYs were calculated for 291 causes, 20 age groups, both sexes, and for 187 countries, and aggregated to regional and global estimates of disease burden for three points in time with strictly comparable definitions and methods. YLLs were calculated from age-sex-country-time-specific estimates of mortality by cause, with death by standardised lost life expectancy at each age. YLDs were calculated as prevalence of 1160 disabling sequelae, by age, sex, and cause, and weighted by new disability weights for each health state. Neither YLLs nor YLDs were age-weighted or discounted. Uncertainty around cause-specific DALYs was calculated incorporating uncertainty in levels of all-cause mortality, cause-specific mortality, prevalence, and disability weights.Global DALYs remained stable from 1990 (2·503 billion) to 2010 (2·490 billion). Crude DALYs per 1000 decreased by 23% (472 per 1000 to 361 per 1000). An important shift has occurred in DALY composition with the contribution of deaths and disability among children (younger than 5 years of age) declining from 41% of global DALYs in 1990 to 25% in 2010. YLLs typically account for about half of disease burden in more developed regions (high-income Asia Pacific, western Europe, high-income North America, and Australasia), rising to over 80% of DALYs in sub-Saharan Africa. In 1990, 47% of DALYs worldwide were from communicable, maternal, neonatal, and nutritional disorders, 43% from non-communicable diseases, and 10% from injuries. By 2010, this had shifted to 35%, 54%, and 11%, respectively. Ischaemic heart disease was the leading cause of DALYs worldwide in 2010 (up from fourth rank in 1990, increasing by 29%), followed by lower respiratory infections (top rank in 1990; 44% decline in DALYs), stroke (fifth in 1990; 19% increase), diarrhoeal diseases (second in 1990; 51% decrease), and HIV/AIDS (33rd in 1990; 351% increase). Major depressive disorder increased from 15th to 11th rank (37% increase) and road injury from 12th to 10th rank (34% increase). Substantial heterogeneity exists in rankings of leading causes of disease burden among regions.Global disease burden has continued to shift away from communicable to non-communicable diseases and from premature death to years lived with disability. In sub-Saharan Africa, however, many communicable, maternal, neonatal, and nutritional disorders remain the dominant causes of disease burden. The rising burden from mental and behavioural disorders, musculoskeletal disorders, and diabetes will impose new challenges on health systems. Regional heterogeneity highlights the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account. Because of improved definitions, methods, and data, these results for 1990 and 2010 supersede all previously published Global Burden of Disease results.Bill & Melinda Gates Foundation.

  View details for Web of Science ID 000312387000016

  View details for PubMedID 23245608

• Genome-Wide Association Study of Clinical Dimensions of Schizophrenia: Polygenic Effect on Disorganized Symptoms AMERICAN JOURNAL OF PSYCHIATRY Fanous, A. H., Zhou, B., Aggen, S. H., Bergen, S. E., Amdur, R. L., Duan, J., Sanders, A. R., Shi, J., Mowry, B. J., Olincy, A., Amin, F., Cloninger, C. R., Silverman, J. M., Buccola, N. G., Byerley, W. F., Black, D. W., Freedman, R., Dudbridge, F., Holmans, P. A., Ripke, S., Gejman, P. V., Kendler, K. S., Levinson, D. F. 2012; 169 (12): 1309-1317

  Abstract

  Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia.Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor.No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples.The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

  View details for DOI 10.1176/appi.ajp.2012.12020218

  View details for Web of Science ID 000312179500014

  View details for PubMedID 23212062

  View details for PubMedCentralID PMC3646712

• Additive genetic variation in risk to schizophrenia across African American and European American populations de Candia, T., Lee, H., Yang, J., Browning, B., Gejman, P., Levinson, D., Hewitt, J., Visscher, P., Wray, N., Keller, M. SPRINGER. 2012: 928

  View details for Web of Science ID 000309659800053

• Genome-Wide Association Study of Multiplex Schizophrenia Pedigrees AMERICAN JOURNAL OF PSYCHIATRY Levinson, D. F., Shi, J., Wang, K., Oh, S., Riley, B., Pulver, A. E., Wildenauer, D. B., Laurent, C., Mowry, B. J., Gejman, P. V., Owen, M. J., Kendler, K. S., Nestadt, G., Schwab, S. G., Mallet, J., Nertney, D., Sanders, A. R., Williams, N. M., Wormley, B., Lasseter, V. K., Albus, M., Godard-Bauche, S., Alexander, M., Duan, J., O'Donovan, M. C., Walsh, D., O'Neill, A., Papadimitriou, G. N., Dikeos, D., Maier, W., Lerer, B., Campion, D., Cohen, D., Jay, M., Fanous, A., Eichhammer, P., Silverman, J. M., Norton, N., Zhang, N., Hakonarson, H., Gao, C., Citri, A., Hansen, M., Ripke, S., Dudbridge, F., Holmans, P. A. 2012; 169 (9): 963-973

  Abstract

  The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs).The family sample included 2,461 individuals from 631 pedigrees (581 in the primary European-ancestry analyses). Association was tested for single SNPs and genetic pathways. Polygenic scores based on family study results were used to predict case-control status in the Schizophrenia Psychiatric GWAS Consortium (PGC) data set, and consistency of direction of effect with the family study was determined for top SNPs in the PGC GWAS analysis. Within-family segregation was examined for schizophrenia-associated rare CNVs.No genome-wide significant associations were observed for single SNPs or for pathways. PGC case and control subjects had significantly different genome-wide polygenic scores (computed by weighting their genotypes by log-odds ratios from the family study) (best p=10(-17), explaining 0.4% of the variance). Family study and PGC analyses had consistent directions for 37 of the 58 independent best PGC SNPs (p=0.024). The overall frequency of CNVs in regions with reported associations with schizophrenia (chromosomes 1q21.1, 15q13.3, 16p11.2, and 22q11.2 and the neurexin-1 gene [NRXN1]) was similar to previous case-control studies. NRXN1 deletions and 16p11.2 duplications (both of which were transmitted from parents) and 22q11.2 deletions (de novo in four cases) did not segregate with schizophrenia in families.Many common SNPs are likely to contribute to schizophrenia risk, with substantial overlap in genetic risk factors between multiply affected families and cases in large case-control studies. Our findings are consistent with a role for specific CNVs in disease pathogenesis, but the partial segregation of some CNVs with schizophrenia suggests that researchers should exercise caution in using them for predictive genetic testing until their effects in diverse populations have been fully studied.

  View details for DOI 10.1176/appl.ajp.2012.11091423

  View details for PubMedID 22885689

• Increased Genetic Vulnerability to Smoking at CHRNA5 in Early-Onset Smokers ARCHIVES OF GENERAL PSYCHIATRY Hartz, S. M., Short, S. E., Saccone, N. L., Culverhouse, R., Chen, L., Schwantes-An, T., Coon, H., Han, Y., Stephens, S. H., Sun, J., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Geller, F., Guobjartsson, D., Hansel, N. N., Jiang, C., Keskitalo-Vuokko, K., Liu, Z., Lyytikainen, L., Michel, M., Rawal, R., Hum, S., Rosenberger, A., Scheet, P., Shaffer, J. R., Teumer, A., Thompson, J. R., Vink, J. M., Vogelzangs, N., Wenzlaff, A. S., Wheeler, W., Xiao, X., Yang, B., Aggen, S. H., Balmforth, A. J., Baumeister, S. E., Beaty, T., Bennett, S., Bergen, A. W., Boyd, H. A., Broms, U., Campbell, H., Chatterjee, N., Chen, J., Cheng, Y., Cichon, S., Couper, D., Cucca, F., Dick, D. M., Foroud, T., Furberg, H., Giegling, I., Gu, F., Hall, A. S., Hallfors, J., Han, S., Hartmann, A. M., Hayward, C., Heikkila, K., Hewitt, J. K., Hottenga, J. J., Jensen, M. K., Jousilahti, P., Kaakinen, M., Kittner, S. J., Konte, B., Korhonen, T., Landi, M., Laatikainen, T., Leppert, M., Levy, S. M., Mathias, R. A., McNeil, D. W., Medland, S. E., Montgomery, G. W., Muley, T., Murray, T., Nauck, M., North, K., Pergadia, M., Polasek, O., Ramos, E. M., Ripatti, S., Risch, A., Ruczinski, I., Rudan, I., Salomaa, V., Schlessinger, D., Styrkarsdottir, U., Terracciano, A., Uda, M., Willemsen, G., Wu, X., Abecasis, G., Barnes, K., Bickeboeller, H., Boerwinkle, E., Boomsma, D. I., Caporaso, N., Duan, J., Edenberg, H. J., Francks, C., Gejman, P. V., Gelernter, J., Grabe, H. J., Hops, H., Jarvelin, M., Viikari, J., Kahonen, M., Kendler, K. S., Lehtimaki, T., Levinson, D. F., Marazita, M. L., Marchini, J., Melbye, M., Mitchell, B. D., Murray, J. C., Nothen, M. M., Penninx, B. W., Raitakari, O., Rietschel, M., Rujescu, D., Samani, N. J., Sanders, A. R., Schwartz, A. G., Shete, S., Shi, J., Spitz, M., Stefansson, K., Swan, G. E., Thorgeirsson, T., Volzke, H., Wei, Q., Wichmann, H., Amos, C. I., Breslau, N., Cannon, D. S., Ehringer, M., Grucza, R., Hatsukami, D., Heath, A., Johnson, E. O., Kaprio, J., Madden, P., Martin, N. G., Stevens, V. L., Stitzel, J. A., Weiss, R. B., Kraft, P., Bierut, L. J. 2012; 69 (8): 854-861

  Abstract

  Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968.To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking.Primary data.Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy.Uniform statistical analysis scripts were run locally. Starting with 94,050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33,348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum.Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR] = 1.45; 95% CI, 1.36-1.55; n = 13,843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21-1.33, n = 19,505) (P = .01).These results highlight an increased genetic vulnerability to smoking in early-onset smokers.

  View details for DOI 10.1001/archgenpsychiatry.2012.124

  View details for Web of Science ID 000307185000011

  View details for PubMedID 22868939

  View details for PubMedCentralID PMC3482121

• Smoking and Genetic Risk Variation Across Populations of European, Asian, and African American AncestryuA Meta-Analysis of Chromosome 15q25(vol 36, pg 525, 2010) GENETIC EPIDEMIOLOGY Chen, L., Saccone, N. L., Culverhouse, R. C., Bracci, P. M., Chen, C., Dueker, N., Han, Y., Huang, H., Jin, G., Kohno, T., Ma, J. Z., Przybeck, T. R., Sanders, A. R., Smith, J. A., Sung, Y. J., Wenzlaff, A. S., Wu, C., Yoon, D., Chen, Y., Cheng, Y., Cho, Y. S., David, S. P., Duan, J., Eaton, C. B., Furberg, H., Goate, A. M., Gu, D., Hansen, H. M., Hartz, S., Hu, Z., Kim, Y. J., Kittner, S. J., Levinson, D. F., Mosley, T. H., Payne, T. J., Rao, D. C., Rice, J. P., Rice, T. K., Schwantes-An, T., Shete, S. S., Shi, J., Spitz, M. R., Sun, Y. V., Tsai, F., Wang, J. C., Wrensch, M. R., Xian, H., Gejman, P. V., He, J., Hunt, S. C., Kardia, S. L., Li, M. D., Lin, D., Mitchell, B. D., Park, T., Schwartz, A. G., Shen, H., Wiencke, J. K., Wu, J., Yokota, J., Amos, C. I., Bierut, L. J. 2012; 36 (5): 525-526

  View details for DOI 10.1002/gepi.21654

  View details for Web of Science ID 000305125800012

• Segment-Wise Genome-Wide Association Analysis Identifies a Candidate Region Associated with Schizophrenia in Three Independent Samples PLOS ONE Gladwin, T. E., Derks, E. M., Rietschel, M., Mattheisen, M., Breuer, R., Schulze, T. G., Noethen, M. M., Levinson, D., Shi, J., Gejman, P. V., Cichon, S., Ophoff, R. A. 2012; 7 (6)

  Abstract

  Recent studies suggest that variation in complex disorders (e.g., schizophrenia) is explained by a large number of genetic variants with small effect size (Odds Ratio ≈ 1.05-1.1). The statistical power to detect these genetic variants in Genome Wide Association (GWA) studies with large numbers of cases and controls (v 15,000) is still low. As it will be difficult to further increase sample size, we decided to explore an alternative method for analyzing GWA data in a study of schizophrenia, dramatically reducing the number of statistical tests. The underlying hypothesis was that at least some of the genetic variants related to a common outcome are collocated in segments of chromosomes at a wider scale than single genes. Our approach was therefore to study the association between relatively large segments of DNA and disease status. An association test was performed for each SNP and the number of nominally significant tests in a segment was counted. We then performed a permutation-based binomial test to determine whether this region contained significantly more nominally significant SNPs than expected under the null hypothesis of no association, taking linkage into account. Genome Wide Association data of three independent schizophrenia case/control cohorts with European ancestry (Dutch, German, and US) using segments of DNA with variable length (2 to 32 Mbp) was analyzed. Using this approach we identified a region at chromosome 5q23.3-q31.3 (128-160 Mbp) that was significantly enriched with nominally associated SNPs in three independent case-control samples. We conclude that considering relatively wide segments of chromosomes may reveal reliable relationships between the genome and schizophrenia, suggesting novel methodological possibilities as well as raising theoretical questions.

  View details for DOI 10.1371/journal.pone.0038828

  View details for Web of Science ID 000305583300057

  View details for PubMedID 22723893

  View details for PubMedCentralID PMC3377732

• HIGH THROUGHPUT, HIGH FIDELITY HLA GENOTYPING WITH ULTRA DEEP SEQUENCING Joint 16th International HLA and Immunogenetics Workshop/26th European Federation for Immunogenetics Conference/23rd British-Society-of-Histocompatibility-and-Immunogenetics Conference Krishnakumar, S., Wang, C., Wilhelmy, J., Babrzadeh, F., Su, L., Levinson, D., Fernandez-Vina, M., Davis, R., Davis, M., Mindrinos, M. N. WILEY-BLACKWELL. 2012: 426–26

  View details for Web of Science ID 000303499800058

• High-throughput, high-fidelity HLA genotyping with deep sequencing PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Wang, C., Krishnakumar, S., Wilhelmy, J., Babrzadeh, F., Stepanyan, L., Su, L. F., Levinson, D., Fernandez-Vina, M. A., Davis, R. W., Davis, M. M., Mindrinos, M. 2012; 109 (22): 8676-8681

  Abstract

  Human leukocyte antigen (HLA) genes are the most polymorphic in the human genome. They play a pivotal role in the immune response and have been implicated in numerous human pathologies, especially autoimmunity and infectious diseases. Despite their importance, however, they are rarely characterized comprehensively because of the prohibitive cost of standard technologies and the technical challenges of accurately discriminating between these highly related genes and their many allelles. Here we demonstrate a high-resolution, and cost-effective methodology to type HLA genes by sequencing, which combines the advantage of long-range amplification, the power of high-throughput sequencing platforms, and a unique genotyping algorithm. We calibrated our method for HLA-A, -B, -C, and -DRB1 genes with both reference cell lines and clinical samples and identified several previously undescribed alleles with mismatches, insertions, and deletions. We have further demonstrated the utility of this method in a clinical setting by typing five clinical samples in an Illumina MiSeq instrument with a 5-d turnaround. Overall, this technology has the capacity to deliver low-cost, high-throughput, and accurate HLA typing by multiplexing thousands of samples in a single sequencing run, which will enable comprehensive disease-association studies with large cohorts. Furthermore, this approach can also be extended to include other polymorphic genes.

  View details for DOI 10.1073/pnas.1206614109

  View details for PubMedID 22589303

• Smoking and Genetic Risk Variation Across Populations of European, Asian, and African American Ancestry-A Meta-Analysis of Chromosome 15q25 GENETIC EPIDEMIOLOGY Chen, L., Saccone, N. L., Culverhouse, R. C., Bracci, P. M., Chen, C., Dueker, N., Han, Y., Huang, H., Jin, G., Kohno, T., Ma, J. Z., Przybeck, T. R., Sanders, A. R., Smith, J. A., Sung, Y. J., Wenzlaff, A. S., Wu, C., Yoon, D., Chen, Y., Cheng, Y., Cho, Y. S., David, S. P., Duan, J., Eaton, C. B., Furberg, H., Goate, A. M., Gu, D., Hansen, H. M., Hartz, S., Hu, Z., Kim, Y. J., Kittner, S. J., Levinson, D. F., Mosley, T. H., Payne, T. J., Rao, D. C., Rice, J. P., Rice, T. K., Schwantes-An, T., Shete, S. S., Shi, J., Spitz, M. R., Sun, Y. V., Tsai, F., Wang, J. C., Wrensch, M. R., Xian, H., Gejman, P. V., He, J., Hunt, S. C., Kardia, S. L., Li, M. D., Lin, D., Mitchell, B. D., Park, T., Schwartz, A. G., Shen, H., Wiencke, J. K., Wu, J., Yokota, J., Amos, C. I., Bierut, L. J. 2012; 36 (4): 340-351

  Abstract

  Recent meta-analyses of European ancestry subjects show strong evidence for association between smoking quantity and multiple genetic variants on chromosome 15q25. This meta-analysis extends the examination of association between distinct genes in the CHRNA5-CHRNA3-CHRNB4 region and smoking quantity to Asian and African American populations to confirm and refine specific reported associations. Association results for a dichotomized cigarettes smoked per day phenotype in 27 datasets (European ancestry (N = 14,786), Asian (N = 6,889), and African American (N = 10,912) for a total of 32,587 smokers) were meta-analyzed by population and results were compared across all three populations. We demonstrate association between smoking quantity and markers in the chromosome 15q25 region across all three populations, and narrow the region of association. Of the variants tested, only rs16969968 is associated with smoking (P < 0.01) in each of these three populations (odds ratio [OR] = 1.33, 95% CI = 1.25-1.42, P = 1.1 × 10(-17) in meta-analysis across all population samples). Additional variants displayed a consistent signal in both European ancestry and Asian datasets, but not in African Americans. The observed consistent association of rs16969968 with heavy smoking across multiple populations, combined with its known biological significance, suggests rs16969968 is most likely a functional variant that alters risk for heavy smoking. We interpret additional association results that differ across populations as providing evidence for additional functional variants, but we are unable to further localize the source of this association. Using the cross-population study paradigm provides valuable insights to narrow regions of interest and inform future biological experiments.

  View details for DOI 10.1002/gepi.21627

  View details for Web of Science ID 000303319900006

  View details for PubMedID 22539395

• A Rare Deletion At Distal 16p11.2 Is Implicated In Schizophrenia Guha, S., Rees, E., Darvasi, A., Ivanov, D., Ikeda, M., Bergen, S. E., Magnusson, P. K., Cormican, P., Cihon, S., Rosenfeld, J. A., Malhotra, A. K., Rujescu, D., Ruderfer, D., Purcell, S., Sklar, P., Iwata, N., Hultman, C. M., Sullivan, P., Sebat, J., McCarthy, S., Levinson, D., Owen, M. J., O'Donovan, M. C., Lencz, T., Kirov, G. ELSEVIER SCIENCE INC. 2012: 120S–121S

  View details for Web of Science ID 000302466000382

• Runs of Homozygosity Implicate Autozygosity as a Schizophrenia Risk Factor PLOS GENETICS Keller, M. C., Simonson, M. A., Ripke, S., Neale, B. M., Gejman, P. V., Howrigan, D. P., Lee, S. H., Lencz, T., Levinson, D. F., Sullivan, P. F. 2012; 8 (4): 425-435

  Abstract

  Autozygosity occurs when two chromosomal segments that are identical from a common ancestor are inherited from each parent. This occurs at high rates in the offspring of mates who are closely related (inbreeding), but also occurs at lower levels among the offspring of distantly related mates. Here, we use runs of homozygosity in genome-wide SNP data to estimate the proportion of the autosome that exists in autozygous tracts in 9,388 cases with schizophrenia and 12,456 controls. We estimate that the odds of schizophrenia increase by ~17% for every 1% increase in genome-wide autozygosity. This association is not due to one or a few regions, but results from many autozygous segments spread throughout the genome, and is consistent with a role for multiple recessive or partially recessive alleles in the etiology of schizophrenia. Such a bias towards recessivity suggests that alleles that increase the risk of schizophrenia have been selected against over evolutionary time.

  View details for DOI 10.1371/journal.pgen.1002656

  View details for Web of Science ID 000303441800032

  View details for PubMedID 22511889

  View details for PubMedCentralID PMC3325203

• Schizophrenia susceptibility alleles are enriched for alleles that affect gene expression in adult human brain MOLECULAR PSYCHIATRY Richards, A. L., Jones, L., Moskvina, V., Kirov, G., GEJMAN, P. V., Levinson, D. F., Sanders, A. R., Purcell, S., Visscher, P. M., Craddock, N., Owen, M. J., Holmans, P., O'Donovan, M. C. 2012; 17 (2): 193-201

  Abstract

  It is widely thought that alleles that influence susceptibility to common diseases, including schizophrenia, will frequently do so through effects on gene expression. As only a small proportion of the genetic variance for schizophrenia has been attributed to specific loci, this remains an unproven hypothesis. The International Schizophrenia Consortium (ISC) recently reported a substantial polygenic contribution to that disorder, and that schizophrenia risk alleles are enriched among single-nucleotide polymorphisms (SNPs) selected for marginal evidence for association (P<0.5) from genome-wide association studies (GWAS). It follows that if schizophrenia susceptibility alleles are enriched for those that affect gene expression, those marginally associated SNPs, which are also expression quantitative trait loci (eQTLs), should carry more true association signals compared with SNPs that are not marginally associated. To test this, we identified marginally associated (P<0.5) SNPs from two of the largest available schizophrenia GWAS data sets. We assigned eQTL status to those SNPs based upon an eQTL data set derived from adult human brain. Using the polygenic score method of analysis reported by the ISC, we observed and replicated the observation that higher probability cis-eQTLs predicted schizophrenia better than those with a lower probability for being a cis-eQTL. Our data support the hypothesis that alleles conferring risk of schizophrenia are enriched among those that affect gene expression. Moreover, our data show that notwithstanding the likely developmental origin of schizophrenia, studies of adult brain tissue can, in principle, allow relevant susceptibility eQTLs to be identified.

  View details for DOI 10.1038/mp.2011.11

  View details for Web of Science ID 000299802400012

  View details for PubMedID 21339752

• ACSL6 Is Associated with the Number of Cigarettes Smoked and Its Expression Is Altered by Chronic Nicotine Exposure PLOS ONE Chen, J., Brunzell, D. H., Jackson, K., van der Vaart, A., Ma, J. Z., Payne, T. J., Sherva, R., Farrer, L. A., Gejman, P., Levinson, D. F., Holmans, P., Aggen, S. H., Damaj, I., Kuo, P., Webb, B. T., Anton, R., Kranzler, H. R., Gelernter, J., Li, M. D., Kendler, K. S., Chen, X. 2011; 6 (12)

  Abstract

  Individuals with schizophrenia tend to be heavy smokers and are at high risk for tobacco dependence. However, the nature of the comorbidity is not entirely clear. We previously reported evidence for association of schizophrenia with SNPs and SNP haplotypes in a region of chromosome 5q containing the SPEC2, PDZ-GEF2 and ACSL6 genes. In this current study, analysis of the control subjects of the Molecular Genetics of Schizophrenia (MGS) sample showed similar pattern of association with number of cigarettes smoked per day (numCIG) for the same region. To further test if this locus is associated with tobacco smoking as measured by numCIG and FTND, we conducted replication and meta-analysis in 12 independent samples (n>16,000) for two markers in ACSL6 reported in our previous schizophrenia study. In the meta-analysis of the replication samples, we found that rs667437 and rs477084 were significantly associated with numCIG (p = 0.00038 and 0.00136 respectively) but not with FTND scores. We then used in vitro and in vivo techniques to test if nicotine exposure influences the expression of ACSL6 in brain. Primary cortical culture studies showed that chronic (5-day) exposure to nicotine stimulated ACSL6 mRNA expression. Fourteen days of nicotine administration via osmotic mini pump also increased ACSL6 protein levels in the prefrontal cortex and hippocampus of mice. These increases were suppressed by injection of the nicotinic receptor antagonist mecamylamine, suggesting that elevated expression of ACSL6 requires nicotinic receptor activation. These findings suggest that variations in the ACSL6 gene may contribute to the quantity of cigarettes smoked. The independent associations of this locus with schizophrenia and with numCIG in non-schizophrenic subjects suggest that this locus may be a common liability to both conditions.

  View details for DOI 10.1371/journal.pone.0028790

  View details for Web of Science ID 000298666200011

  View details for PubMedID 22205969

  View details for PubMedCentralID PMC3243669

• GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia MOLECULAR PSYCHIATRY Chen, X., Lee, G., Maher, B. S., Fanous, A. H., Chen, J., Zhao, Z., Guo, A., van den Oord, E., Sullivan, P. F., Shi, J., Levinson, D. F., GEJMAN, P. V., Sanders, A., Duan, J., Owen, M. J., Craddock, N. J., O'Donovan, M. C., Blackman, J., Lewis, D., Kirov, G. K., Qin, W., Schwab, S., Wildenauer, D., Chowdari, K., Nimgaonkar, V., Straub, R. E., Weinberger, D. R., O'Neill, F. A., Walsh, D., Bronstein, M., Darvasi, A., Lencz, T., Malhotra, A. K., Rujescu, D., Giegling, I., Werge, T., Hansen, T., Ingason, A., Noeethen, M. M., Rietschel, M., Cichon, S., Djurovic, S., Andreassen, O. A., Cantor, R. M., Ophoff, R., Corvin, A., Morris, D. W., Gill, M., Pato, C. N., Pato, M. T., Macedo, A., Gurling, H. M., McQuillin, A., Pimm, J., Hultman, C., Lichtenstein, P., Sklar, P., Purcell, S. M., Scolnick, E., St Clair, D., Blackwood, D. H., Kendler, K. S. 2011; 16 (11): 1117-1129

  Abstract

  We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ≤0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611-rs10043986, r(2)=0.008; rs10043986-rs4704591, r(2)=0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case-control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR)=1.11, 95% confidence interval (CI)=1.04-1.18, P=8.2 × 10(-4) and rs4704591, OR=1.07, 95% CI=1.03-1.11, P=3.0 × 10(-4)). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR=1.11, 95% CI=1.03-1.17, P=0.0026 and rs4704591, OR=1.07, 95% CI=1.02-1.11, P=0.0015). Furthermore, haplotype conditioned analyses indicated that the association signals observed at these two markers are independent. On the basis of these results, we concluded that CMYA5 is associated with schizophrenia and further investigation of the gene is warranted.

  View details for DOI 10.1038/mp.2010.96

  View details for Web of Science ID 000296429100011

  View details for PubMedID 20838396

  View details for PubMedCentralID PMC3443634

• Genome-wide association study identifies five new schizophrenia loci NATURE GENETICS Ripke, S., Sanders, A. R., Kendler, K. S., Levinson, D. F., Sklar, P., Holmans, P. A., Lin, D., Duan, J., Ophoff, R. A., Andreassen, O. A., Scolnick, E., Cichon, S., Clair, D. S., Corvin, A., Gurling, H., Werge, T., Rujescu, D., Blackwood, D. H., Pato, C. N., Malhotra, A. K., Purcell, S., Dudbridge, F., Neale, B. M., Rossin, L., Visscher, P. M., Posthuma, D., Ruderfer, D. M., Fanous, A., Stefansson, H., Steinberg, S., Mowry, B. J., Golimbet, V., De Hert, M., Jonsson, E. G., Bitter, I., Pietilainen, O. P., Collier, D. A., Tosato, S., Agartz, I., Albus, M., Alexander, M., Amdur, R. L., Amin, F., Bass, N., Bergen, S. E., Black, D. W., Borglum, A. D., Brown, M. A., Bruggeman, R., Buccola, N. G., Byerley, W. F., Cahn, W., Cantor, R. M., Carr, V. J., Catts, S. V., Choudhury, K., Cloninger, C. R., Cormican, P., Craddock, N., Danoy, P. A., Datta, S., de Haan, L., Demontis, D., Dikeos, D., Djurovic, S., Donnelly, P., Donohoe, G., Duong, L., Dwyer, S., Fink-Jensen, A., Freedman, R., Freimer, N. B., Friedl, M., Georgieva, L., Giegling, I., Gill, M., Glenthoj, B., Godard, S., Hamshere, M., Hansen, M., Hansen, T., Hartmann, A. M., Henskens, F. A., Hougaard, D. M., Hultman, C. M., Ingason, A., Jablensky, A. V., Jakobsen, K. D., Jay, M., Juergens, G., Kahn, R., Keller, M. C., Kenis, G., Kenny, E., Kim, Y., Kirov, G. K., Konnerth, H., Konte, B., Krabbendam, L., Krasucki, R., Lasseter, V. K., Laurent, C., Lawrence, J., Lencz, T., Lerer, F. B., Liang, K., Lichtenstein, P., Lieberman, J. A., Linszen, D. H., Lonnqvist, J., Loughland, C. M., MacLean, A. W., Maher, B. S., Maier, W., Mallet, J., Malloy, P., Mattheisen, M., Mattingsdal, M., McGhee, K. A., McGrath, J. J., McIntosh, A., McLean, D. E., McQuillin, A., Melle, I., Michie, P. T., Milanova, V., Morris, D. W., Mors, O., Mortensen, P. B., Moskvina, V., Muglia, P., Myin-Germeys, I., Nertney, D. A., Nestadt, G., Nielsen, J., Nikolov, I., Nordentoft, M., Norton, N., Noethen, M. M., O'Dushlaine, C. T., Olincy, A., Olsen, L., O'Neill, F. A., Orntoft, T. F., Owen, M. J., Pantelis, C., Papadimitriou, G., Pato, M. T., Peltonen, L., Petursson, H., Pickard, B., Pimm, J., Pulver, A. E., Puri, V., Quested, D., Quinn, E. M., Rasmussen, H. B., Rethelyi, J. M., Ribble, R., Rietschel, M., Riley, B. P., Ruggeri, M., Schall, U., Schulze, T. G., Schwab, S. G., Scott, R. J., Shi, J., Sigurdsson, E., Silverman, J. M., Spencer, C. C., Stefansson, K., Strange, A., Strengman, E., Stroup, T. S., Suvisaari, J., Terenius, L., Thirumalai, S., Thygesen, J. H., Timm, S., Toncheva, D., van den Oord, E., van Os, J., van Winkel, R., Veldink, J., Walsh, D., Wang, A. G., Wiersma, D., Wildenauer, D. B., Williams, H. J., Williams, N. M., Wormley, B., Zammit, S., Sullivan, P. F., O'Donovan, M. C., Daly, M. J., Gejman, P. V. 2011; 43 (10): 969-U77

  Abstract

  We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10(-9)), ANK3 (rs10994359, P = 2.5 × 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10(-9)).

  View details for DOI 10.1038/ng.940

  View details for Web of Science ID 000295316200011

  View details for PubMedCentralID PMC3303194

• Genomewide Association Analysis of Symptoms of Alcohol Dependence in the Molecular Genetics of Schizophrenia (MGS2) Control Sample ALCOHOLISM-CLINICAL AND EXPERIMENTAL RESEARCH Kendler, K. S., Kalsi, G., Holmans, P. A., Sanders, A. R., Aggen, S. H., Dick, D. M., Aliev, F., Shi, J., Levinson, D. F., Gejman, P. V. 2011; 35 (5): 963-975

  Abstract

  While genetic influences on alcohol dependence (AD) are substantial, progress in the identification of individual genetic variants that impact on risk has been difficult.We performed a genome-wide association study on 3,169 alcohol consuming subjects from the population-based Molecular Genetics of Schizophrenia (MGS2) control sample. Subjects were asked 7 questions about symptoms of AD which were analyzed by confirmatory factor analysis. Genotyping was performed using the Affymetrix 6.0 array. Three sets of analyses were conducted separately for European American (EA, n = 2,357) and African-American (AA, n = 812) subjects: individual single nucleotide polymorphisms (SNPs), candidate genes and enriched pathways using gene ontology (GO) categories.The symptoms of AD formed a highly coherent single factor. No SNP approached genome-wide significance. In the EA sample, the most significant intragenic SNP was in KCNMA1, the human homolog of the slo-1 gene in C. Elegans. Genes with clusters of significant SNPs included AKAP9, phosphatidylinositol glycan anchor biosynthesis, class G (PIGG), and KCNMA1. In the AA sample, the most significant intragenic SNP was CEACAM6 and genes showing empirically significant SNPs included KCNQ5, SLC35B4, and MGLL. In the candidate gene based analyses, the most significant findings were with ADH1C, nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NFKB1) and ankyrin repeat and kinase domain containing 1 (ANKK1) in the EA sample, and ADH5, POMC, and CHRM2 in the AA sample. The ALIGATOR program identified a significant excess of associated SNPs within and near genes in a substantial number of GO categories over a range of statistical stringencies in both the EA and AA sample.While we cannot be highly confident about any single result from these analyses, a number of findings were suggestive and worthy of follow-up. Although quite large samples will be needed to obtain requisite power, the study of AD symptoms in general population samples is a viable complement to case-control studies in identifying genetic risk variants for AD.

  View details for DOI 10.1111/j.1530-0277.2010.01427.x

  View details for Web of Science ID 000289896200032

  View details for PubMedID 21314694

  View details for PubMedCentralID PMC3083473

• Copy Number Variants in Schizophrenia: Confirmation of Five Previous Findings and New Evidence for 3q29 Microdeletions and VIPR2 Duplications 60th Annual Meeting of the American-Society-of-Human-Genetics Levinson, D. F., Duan, J., Oh, S., Wang, K., Sanders, A. R., Shi, J., Zhang, N., Mowry, B. J., Olincy, A., Amin, F., Cloninger, C. R., Silverman, J. M., Buccola, N. G., Byerley, W. F., Black, D. W., Kendler, K. S., Freedman, R., Dudbridge, F., Pe'er, I., Hakonarson, H., Bergen, S. E., Fanous, A. H., Holmans, P. A., Gejman, P. V. AMER PSYCHIATRIC PUBLISHING, INC. 2011: 302–16

  Abstract

  To evaluate previously reported associations of copy number variants (CNVs) with schizophrenia and to identify additional associations, the authors analyzed CNVs in the Molecular Genetics of Schizophrenia study (MGS) and additional available data.After quality control, MGS data for 3,945 subjects with schizophrenia or schizoaffective disorder and 3,611 screened comparison subjects were available for analysis of rare CNVs (<1% frequency). CNV detection thresholds were chosen that maximized concordance in 151 duplicate assays. Pointwise and genewise analyses were carried out, as well as analyses of previously reported regions. Selected regions were visually inspected and confirmed with quantitative polymerase chain reaction.In analyses of MGS data combined with other available data sets, odds ratios of 7.5 or greater were observed for previously reported deletions in chromosomes 1q21.1, 15q13.3, and 22q11.21, duplications in 16p11.2, and exon-disrupting deletions in NRXN1. The most consistently supported candidate associations across data sets included a 1.6-Mb deletion in chromosome 3q29 (21 genes, TFRC to BDH1) that was previously described in a mild-moderate mental retardation syndrome, exonic duplications in the gene for vasoactive intestinal peptide receptor 2 (VIPR2), and exonic duplications in C16orf72. The case subjects had a modestly higher genome-wide number of gene-containing deletions (>100 kb and >1 Mb) but not duplications.The data strongly confirm the association of schizophrenia with 1q21.1, 15q13.3, and 22q11.21 deletions, 16p11.2 duplications, and exonic NRXN1 deletions. These CNVs, as well as 3q29 deletions, are also associated with mental retardation, autism spectrum disorders, and epilepsy. Additional candidate genes and regions, including VIPR2, were identified. Study of the mechanisms underlying these associations should shed light on the pathophysiology of schizophrenia.

  View details for DOI 10.1176/appi.ajp.2010.10060876

  View details for PubMedID 21285140

• Genetic risk sum score comprised of common polygenic variation is associated with body mass index HUMAN GENETICS Peterson, R. E., Maes, H. H., Holmans, P., Sanders, A. R., Levinson, D. F., Shi, J., Kendler, K. S., Gejman, P. V., Webb, B. T. 2011; 129 (2): 221-230

  Abstract

  Genome-wide association studies (GWAS) of body mass index (BMI) using large samples have yielded approximately a dozen robustly associated variants and implicated additional loci. Individually these variants have small effects and in aggregate explain a small proportion of the variance. As a result, replication attempts have limited power to achieve genome-wide significance, even with several thousand subjects. Since there is strong prior evidence for genetic influence on BMI for specific variants, alternative approaches to replication can be applied. Instead of testing individual loci sequentially, a genetic risk sum score (GRSS) summarizing the total number of risk alleles can be tested. In the current study, GRSS comprising 56 top variants catalogued from two large meta-analyses was tested for association with BMI in the Molecular Genetics of Schizophrenia controls (2,653 European-Americans, 973 African-Americans). After accounting for covariates known to influence BMI (ancestry, sex, age), GRSS was highly associated with BMI (p value = 3.19 E-06) although explained a limited amount of the variance (0.66%). However, area under receiver operator criteria curve (AUC) estimates indicated that the GRSS and covariates significantly predicted overweight and obesity classification with maximum discriminative ability for predicting class III obesity (AUC = 0.697). The relative contributions of the individual loci to GRSS were examined post hoc and the results were not due to a few highly significant variants, but rather the result of numerous variants of small effect. This study provides evidence of the utility of a GRSS as an alternative approach to replication of common polygenic variation in complex traits.

  View details for DOI 10.1007/s00439-010-0917-1

  View details for Web of Science ID 000286194000010

  View details for PubMedID 21104096

  View details for PubMedCentralID PMC3403709

• Genome-wide association study of recurrent early-onset major depressive disorder MOLECULAR PSYCHIATRY Shi, J., Potash, J. B., Knowles, J. A., Weissman, M. M., Coryell, W., Scheftner, W. A., Lawson, W. B., DePaulo, J. R., GEJMAN, P. V., Sanders, A. R., Johnson, J. K., Adams, P., Chaudhury, S., JANCIC, D., Evgrafov, O., Zvinyatskovskiy, A., Ertman, N., Gladis, M., Neimanas, K., Goodell, M., Hale, N., NEY, N., Verma, R., Mirel, D., Holmans, P., Levinson, D. F. 2011; 16 (2): 193-201

  Abstract

  A genome-wide association study was carried out in 1020 case subjects with recurrent early-onset major depressive disorder (MDD) (onset before age 31) and 1636 control subjects screened to exclude lifetime MDD. Subjects were genotyped with the Affymetrix 6.0 platform. After extensive quality control procedures, 671 424 autosomal single nucleotide polymorphisms (SNPs) and 25 068 X chromosome SNPs with minor allele frequency greater than 1% were available for analysis. An additional 1 892 186 HapMap II SNPs were analyzed based on imputed genotypic data. Single-SNP logistic regression trend tests were computed, with correction for ancestry-informative principal component scores. No genome-wide significant evidence for association was observed, assuming that nominal P<5 × 10(-8) approximates a 5% genome-wide significance threshold. The strongest evidence for association was observed on chromosome 18q22.1 (rs17077540, P=1.83 × 10(-7)) in a region that has produced some evidence for linkage to bipolar-I or -II disorder in several studies, within an mRNA detected in human brain tissue (BC053410) and approximately 75 kb upstream of DSEL. Comparing these results with those of a meta-analysis of three MDD GWAS data sets reported in a companion article, we note that among the strongest signals observed in the GenRED sample, the meta-analysis provided the greatest support (although not at a genome-wide significant level) for association of MDD to SNPs within SP4, a brain-specific transcription factor. Larger samples will be required to confirm the hypothesis of association between MDD (and particularly the recurrent early-onset subtype) and common SNPs.

  View details for DOI 10.1038/mp.2009.124

  View details for Web of Science ID 000286581400009

  View details for PubMedID 20125088

• Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies MOLECULAR PSYCHIATRY Shyn, S. I., Shi, J., Kraft, J. B., Potash, J. B., Knowles, J. A., Weissman, M. M., Garriock, H. A., Yokoyama, J. S., McGrath, P. J., Peters, E. J., Scheftner, W. A., Coryell, W., Lawson, W. B., JANCIC, D., GEJMAN, P. V., Sanders, A. R., Holmans, P., Slager, S. L., Levinson, D. F., Hamilton, S. P. 2011; 16 (2): 202-215

  Abstract

  We report a genome-wide association study (GWAS) of major depressive disorder (MDD) in 1221 cases from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study and 1636 screened controls. No genome-wide evidence for association was detected. We also carried out a meta-analysis of three European-ancestry MDD GWAS data sets: STAR*D, Genetics of Recurrent Early-onset Depression and the publicly available Genetic Association Information Network-MDD data set. These data sets, totaling 3957 cases and 3428 controls, were genotyped using four different platforms (Affymetrix 6.0, 5.0 and 500 K, and Perlegen). For each of 2.4 million HapMap II single-nucleotide polymorphisms (SNPs), using genotyped data where available and imputed data otherwise, single-SNP association tests were carried out in each sample with correction for ancestry-informative principal components. The strongest evidence for association in the meta-analysis was observed for intronic SNPs in ATP6V1B2 (P=6.78 x 10⁻⁷), SP4 (P=7.68 x 10⁻⁷) and GRM7 (P=1.11 x 10⁻⁶). Additional exploratory analyses were carried out for a narrower phenotype (recurrent MDD with onset before age 31, N=2191 cases), and separately for males and females. Several of the best findings were supported primarily by evidence from narrow cases or from either males or females. On the basis of previous biological evidence, we consider GRM7 a strong MDD candidate gene. Larger samples will be required to determine whether any common SNPs are significantly associated with MDD.

  View details for DOI 10.1038/mp.2009.125

  View details for Web of Science ID 000286581400010

  View details for PubMedID 20038947

  View details for PubMedCentralID PMC2888856

• Common variants in P2RY11 are associated with narcolepsy NATURE GENETICS Kornum, B. R., Kawashima, M., Faraco, J., Lin, L., Rico, T. J., Hesselson, S., Axtell, R. C., Kuipers, H., Weiner, K., Hamacher, A., Kassack, M. U., Han, F., Knudsen, S., Li, J., Dong, X., Winkelmann, J., Plazzi, G., Nevsimalova, S., Hong, S., Honda, Y., Honda, M., Hogl, B., Ton, T. G., Montplaisir, J., Bourgin, P., Kemlink, D., Huang, Y., Warby, S., Einen, M., Eshragh, J. L., Miyagawa, T., Desautels, A., Ruppert, E., Hesla, P. E., Poli, F., Pizza, F., Frauscher, B., Jeong, J., Lee, S., Strohl, K. P., Longstreth, W. T., Kvale, M., Dobrovolna, M., Ohayon, M. M., Nepom, G. T., Wichmann, H., Rouleau, G. A., Gieger, C., Levinson, D. F., Gejman, P. V., Meitinger, T., Peppard, P., Young, T., Jennum, P., Steinman, L., Tokunaga, K., Kwok, P., Risch, N., Hallmayer, J., Mignot, E. 2011; 43 (1): 66-U90

  Abstract

  Growing evidence supports the hypothesis that narcolepsy with cataplexy is an autoimmune disease. We here report genome-wide association analyses for narcolepsy with replication and fine mapping across three ethnic groups (3,406 individuals of European ancestry, 2,414 Asians and 302 African Americans). We identify a SNP in the 3' untranslated region of P2RY11, the purinergic receptor subtype P2Y₁₁ gene, which is associated with narcolepsy (rs2305795, combined P = 6.1 × 10⁻¹⁰, odds ratio = 1.28, 95% CI 1.19-1.39, n = 5689). The disease-associated allele is correlated with reduced expression of P2RY11 in CD8(+) T lymphocytes (339% reduced, P = 0.003) and natural killer (NK) cells (P = 0.031), but not in other peripheral blood mononuclear cell types. The low expression variant is also associated with reduced P2RY11-mediated resistance to ATP-induced cell death in T lymphocytes (P = 0.0007) and natural killer cells (P = 0.001). These results identify P2RY11 as an important regulator of immune-cell survival, with possible implications in narcolepsy and other autoimmune diseases.

  View details for DOI 10.1038/ng.734

  View details for PubMedID 21170044

• Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index NATURE GENETICS Speliotes, E. K., Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., Allen, H. L., Lindgren, C. M., Luan, J., Maegi, R., Randall, J. C., Vedantam, S., Winkler, T. W., Qi, L., Workalemahu, T., Heid, I. M., Steinthorsdottir, V., Stringham, H. M., Weedon, M. N., Wheeler, E., Wood, A. R., Ferreira, T., Weyant, R. J., Segre, A. V., Estrada, K., Liang, L., Nemesh, J., Park, J., Gustafsson, S., Kilpelaenen, T. O., Yang, J., Bouatia-Naji, N., Esko, T., Feitosa, M. F., Kutalik, Z., Mangino, M., Raychaudhuri, S., Scherag, A., Smith, A. V., Welch, R., Zhao, J. H., Aben, K. K., Absher, D. M., Amin, N., Dixon, A. L., Fisher, E., Glazer, N. L., Goddard, M. E., Heard-Costa, N. L., Hoesel, V., Hottenga, J., Johansson, A., Johnson, T., Ketkar, S., Lamina, C., Li, S., Moffatt, M. F., Myers, R. H., Narisu, N., Perry, J. R., Peters, M. J., Preuss, M., Ripatti, S., Rivadeneira, F., Sandholt, C., Scott, L. J., Timpson, N. J., Tyrer, J. P., van Wingerden, S., Watanabe, R. M., White, C. C., Wiklund, F., Barlassina, C., Chasman, D. I., Cooper, M. N., Jansson, J., Lawrence, R. W., Pellikka, N., Prokopenko, I., Shi, J., Thiering, E., Alavere, H., Alibrandi, M. T., Almgren, P., Arnold, A. M., Aspelund, T., Atwood, L. D., Balkau, B., Balmforth, A. J., Bennett, A. J., Ben-Shlomo, Y., Bergman, R. N., Bergmann, S., Biebermann, H., Blakemore, A. I., Boes, T., Bonnycastle, L. L., Bornstein, S. R., Brown, M. J., Buchanan, T. A., Busonero, F., Campbell, H., Cappuccio, F. P., Cavalcanti-Proenca, C., Chen, Y. I., Chen, C., Chines, P. S., Clarke, R., Coin, L., Connell, J., Day, I. N., den Heijer, M., Duan, J., Ebrahim, S., Elliott, P., Elosua, R., Eiriksdottir, G., Erdos, M. R., Eriksson, J. G., Facheris, M. F., Felix, S. B., Fischer-Posovszky, P., Folsom, A. R., Friedrich, N., Freimer, N. B., Fu, M., Gaget, S., Gejman, P. V., Geus, E. J., Gieger, C., Gjesing, A. P., Goel, A., Goyette, P., Grallert, H., Graessler, J., Greenawalt, D. M., Groves, C. J., Gudnason, V., Guiducci, C., Hartikainen, A., Hassanali, N., Hall, A. S., Havulinna, A. S., Hayward, C., Heath, A. C., Hengstenberg, C., Hicks, A. A., Hinney, A., Hofman, A., Homuth, G., Hui, J., Igl, W., Iribarren, C., Isomaa, B., Jacobs, K. B., Jarick, I., Jewell, E., John, U., Jorgensen, T., Jousilahti, P., Jula, A., Kaakinen, M., Kajantie, E., Kaplan, L. M., Kathiresan, S., Kettunen, J., Kinnunen, L., Knowles, J. W., Kolcic, I., Koenig, I. R., Koskinen, S., Kovacs, P., Kuusisto, J., Kraft, P., Kvaloy, K., Laitinen, J., Lantieri, O., Lanzani, C., Launer, L. J., Lecoeur, C., Lehtimaeki, T., Lettre, G., Liu, J., Lokki, M., Lorentzon, M., Luben, R. N., Ludwig, B., Manunta, P., Marek, D., Marre, M., Martin, N. G., McArdle, W. L., McCarthy, A., McKnight, B., Meitinger, T., Melander, O., Meyre, D., Midthjell, K., Montgomery, G. W., Morken, M. A., Morris, A. P., Mulic, R., Ngwa, J. S., Nelis, M., Neville, M. J., Nyholt, D. R., O'Donnell, C. J., O'Rahilly, S., Ong, K. K., Oostra, B., Pare, G., Parker, A. N., Perola, M., Pichler, I., Pietilaeinen, K. H., Platou, C. G., Polasek, O., Pouta, A., Rafelt, S., Raitakari, O., Rayner, N. W., Ridderstrale, M., Rief, W., Ruokonen, A., Robertson, N. R., Rzehak, P., Salomaa, V., Sanders, A. R., Sandhu, M. S., Sanna, S., Saramies, J., Savolainen, M. J., Scherag, S., Schipf, S., Schreiber, S., Schunkert, H., Silander, K., Sinisalo, J., Siscovick, D. S., Smit, J. H., Soranzo, N., Sovio, U., Stephens, J., Surakka, I., Swift, A. J., Tammesoo, M., Tardif, J., Teder-Laving, M., Teslovich, T. M., Thompson, J. R., Thomson, B., Toenjes, A., Tuomi, T., van Meurs, J. B., van Ommen, G., Vatin, V., Viikari, J., Visvikis-Siest, S., Vitart, V., Vogel, C. I., Voight, B. F., Waite, L. L., Wallaschofski, H., Walters, G. B., Widen, E., Wiegand, S., Wild, S. H., Willemsen, G., Witte, D. R., Witteman, J. C., Xu, J., Zhang, Q., Zgaga, L., Ziegler, A., Zitting, P., Beilby, J. P., Farooqi, I. S., Hebebrand, J., Huikuri, H. V., James, A. L., Kaehoenen, M., Levinson, D. F., Macciardi, F., Nieminen, M. S., Ohlsson, C., Palmer, L. J., Ridker, P. M., Stumvoll, M., Beckmann, J. S., Boeing, H., Boerwinkle, E., Boomsma, D. I., Caulfield, M. J., Chanock, S. J., Collins, F. S., Cupples, L. A., Smith, G. D., Erdmann, J., Froguel, P., Greonberg, H., Gyllensten, U., Hall, P., Hansen, T., Harris, T. B., Hattersley, A. T., Hayes, R. B., Heinrich, J., Hu, F. B., Hveem, K., Illig, T., Jarvelin, M., Kaprio, J., Karpe, F., Khaw, K., Kiemeney, L. A., Krude, H., Laakso, M., Lawlor, D. A., Metspalu, A., Munroe, P. B., Ouwehand, W. H., Pedersen, O., Penninx, B. W., Peters, A., Pramstaller, P. P., Quertermous, T., Reinehr, T., Rissanen, A., Rudan, I., Samani, N. J., Schwarz, P. E., Shuldiner, A. R., Spector, T. D., Tuomilehto, J., Uda, M., Uitterlinden, A., Valle, T. T., Wabitsch, M., Waeber, G., Wareham, N. J., Watkins, H., Wilson, J. F., Wright, A. F., Zillikens, M. C., Chatterjee, N., McCarroll, S. A., Purcell, S., Schadt, E. E., Visscher, P. M., Assimes, T. L., Borecki, I. B., Deloukas, P., Fox, C. S., Groop, L. C., Haritunians, T., Hunter, D. J., Kaplan, R. C., Mohlke, K. L., O'Connell, J. R., Peltonen, L., Schlessinger, D., Strachan, D. P., van Duijn, C. M., Wichmann, H., Frayling, T. M., Thorsteinsdottir, U., Abecasis, G. R., Barroso, I., Boehnke, M., Stefansson, K., North, K. E., McCarthy, M. I., Hirschhorn, J. N., Ingelsson, E., Loos, R. J. 2010; 42 (11): 937-U53

  Abstract

  Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

  View details for DOI 10.1038/ng.686

  View details for Web of Science ID 000283540500010

  View details for PubMedID 20935630

• Mood Disorder Susceptibility Gene CACNA1C Modifies Mood-Related Behaviors in Mice and Interacts with Sex to Influence Behavior in Mice and Diagnosis in Humans BIOLOGICAL PSYCHIATRY Dao, D. T., Mahon, P. B., Cai, X., Kovacsics, C. E., Blackwell, R. A., Arad, M., Shi, J., Zandi, P. P., O'Donnell, P., Knowles, J. A., Weissman, M. M., Coryell, W., Scheftner, W. A., Lawson, W. B., Levinson, D. F., Thompson, S. M., Potash, J. B., Gould, T. D. 2010; 68 (9): 801-810

  Abstract

  Recent genome-wide association studies have associated polymorphisms in the gene CACNA1C, which codes for Ca(v)1.2, with a bipolar disorder and depression diagnosis.The behaviors of wild-type and Cacna1c heterozygous mice of both sexes were evaluated in a number of tests. Based upon sex differences in our mouse data, we assessed a gene × sex interaction for diagnosis of mood disorders in human subjects. Data from the National Institute of Mental Health Genetics Initiative Bipolar Disorder Consortium and the Genetics of Recurrent Early-Onset Major Depression Consortium were examined using a combined dataset that included 2021 mood disorder cases (1223 female cases) and 1840 control subjects (837 female subjects).In both male and female mice, Cacna1c haploinsufficiency was associated with lower exploratory behavior, decreased response to amphetamine, and antidepressant-like behavior in the forced swim and tail suspension tests. Female, but not male, heterozygous mice displayed decreased risk-taking behavior or increased anxiety in multiple tests, greater attenuation of amphetamine-induced hyperlocomotion, decreased development of learned helplessness, and a decreased acoustic startle response, indicating a sex-specific role of Cacna1c. In humans, sex-specific genetic association was seen for two intronic single nucleotide polymorphisms, rs2370419 and rs2470411, in CACNA1C, with effects in female subjects (odds ratio = 1.64, 1.32) but not in male subjects (odds ratio = .82, .86). The interactions by sex were significant after correction for testing 190 single nucleotide polymorphisms (p = 1.4 × 10⁻⁴, 2.1 × 10⁻⁴; p(corrected) = .03, .04) and were consistent across two large datasets.Our preclinical results support a role for CACNA1C in mood disorder pathophysiology, and the combination of human genetic and preclinical data support an interaction between sex and genotype.

  View details for DOI 10.1016/j.biopsych.2010.06.019

  View details for Web of Science ID 000283608600005

  View details for PubMedID 20723887

  View details for PubMedCentralID PMC2955812

• Hundreds of variants clustered in genomic loci and biological pathways affect human height NATURE Allen, H. L., Estrada, K., Lettre, G., Berndt, S. I., Weedon, M. N., Rivadeneira, F., Willer, C. J., Jackson, A. U., Vedantam, S., Raychaudhuri, S., Ferreira, T., Wood, A. R., Weyant, R. J., Segre, A. V., Speliotes, E. K., Wheeler, E., Soranzo, N., Park, J., Yang, J., Gudbjartsson, D., Heard-Costa, N. L., Randall, J. C., Qi, L., Smith, A. V., Maegi, R., Pastinen, T., Liang, L., Heid, I. M., Luan, J., Thorleifsson, G., Winkler, T. W., Goddard, M. E., Lo, K. S., Palmer, C., Workalemahu, T., Aulchenko, Y. S., Johansson, A., Zillikens, M. C., Feitosa, M. F., Esko, T., Johnson, T., Ketkar, S., Kraft, P., Mangino, M., Prokopenko, I., Absher, D., Albrecht, E., Ernst, F., Glazer, N. L., Hayward, C., Hottenga, J., Jacobs, K. B., Knowles, J. W., Kutalik, Z., Monda, K. L., Polasek, O., Preuss, M., Rayner, N. W., Robertson, N. R., Steinthorsdottir, V., Tyrer, J. P., Voight, B. F., Wiklund, F., Xu, J., Zhao, J. H., Nyholt, D. R., Pellikka, N., Perola, M., Perry, J. R., Surakka, I., Tammesoo, M., Altmaier, E. L., Amin, N., Aspelund, T., Bhangale, T., Boucher, G., Chasman, D. I., Chen, C., Coin, L., Cooper, M. N., Dixon, A. L., Gibson, Q., Grundberg, E., Hao, K., Junttila, M. J., Kaplan, L. M., Kettunen, J., Koenig, I. R., Kwan, T., Lawrence, R. W., Levinson, D. F., Lorentzon, M., McKnight, B., Morris, A. P., Mueller, M., Ngwa, J. S., Purcell, S., Rafelt, S., Salem, R. M., Salvi, E., Sanna, S., Shi, J., Sovio, U., Thompson, J. R., Turchin, M. C., Vandenput, L., Verlaan, D. J., Vitart, V., White, C. C., Ziegler, A., Almgren, P., Balmforth, A. J., Campbell, H., Citterio, L., de Grandi, A., Dominiczak, A., Duan, J., Elliott, P., Elosua, R., Eriksson, J. G., Freimer, N. B., Geus, E. J., Glorioso, N., Haiqing, S., Hartikainen, A., Havulinna, A. S., Hicks, A. A., Hui, J., Igl, W., Illig, T., Jula, A., Kajantie, E., Kilpelaeinen, T. O., Koiranen, M., Kolcic, I., Koskinen, S., Kovacs, P., Laitinen, J., Liu, J., Lokki, M., Marusic, A., Maschio, A., Meitinger, T., Mulas, A., Pare, G., Parker, A. N., Peden, J. F., Petersmann, A., Pichler, I., Pietilainen, K. H., Pouta, A., Riddertrale, M., Rotter, J. I., Sambrook, J. G., Sanders, A. R., Schmidt, C. O., Sinisalo, J., Smit, J. H., Stringham, H. M., Walters, G. B., Widen, E., Wild, S. H., Willemsen, G., Zagato, L., Zgaga, L., Zitting, P., Alavere, H., Farrall, M., McArdle, W. L., Nelis, M., Peters, M. J., Ripatti, S., vVan Meurs, J. B., Aben, K. K., Ardlie, K. G., Beckmann, J. S., Beilby, J. P., Bergman, R. N., Bergmann, S., Collins, F. S., Cusi, D., den Heijer, M., Eiriksdottir, G., Gejman, P. V., Hall, A. S., Hamsten, A., Huikuri, H. V., Iribarren, C., Kahonen, M., Kaprio, J., Kathiresan, S., Kiemeney, L., Kocher, T., Launer, L. J., Lehtimaki, T., Melander, O., Mosley, T. H., Musk, A. W., Nieminen, M. S., O'Donnell, C. J., Ohlsson, C., Oostra, B., Palmer, L. J., Raitakari, O., Ridker, P. M., Rioux, J. D., Rissanen, A., Rivolta, C., Schunkert, H., Shuldiner, A. R., Siscovick, D. S., Stumvoll, M., Toenjes, A., Tuomilehto, J., van Ommen, G., Viikari, J., Heath, A. C., Martin, N. G., Montgomery, G. W., Province, M. A., Kayser, M., Arnold, A. M., Atwood, L. D., Boerwinkle, E., Chanock, S. J., Deloukas, P., Gieger, C., Gronberg, H., Hall, P., Hattersley, A. T., Hengstenberg, C., Hoffman, W., Lathrop, G. M., Salomaa, V., Schreiber, S., Uda, M., Waterworth, D., Wright, A. F., Assimes, T. L., Barroso, I., Hofman, A., Mohlke, K. L., Boomsma, D. I., Caulfield, M. J., Cupples, L. A., Erdmann, J., Fox, C. S., Gudnason, V., Gyllensten, U., Harris, T. B., Hayes, R. B., Jarvelin, M., Mooser, V., Munroe, P. B., Ouwehand, W. H., Penninx, B. W., Pramstaller, P. P., Quertermous, T., Rudan, I., Samani, N. J., Spector, T. D., Voelzke, H., Watkins, H., Wilson, J. F., Groop, L. C., Haritunians, T., Hu, F. B., Kaplan, R. C., Metspalu, A., North, K. E., Schlessinger, D., Wareham, N. J., Hunter, D. J., O'Connell, J. R., Strachan, D. P., Schadt, H., Thorsteinsdottir, U., Peltonen, L., Uitterlinden, A. G., Visscher, P. M., Chatterjee, N., Loos, R. J., Boehnke, M., McCarthy, M. I., Ingelsson, E., Lindgren, C. M., Abecasis, G. R., Stefansson, K., Frayling, T. M., Hirschhorn, J. N. 2010; 467 (7317): 832-838

  Abstract

  Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

  View details for DOI 10.1038/nature09410

  View details for Web of Science ID 000282898700065

  View details for PubMedID 20881960

• The Internet-Based MGS2 Control Sample: Self Report of Mental Illness AMERICAN JOURNAL OF PSYCHIATRY Sanders, A. R., Levinson, D. F., Duan, J., Dennis, J. M., Li, R., Kendler, K. S., Rice, J. P., Shi, J., Mowry, B. J., Amin, F., Silverman, J. M., Buccola, N. G., Byerley, W. F., Black, D. W., Freedman, R., Cloninger, C. R., Gejman, P. V. 2010; 167 (7): 854-865

  Abstract

  The Molecular Genetics of Schizophrenia (MGS2) project recruited an adult control sample of non-Hispanic European-ancestry (N=3,364) and African American (N=1,301) subjects.Subjects gave consent to deposit phenotypic data and blood samples into a repository for general research use, with full anonymization of the sample. The authors compared the control sample with population census data for demographic data and with previous population surveys for anthropometrics and prevalences of psychiatric disorders as estimated by an Internet-administered questionnaire.The full MGS2 control sample includes 4,665 subjects (European-ancestry: N=3,364; African American: N=1,301), of whom 3,626 were included in the MGS2 genome-wide association study (GWAS). The sample is generally demographically representative of the U.S. population, except for being older and more female, educated, and affluent, although all strata are represented. Self-reported ancestry was consistent with genotypic and census data. Lifetime prevalences for depressive, anxiety, and substance use diagnoses were higher than in previous population-based surveys, probably due to use of an abbreviated self-report instrument. However, patterns such as sex ratios, comorbidity, and demographic associations were consistent with previous reports. DNA quality for the Internet collected/evaluated control sample was comparable to that of the face-to-face case sample.The Internet-based methods facilitated the rapid collection of large and anonymized non-Hispanic European-ancestry and African American control samples that have been validated as being generally representative for many aspects of demography, ancestry, and morbidity. Utilization of clinical screening data shared with the scientific community may permit investigators to select appropriate controls for some studies.

  View details for DOI 10.1176/appi.ajp.2010.09071050

  View details for Web of Science ID 000279429300020

  View details for PubMedID 20516154

• Genome-wide meta-analyses identify multiple loci associated with smoking behavior NATURE GENETICS Furberg, H., Kim, Y., Dackor, J., Boerwinkle, E., Franceschini, N., Ardissino, D., Bernardinelli, L., Mannucci, P. M., Mauri, F., Merlini, P. A., Absher, D., Assimes, T. L., Fortmann, S. P., Iribarren, C., Knowles, J. W., Quertermous, T., Ferrucci, L., Tanaka, T., Bis, J. C., Furberg, C. D., Haritunians, T., McKnight, B., Psaty, B. M., Taylor, K. D., Thacker, E. L., Almgren, P., Groop, L., Ladenvall, C., Boehnke, M., Jackson, A. U., Mohlke, K. L., Stringham, H. M., Tuomilehto, J., Benjamin, E. J., Hwang, S., Levy, D., Preis, S. R., Vasan, R. S., Duan, J., Gejman, P. V., Levinson, D. F., Sanders, A. R., Shi, J., Lips, E. H., McKay, J. D., Agudo, A., Barzan, L., Bencko, V., Benhamou, S., Castellsague, X., Canova, C., Conway, D. I., Fabianova, E., Foretova, L., Janout, V., Healy, C. M., Holcatova, I., Kjaerheim, K., Lagiou, P., Lissowska, J., Lowry, R., Macfarlane, T. V., Mates, D., Richiardi, L., Rudnai, P., Szeszenia-Dabrowska, N., Zaridze, D., Znaor, A., Lathrop, M., Brennan, P., Bandinelli, S., Frayling, T. M., Guralnik, J. M., Milaneschi, Y., Perry, J. R., Altshuler, D., Elosua, R., Kathiresan, S., Lucas, G., Melander, O., O'Donnell, C. J., Salomaa, V., Schwartz, S. M., Voight, B. F., Penninx, B. W., Smit, J. H., Vogelzangs, N., Boomsma, D. I., de Geus, E. J., Vink, J. M., Willemsen, G., Chanock, S. J., Gu, F., Hankinson, S. E., Hunter, D. J., Hofman, A., Tiemeier, H., Uitterlinden, A. G., van Duijn, C. M., Walter, S., Chasman, D. I., Everett, B. M., Pare, G., Ridker, P. M., Li, M. D., Maes, H. H., Audrain-McGovern, J., Posthuma, D., Thornton, L. M., Lerman, C., Kaprio, J., Rose, J. E., Ioannidis, J. P., Kraft, P., Lin, D., Sullivan, P. F. 2010; 42 (5): 441-U134

  Abstract

  Consistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n > 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], beta = 1.03, standard error (s.e.) = 0.053, P = 2.8 x 10(-73)). Two 10q25 SNPs (rs1329650[G], beta = 0.367, s.e. = 0.059, P = 5.7 x 10(-10); and rs1028936[A], beta = 0.446, s.e. = 0.074, P = 1.3 x 10(-9)) and one 9q13 SNP in EGLN2 (rs3733829[G], beta = 0.333, s.e. = 0.058, P = 1.0 x 10(-8)) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95% confidence interval (Cl) 1.04-1.08, P = 1.8 x 10(-8)). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95% Cl 1.08-1.18, P = 3.6 x 10(-8)) was significantly associated with smoking cessation.

  View details for DOI 10.1038/ng.571

  View details for Web of Science ID 000277179500017

  View details for PubMedID 20418890

  View details for PubMedCentralID PMC2914600

• Mood Disorder Susceptibility Gene CACNA1C Modifies Mood-Related Behaviors in Mice and Interacts with Sex to Influence Behavior in Mice and Diagnosis in Humans 65th Annual Convention of the Society-of-Biological-Psychiatry Dao, D. T., Mahon, P. B., Cai, X., Kovacsics, C. E., Blackwell, R. A., O'Donnell, P., Shi, J., Zandi, P. P., Knowles, J. A., Weissman, M. M., Coryell, W., Scheftner, W. A., Lawson, W. B., Levinson, D. F., Thompson, S. M., Potash, J. B., Gould, T. D. ELSEVIER SCIENCE INC. 2010: 124S–125S

  View details for Web of Science ID 000277064200397

• SEGMENT-WISE GENOME-WIDE ASSOCIATION ANALYSIS IDENTIFIES A LIMITED NUMBER OF REPLICABLE CANDIDATE REGIONS ASSOCIATED WITH SCHIZOPHRENIA Derks, E. M., Gladwin, T., Rietschel, M., Mattheisen, M., Breuer, R., Schulze, T. G., Nothen, M. M., Levinson, D., Shi, J., Cichon, S., Freimer, N. B., Cantor, R., Ophoff, R. A., Group XXX ELSEVIER SCIENCE BV. 2010: 219

  View details for DOI 10.1016/j.schres.2010.02.312

  View details for Web of Science ID 000276936800311

• Genome-Wide Linkage and Follow-Up Association Study of Postpartum Mood Symptoms AMERICAN JOURNAL OF PSYCHIATRY Mahon, P. B., Payne, J. L., MacKinnon, D. F., Mondimore, F. M., Goes, F. S., Schweizer, B., Jancic, D., Coryell, W. H., Holmans, P. A., Shi, J., Knowles, J. A., Scheftner, W. A., Weissman, M. M., Levinson, D. F., DePaulo, J. R., Zandi, P. P., Potash, J. B. 2009; 166 (11): 1229-1237

  Abstract

  Family studies have suggested that postpartum mood symptoms might have a partly genetic etiology. The authors used a genome-wide linkage analysis to search for chromosomal regions that harbor genetic variants conferring susceptibility for such symptoms. The authors then fine-mapped their best linkage regions, assessing single nucleotide polymorphisms (SNPs) for genetic association with postpartum symptoms.Subjects were ascertained from two studies: the NIMH Genetics Initiative Bipolar Disorder project and the Genetics of Recurrent Early-Onset Depression. Subjects included women with a history of pregnancy, any mood disorder, and information about postpartum symptoms. In the linkage study, 1,210 women met criteria (23% with postpartum symptoms), and 417 microsatellite markers were analyzed in multipoint allele sharing analyses. For the association study, 759 women met criteria (25% with postpartum symptoms), and 16,916 SNPs in the regions of the best linkage peaks were assessed for association with postpartum symptoms.The maximum linkage peak for postpartum symptoms occurred on chromosome 1q21.3-q32.1, with a chromosome-wide significant likelihood ratio Z score (Z(LR)) of 2.93 (permutation p=0.02). This was a significant increase over the baseline Z(LR) of 0.32 observed at this locus among all women with a mood disorder (permutation p=0.004). Suggestive linkage was also found on 9p24.3-p22.3 (Z(LR)=2.91). In the fine-mapping study, the strongest implicated gene was HMCN1 (nominal p=0.00017), containing four estrogen receptor binding sites, although this was not region-wide significant.This is the first study to examine the genetic etiology of postpartum mood symptoms using genome-wide data. The results suggest that genetic variations on chromosomes 1q21.3-q32.1 and 9p24.3-p22.3 may increase susceptibility to postpartum mood symptoms.

  View details for DOI 10.1176/appi.ajp.2009.09030417

  View details for Web of Science ID 000271429600009

  View details for PubMedID 19755578

  View details for PubMedCentralID PMC3665341

• Common variants on chromosome 6p22.1 are associated with schizophrenia NATURE Shi, J., Levinson, D. F., Duan, J., Sanders, A. R., Zheng, Y., Pe'er, I., Dudbridge, F., Holmans, P. A., Whittemore, A. S., Mowry, B. J., Olincy, A., Amin, F., Cloninger, C. R., Silverman, J. M., Buccola, N. G., Byerley, W. F., Black, D. W., Crowe, R. R., Oksenberg, J. R., Mirel, D. B., Kendler, K. S., Freedman, R., Gejman, P. V. 2009; 460 (7256): 753-757

  Abstract

  Schizophrenia, a devastating psychiatric disorder, has a prevalence of 0.5-1%, with high heritability (80-85%) and complex transmission. Recent studies implicate rare, large, high-penetrance copy number variants in some cases, but the genes or biological mechanisms that underlie susceptibility are not known. Here we show that schizophrenia is significantly associated with single nucleotide polymorphisms (SNPs) in the extended major histocompatibility complex region on chromosome 6. We carried out a genome-wide association study of common SNPs in the Molecular Genetics of Schizophrenia (MGS) case-control sample, and then a meta-analysis of data from the MGS, International Schizophrenia Consortium and SGENE data sets. No MGS finding achieved genome-wide statistical significance. In the meta-analysis of European-ancestry subjects (8,008 cases, 19,077 controls), significant association with schizophrenia was observed in a region of linkage disequilibrium on chromosome 6p22.1 (P = 9.54 x 10(-9)). This region includes a histone gene cluster and several immunity-related genes--possibly implicating aetiological mechanisms involving chromatin modification, transcriptional regulation, autoimmunity and/or infection. These results demonstrate that common schizophrenia susceptibility alleles can be detected. The characterization of these signals will suggest important directions for research on susceptibility mechanisms.

  View details for DOI 10.1038/nature08192

  View details for PubMedID 19571809

• Genomewide linkage scan of schizophrenia in a large multicenter pedigree sample using single nucleotide polymorphisms MOLECULAR PSYCHIATRY Holmans, P. A., Riley, B., Pulver, A. E., Owen, M. J., Wildenauer, D. B., GEJMAN, P. V., Mowry, B. J., Laurent, C., Kendler, K. S., Nestadt, G., Williams, N. M., Schwab, S. G., Sanders, A. R., Nertney, D., Mallet, J., Wormley, B., Lasseter, V. K., O'Donovan, M. C., Duan, J., Albus, M., Alexander, M., Godard, S., Ribble, R., Liang, K. Y., Norton, N., Maier, W., Papadimitriou, G., Walsh, D., Jay, M., O'Neill, A., Lerer, F. B., Dikeos, D., Crowe, R. R., Silverman, J. M., Levinson, D. F. 2009; 14 (8): 786-795

  Abstract

  A genomewide linkage scan was carried out in eight clinical samples of informative schizophrenia families. After all quality control checks, the analysis of 707 European-ancestry families included 1615 affected and 1602 unaffected genotyped individuals, and the analysis of all 807 families included 1900 affected and 1839 unaffected individuals. Multipoint linkage analysis with correction for marker-marker linkage disequilibrium was carried out with 5861 single nucleotide polymorphisms (SNPs; Illumina version 4.0 linkage map). Suggestive evidence for linkage (European families) was observed on chromosomes 8p21, 8q24.1, 9q34 and 12q24.1 in nonparametric and/or parametric analyses. In a logistic regression allele-sharing analysis of linkage allowing for intersite heterogeneity, genomewide significant evidence for linkage was observed on chromosome 10p12. Significant heterogeneity was also observed on chromosome 22q11.1. Evidence for linkage across family sets and analyses was most consistent on chromosome 8p21, with a one-LOD support interval that does not include the candidate gene NRG1, suggesting that one or more other susceptibility loci might exist in the region. In this era of genomewide association and deep resequencing studies, consensus linkage regions deserve continued attention, given that linkage signals can be produced by many types of genomic variation, including any combination of multiple common or rare SNPs or copy number variants in a region.

  View details for DOI 10.1038/mp.2009.11

  View details for Web of Science ID 000268239200008

  View details for PubMedID 19223858

  View details for PubMedCentralID PMC2714870

• Meta-analysis of 32 genome-wide linkage studies of schizophrenia MOLECULAR PSYCHIATRY Ng, M. Y., Levinson, D. F., Faraone, S. V., Suarez, B. K., DeLisi, L. E., Arinami, T., Riley, B., Paunio, T., Pulver, A. E., Irmansyah, Holmans, P. A., Escamilla, M., Wildenauer, D. B., Williams, N. M., Laurent, C., Mowry, B. J., Brzustowicz, L. M., Maziade, M., Sklar, P., Garver, D. L., Abecasis, G. R., Lerer, B., Fallin, M. D., Gurling, H. M., GEJMAN, P. V., Lindholm, E., Moises, H. W., Byerley, W., Wijsman, E. M., Forabosco, P., Tsuang, M. T., Hwu, H., Okazaki, Y., Kendler, K. S., Wormley, B., Fanous, A., Walsh, D., O'Neill, F. A., Peltonen, L., Nestadt, G., Lasseter, V. K., Liang, K. Y., Papadimitriou, G. M., Dikeos, D. G., Schwab, S. G., Owen, M. J., O'Donovan, M. C., Norton, N., Hare, E., Raventos, H., Nicolini, H., Albus, M., Maier, W., Nimgaonkar, V. L., Terenius, L., Mallet, J., Jay, M., Godard, S., Nertney, D., Alexander, M., Crowe, R. R., Silverman, J. M., Bassett, A. S., Roy, M., Merette, C., Pato, C. N., Pato, M. T., Roos, J. L., Kohn, Y., Amann-Zalcenstein, D., Kalsi, G., McQuillin, A., Curtis, D., Brynjolfson, J., Sigmundsson, T., Petursson, H., Sanders, A. R., Duan, J., Jazin, E., Myles-Worsley, M., Karayiorgou, M., Lewis, C. M. 2009; 14 (8): 774-785

  Abstract

  A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (P(SR)) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for 'aggregate' genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies.

  View details for DOI 10.1038/mp.2008.135

  View details for Web of Science ID 000268239200007

  View details for PubMedID 19349958

  View details for PubMedCentralID PMC2715392

• Narcolepsy is strongly associated with the T-cell receptor alpha locus NATURE GENETICS Hallmayer, J., Faraco, J., Lin, L., Hesselson, S., Winkelmann, J., Kawashima, M., Mayer, G., Plazzi, G., Nevsimalova, S., Bourgin, P., Hong, S. S., Honda, Y., Honda, M., Hoegl, B., Longstreth, W. T., Montplaisir, J., Kemlink, D., Einen, M., Chen, J., Musone, S. L., Akana, M., Miyagawa, T., Duan, J., Desautels, A., Erhardt, C., Hesla, P. E., Poli, F., Frauscher, B., Jeong, J., Lee, S., Ton, T. G., Kvale, M., Kolesar, L., Dobrovolna, M., Nepom, G. T., Salomon, D., Wichmann, H., Rouleau, G. A., Gieger, C., Levinson, D. F., Gejman, P. V., Meitinger, T., Young, T., Peppard, P., Tokunaga, K., Kwok, P., Risch, N., Mignot, E. 2009; 41 (6): 708-711

  Abstract

  Narcolepsy with cataplexy, characterized by sleepiness and rapid onset into REM sleep, affects 1 in 2,000 individuals. Narcolepsy was first shown to be tightly associated with HLA-DR2 (ref. 3) and later sublocalized to DQB1*0602 (ref. 4). Following studies in dogs and mice, a 95% loss of hypocretin-producing cells in postmortem hypothalami from narcoleptic individuals was reported. Using genome-wide association (GWA) in Caucasians with replication in three ethnic groups, we found association between narcolepsy and polymorphisms in the TRA@ (T-cell receptor alpha) locus, with highest significance at rs1154155 (average allelic odds ratio 1.69, genotypic odds ratios 1.94 and 2.55, P < 10(-21), 1,830 cases, 2,164 controls). This is the first documented genetic involvement of the TRA@ locus, encoding the major receptor for HLA-peptide presentation, in any disease. It is still unclear how specific HLA alleles confer susceptibility to over 100 HLA-associated disorders; thus, narcolepsy will provide new insights on how HLA-TCR interactions contribute to organ-specific autoimmune targeting and may serve as a model for over 100 other HLA-associated disorders.

  View details for DOI 10.1038/ng.372

  View details for PubMedID 19412176

• Genomewide Association Studies: History, Rationale, and Prospects for Psychiatric Disorders AMERICAN JOURNAL OF PSYCHIATRY Cichon, S., Craddock, N., Daly, M., Faraone, S. V., Gejman, P. V., Kelsoe, J., Lehner, T., Levinson, D. F., Moran, A., Sklar, P., Sullivan, P. F. 2009; 166 (5): 540-556

  Abstract

  The authors conducted a review of the history and empirical basis of genomewide association studies (GWAS), the rationale for GWAS of psychiatric disorders, results to date, limitations, and plans for GWAS meta-analyses.A literature review was carried out, power and other issues discussed, and planned studies assessed.Most of the genomic DNA sequence differences between any two people are common (frequency >5%) single nucleotide polymorphisms (SNPs). Because of localized patterns of correlation (linkage disequilibrium), 500,000 to 1,000,000 of these SNPs can test the hypothesis that one or more common variants explain part of the genetic risk for a disease. GWAS technologies can also detect some of the copy number variants (deletions and duplications) in the genome. Systematic study of rare variants will require large-scale resequencing analyses. GWAS methods have detected a remarkable number of robust genetic associations for dozens of common diseases and traits, leading to new pathophysiological hypotheses, although only small proportions of genetic variance have been explained thus far and therapeutic applications will require substantial further effort. Study design issues, power, and limitations are discussed. For psychiatric disorders, there are initial significant findings for common SNPs and for rare copy number variants, and many other studies are in progress.GWAS of large samples have detected associations of common SNPs and of rare copy number variants with psychiatric disorders. More findings are likely, since larger GWAS samples detect larger numbers of common susceptibility variants, with smaller effects. The Psychiatric GWAS Consortium is conducting GWAS meta-analyses for schizophrenia, bipolar disorder, major depressive disorder, autism, and attention deficit hyperactivity disorder. Based on results for other diseases, larger samples will be required. The contribution of GWAS will depend on the true genetic architecture of each disorder.

  View details for DOI 10.1176/appi.ajp.2008.08091354

  View details for Web of Science ID 000265662500009

  View details for PubMedID 19339359

• Premenstrual mood symptoms: study of familiality and personality correlates in mood disorder pedigrees ARCHIVES OF WOMENS MENTAL HEALTH Payne, J. L., Klein, S. R., Zamoiski, R. B., Zandi, P. P., Bienvenu, O. J., MacKinnon, D. F., Mondimore, F. M., Schweizer, B., Swartz, K. L., Crowe, R. P., Scheftner, W. A., Weissman, M. M., Levinson, D. F., DePaulo, J. R., Potash, J. B. 2009; 12 (1): 27-34

  Abstract

  We sought to determine whether premenstrual mood symptoms exhibit familial aggregation in bipolar disorder or major depression pedigrees. Two thousand eight hundred seventy-six women were interviewed with the Diagnostic Interview for Genetic Studies as part of either the NIMH Genetics Initiative Bipolar Disorder Collaborative study or the Genetics of Early Onset Major Depression (GenRED) study and asked whether they had experienced severe mood symptoms premenstrually. In families with two or more female siblings with bipolar disorder (BP) or major depressive disorder (MDD), we examined the odds of having premenstrual mood symptoms given one or more siblings with these symptoms. For the GenRED MDD sample we also assessed the impact of personality as measured by the NEO-FFI. Premenstrual mood symptoms did not exhibit familial aggregation in families with BP or MDD. We unexpectedly found an association between high NEO openness scores and premenstrual mood symptoms, but neither this factor, nor NEO neuroticism influenced evidence for familial aggregation of symptoms. Limitations include the retrospective interview, the lack of data on premenstrual dysphoric disorder, and the inability to control for factors such as medication use.

  View details for DOI 10.1007/s00737-008-0043-4

  View details for Web of Science ID 000263486000003

  View details for PubMedID 19137238

• A framework for interpreting genome-wide association studies of psychiatric disorders The Psychiatric GWAS Consortium Steering Committee MOLECULAR PSYCHIATRY Cichon, S., Craddock, N., Daly, M., Faraone, S. V., Gejman, P. V., Kelsoe, J., Lehner, T., Levinson, D. F., Moran, A., Sklar, P., Sullivan, P. F. 2009; 14 (1): 10-17

  Abstract

  Genome-wide association studies (GWAS) have yielded a plethora of new findings in the past 3 years. By early 2009, GWAS on 47 samples of subjects with attention-deficit hyperactivity disorder, autism, bipolar disorder, major depressive disorder and schizophrenia will be completed. Taken together, these GWAS constitute the largest biological experiment ever conducted in psychiatry (59 000 independent cases and controls, 7700 family trios and >40 billion genotypes). We know that GWAS can work, and the question now is whether it will work for psychiatric disorders. In this review, we describe these studies, the Psychiatric GWAS Consortium for meta-analyses of these data, and provide a logical framework for interpretation of some of the conceivable outcomes.

  View details for DOI 10.1038/mp.2008.126

  View details for Web of Science ID 000261866300004

• Analysis of 10 independent samples provides evidence for association between schizophrenia and a SNP flanking fibroblast growth factor receptor 2 MOLECULAR PSYCHIATRY O'Donovan, M. C., Norton, N., Williams, H., Peirce, T., Moskvina, V., Nikolov, I., Hamshere, M., Carroll, L., Georgieva, L., Dwyer, S., Holmans, P., Marchini, J. L., Spencer, C. C., HOWIE, B., Leung, H., Giegling, I., Hartmann, A. M., Moeller, H., Morris, D. W., Shi, Y., Feng, G., Hoffmann, P., Propping, P., Vasilescu, C., Maier, W., Rietschel, M., Zammit, S., Schumacher, J., QUINN, E. M., Schulze, T. G., Iwata, N., Ikeda, M., Darvasi, A., Shifman, S., He, L., Duan, J., Sanders, A. R., Levinson, D. F., Adolfsson, R., Osby, U., Terenius, L., Jonsson, E. G., Cichon, S., Noethen, M. M., Gill, M., Corvin, A. P., Rujescu, D., GEJMAN, P. V., Kirov, G., Craddock, N., Williams, N. M., Owen, M. J. 2009; 14 (1): 30-36

  Abstract

  We and others have previously reported linkage to schizophrenia on chromosome 10q25-q26 but, to date, a susceptibility gene in the region has not been identified. We examined data from 3606 single-nucleotide polymorphisms (SNPs) mapping to 10q25-q26 that had been typed in a genome-wide association study (GWAS) of schizophrenia (479 UK cases/2937 controls). SNPs with P<0.01 (n=40) were genotyped in an additional 163 UK cases and those markers that remained nominally significant at P<0.01 (n=22) were genotyped in replication samples from Ireland, Germany and Bulgaria consisting of a total of 1664 cases with schizophrenia and 3541 controls. Only one SNP, rs17101921, was nominally significant after meta-analyses across the replication samples and this was genotyped in an additional six samples from the United States/Australia, Germany, China, Japan, Israel and Sweden (n=5142 cases/6561 controls). Across all replication samples, the allele at rs17101921 that was associated in the GWAS showed evidence for association independent of the original data (OR 1.17 (95% CI 1.06-1.29), P=0.0009). The SNP maps 85 kb from the nearest gene encoding fibroblast growth factor receptor 2 (FGFR2) making this a potential susceptibility gene for schizophrenia.

  View details for DOI 10.1038/mp.2008.108

  View details for Web of Science ID 000261866300006

  View details for PubMedID 18813210

  View details for PubMedCentralID PMC3016613

• Identification of loci associated with schizophrenia by genome-wide association and follow-up NATURE GENETICS O'Donovan, M. C., Craddock, N., Norton, N., Williams, H., Peirce, T., Moskvina, V., Nikolov, I., Hamshere, M., Carroll, L., Georgieva, L., Dwyer, S., Holmans, P., Marchini, J. L., Spencer, C. C., Howie, B., Leung, H., Hartmann, A. M., Moeller, H., Morris, D. W., Shi, Y., Feng, G., Hoffmann, P., Propping, P., Vasilescu, C., Maier, W., Rietschel, M., Zammit, S., Schumacher, J., Quinn, E. M., Schulze, T. G., Williams, N. M., Giegling, I., Iwata, N., Ikeda, M., Darvasi, A., Shifman, S., He, L., Duan, J., Sanders, A. R., Levinson, D. F., Gejman, P. V., Cichon, S., Noethen, M. M., Gill, M., Corvin, A., Rujescu, D., Kirov, G., Owen, M. J. 2008; 40 (9): 1053-1055

  Abstract

  We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10(-5) in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 x 10(-4)), and the overall pattern of replication was unlikely to occur by chance (P = 9 x 10(-8)). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 x 10(-7)) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 x 10(-9)).

  View details for DOI 10.1038/ng.201

  View details for Web of Science ID 000258761200014

  View details for PubMedID 18677311

• Significance levels for studies with correlated test statistics BIOSTATISTICS Shi, J., Levinson, D. F., Whittemore, A. S. 2008; 9 (3): 458-466

  Abstract

  When testing large numbers of null hypotheses, one needs to assess the evidence against the global null hypothesis that none of the hypotheses is false. Such evidence typically is based on the test statistic of the largest magnitude, whose statistical significance is evaluated by permuting the sample units to simulate its null distribution. Efron (2007) has noted that correlation among the test statistics can induce substantial interstudy variation in the shapes of their histograms, which may cause misleading tail counts. Here, we show that permutation-based estimates of the overall significance level also can be misleading when the test statistics are correlated. We propose that such estimates be conditioned on a simple measure of the spread of the observed histogram, and we provide a method for obtaining conditional significance levels. We justify this conditioning using the conditionality principle described by Cox and Hinkley (1974). Application of the method to gene expression data illustrates the circumstances when conditional significance levels are needed.

  View details for DOI 10.1093/biostatistics/kxm047

  View details for PubMedID 18089626

• Linkage disequilibrium mapping of a chromosome 15q25-26 major depression linkage region and sequencing of NTRK3 BIOLOGICAL PSYCHIATRY Verma, R., Holmans, P., Knowles, J. A., Grover, D., Evgrafov, O. V., Crowe, R. R., Scheftner, W. A., Weissman, M. M., DePaulo, J. R., Potash, J. B., Levinson, D. F. 2008; 63 (12): 1185-1189

  Abstract

  We reported genome-wide significant linkage on chromosome 15q25.3-26.2 to recurrent early-onset major depressive disorder (MDD-RE). Here we present initial linkage-disequilibrium (LD) fine mapping of this signal and sequence analysis of NTRK3 (neurotrophic receptor kinase-3), a biologically plausible candidate gene.In 300 pedigrees informative for family-based association, 1195 individuals were genotyped for 795 single nucleotide polymorphism (SNPs). We resequenced 21 exons and 7 highly conserved NTRK3 regions in 176 MDD-RE cases to test for an excess of rare functional variants and, 176 controls for case-control analysis of common variants.LD mapping showed nominally significant association in NTRK3, FLJ12484, RHCG, DKFZp547K1113, VPS33B, SV2B, SLCO3A1, RGMA, and MCTP2 with MDD-RE. In NTRK3, five SNPs had nominally significant p values (.035-.001). Sequence analysis revealed 35 variants (24 novel, including 9 rare exonic); the number of rare variants did not exceed chance expectation. Case-control analysis of 13 common variants showed modest nominal association of MDD-RE with rs4887379, rs6496463, and rs3825882 (p = .008, .048, and .034), which were in partial LD with four of five associated SNPs from the family-based experiment.Common variants in NTRK3 or other genes identified might play a role in MDD-RE. However, much larger studies are required for full evaluation of this region.

  View details for DOI 10.1016/j.biopsych.2008.02.005

  View details for Web of Science ID 000256491700013

  View details for PubMedID 18367154

  View details for PubMedCentralID PMC2435230

• Clinical case management of revolving door patients - a semi-randomized study ACTA PSYCHIATRICA SCANDINAVICA Lichtenberg, P., Levinson, D., Sharshevsky, Y., Feldman, D., Lachman, M. 2008; 117 (6): 449-454

  Abstract

  To assess the effectiveness of psychiatric clinical case management.Subjects with at least three admissions in the previous 2 years were randomized into a clinical case management group (CMG; n = 122) and a standard care group (SCG; n = 95). Individuals who refused or were not located were included in a third, non-randomized no-treatment group (NTG; n = 153). Parameters assessed included utilization of in-patient services and psychosocial functioning.We found no difference between the CMG and the SCG in psychosocial functioning as evaluated by interviewers, and no difference between the three groups in hospitalization. In subjects' self-ratings, the CMG showed slight improvement in psychosocial functioning.Clinical case management did not prove itself superior to standard care in a revolving door population.

  View details for DOI 10.1111/j.1600-0447.2008.01170.x

  View details for Web of Science ID 000255813700007

  View details for PubMedID 18331577

• It is time to take a stand for medical research and against terrorism targeting medical scientists BIOLOGICAL PSYCHIATRY Krystal, J. H., Carter, C. S., Geschwind, D., Manji, H. K., March, J. S., Nestler, E. J., Zubieta, J., Charney, D. S., Goldman, D., Gur, R. E., Lieberman, J. A., Roy-Byrne, P., Rubinow, D. R., Anderson, S. A., Barondes, S., Berman, K. F., Blair, J., Braff, D. L., Brown, E. S., Calabrese, J. R., Carlezon, W. A., Cook, E. H., Davidson, R. J., Davis, M., Desimone, R., Drevets, W. C., Duman, R. S., Essock, S. M., Faraone, S. V., Freedman, R., Friston, K. J., Gelernter, J., Geller, B., Gill, M., Gould, E., Grace, A. A., Grillon, C., Gueorguieva, R., Hariri, A. R., Innis, R. B., Jones, E. G., Kleinman, J. E., Koob, G. F., Krystal, A. D., Leibenluft, E., Levinson, D. F., Levitt, P. R., Lewis, D. A., Liberzon, I., Lipska, B. K., Marder, S. R., Markou, A., Mason, G. F., McDougle, C. J., McEwen, B. S., McMahon, F. J., Meaney, M. J., Meltzer, H. Y., Merikangas, K. R., Meyer-Lindenberg, A., Mirnics, K., Monteggia, L. M., Neumeister, A., O'Brien, C. P., Owen, M. J., Pine, D. S., Rapoport, J. L., Rauch, S. L., Robbins, T. W., Rosenbaum, J. F., Rosenberg, D. R., Ross, C. A., Rush, A. J., Sackeim, H. A., Sanacora, G., Schatzberg, A. F., Shaham, Y., Siever, L. J., Sunderland, T., Tecott, L. H., Thase, M. E., Todd, R. D., Weissman, M. M., Yehuda, R., Yoshikawa, T., Young, E. A., McCandless, R. 2008; 63 (8): 725-727

  View details for DOI 10.1016/j.biopsych.2008.03-005

  View details for Web of Science ID 000254817100001

  View details for PubMedID 18371494

• No significant association of 14 candidate genes with schizophrenia in a large European ancestry sample: Implications for psychiatric genetics AMERICAN JOURNAL OF PSYCHIATRY Sanders, A. R., Duan, J., Levinson, D. F., Shi, J., He, D., Hou, C., Burrell, G. J., Rice, J. P., Nertney, D. A., Olincy, A., Rozic, P., Vinogradov, S., Buccola, N. G., Mowry, B. J., Freedman, R., Amin, F., Black, D. W., Silverman, J. M., Byerley, W. F., Crowe, R. R., Cloninger, C. R., Martinez, M., Gejman, P. V. 2008; 165 (4): 497-506

  Abstract

  The authors carried out a genetic association study of 14 schizophrenia candidate genes (RGS4, DISC1, DTNBP1, STX7, TAAR6, PPP3CC, NRG1, DRD2, HTR2A, DAOA, AKT1, CHRNA7, COMT, and ARVCF). This study tested the hypothesis of association of schizophrenia with common single nucleotide polymorphisms (SNPs) in these genes using the largest sample to date that has been collected with uniform clinical methods and the most comprehensive set of SNPs in each gene.The sample included 1,870 cases (schizophrenia and schizoaffective disorder) and 2,002 screened comparison subjects (i.e. controls), all of European ancestry, with ancestral outliers excluded based on analysis of ancestry-informative markers. The authors genotyped 789 SNPs, including tags for most common SNPs in each gene, SNPs previously reported as associated, and SNPs located in functional domains of genes such as promoters, coding exons (including nonsynonymous SNPs), 3' untranslated regions, and conserved noncoding sequences. After extensive data cleaning, 648 SNPs were analyzed for association of single SNPs and of haplotypes.Neither experiment-wide nor gene-wide statistical significance was observed in the primary single-SNP analyses or in secondary analyses of haplotypes or of imputed genotypes for additional common HapMap SNPs. Results in SNPs previously reported as associated with schizophrenia were consistent with chance expectation, and four functional polymorphisms in COMT, DRD2, and HTR2A did not produce nominally significant evidence to support previous evidence for association.It is unlikely that common SNPs in these genes account for a substantial proportion of the genetic risk for schizophrenia, although small effects cannot be ruled out.

  View details for DOI 10.1176/appi.ajp.2007.07101573

  View details for Web of Science ID 000254577800016

  View details for PubMedID 18198266

• Investigating the role of p11 (S100A10) sequence variation in susceptibility to major depression AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Verma, R., Cutler, D. J., Holmans, P., Knowles, J. A., Crowe, R. R., Scheftner, W. A., Weissman, M. M., DePaulo, J. R., Levinson, D. F., Potash, J. B. 2007; 144B (8): 1079-1082

  Abstract

  Recent evidence suggests a potential role for the p11 gene in conferring risk to depressive disorders. p11 has been shown to influence serotonergic transmission, and its expression was found to be reduced in a mouse model of depression, as well as in post-mortem brain tissue from major depressive disorder (MDD) cases. In the present study, we tested for rare variants in p11 by resequencing promoter, exonic and flanking intronic regions in 176 MDD cases and 176 matched controls. We also assessed common variation by genotyping eight single nucleotide polymorphisms (SNPs), seven tag SNPs and one found through resequencing, in 641 cases and 650 controls. Resequencing revealed nine novel rare variants, including a missense mutation (Asp60Glu) observed in one case and one control, and four variants that occurred only in cases and not controls. The number of rare variants in cases did not exceed that expected by chance for the length of sequence analyzed, and also was not significantly greater than that observed in controls. Resequencing also identified two known SNPs, one (rs4845720) of which was significantly more frequent in cases than controls in the resequenced sample (3.1% vs. 0.9%, P = 0.03), though not in the larger sample (3% vs. 2%, P = 0.15). None of the tag SNPs showed any evidence of association. Our results do not support a major role for either common or rare p11 SNPs with MDD. Several limitations of the study are discussed.

  View details for DOI 10.1002/ajmg.b.30514

  View details for Web of Science ID 000251096700018

  View details for PubMedID 17510952

• Bootstrap classification and point-based feature selection from age-staged mouse cerebellum tissues of matrix assisted laser desorption/ionization mass spectra using a fuzzy rule-building expert system ANALYTICA CHIMICA ACTA Harrington, P. B., Laurent, C., Levinson, D. F., Levitt, P., Markey, S. P. 2007; 599 (2): 219-231

  Abstract

  A bootstrap method for point-based detection of candidate biomarker peaks has been developed from pattern classifiers. Point-based detection methods are advantageous in comparison to peak-based methods. Peak determination and selection are problematic when spectral peaks are not baseline resolved or on a varying baseline. The benefit of point-based detection is that peaks can be globally determined from the characteristic features of the entire data set (i.e., subsets of candidate points) as opposed to the traditional method of selecting peaks from individual spectra and then combining the peak list into a data set. The point-based method is demonstrated to be more effective and efficient using a synthetic data set when compared to using Mahalanobis distance for feature selection. In addition, probabilities that characterize the uniqueness of the peaks are determined. This method was applied for detecting peaks that characterize age-specific patterns of protein expression of developing and adult mouse cerebella from matrix assisted laser desorption/ionization (MALDI) mass spectrometry (MS) data. The mice comprised three age groups: 42 adults, 19 14-day-old pups, and 16 7-day-old pups. Three sequential spectra were obtained from each tissue section to yield 126, 57 and 48 spectra for adult, 14-day-old pup, and 7-day-old pup spectra, respectively. Each spectrum comprised 71,879 mass measurements in a range of 3.5-50 kDa. A previous study revealed that 846 unique peaks were detected that were consistent for 50% of the mice in each age group (C. Laurent, D.F. Levinson, S.A. Schwartz, P.B. Harrington, S.P. Markey, R.M. Caprioli, P. Levitt, Direct profiling of the cerebellum by MALDI MS: a methodological study in postnatal and adult mouse, J. Neurosci. Res. 81 (2005) 613-621.). A fuzzy rule-building expert system (FuRES) was applied to investigate the correlation of age with features in the MS data. FuRES detected two outlier pup-14 spectra. Prediction was evaluated using 100 bootstrap samples of 2 Latin-partitions (i.e., 50:50 split between training and prediction set) of the mice. The spectra without the outliers yielded classification rates of 99.1+/-0.1%, 90.1+/-0.8%, and 97.0+/-0.6% for adults, 14-day-old pups, and 7-day-old pups, respectively. At a 95% level of significance, 100 bootstrap samples disclosed 35 adult and 21 pup distinguishing peaks for separating adults from pups; and 8 14-day-old and 15 7-day-old predictive peaks for separating 14-day-old pup from 7-day-old pup spectra. A compressed matrix comprising 40,393 points that were outside the 95% confidence intervals of one of the two FuRES discriminants was evaluated and the classification improved significantly for all classes. When peaks that satisfied a quality criterion were integrated, the 55 integrated peak areas furnished significantly improved classification for all classes: the selected peak areas furnished classification rates of 100%, 97.3+/-0.6%, and 97.4+/-0.3% for adult, 14-day-old pups, and 7-day-old pups using 100 bootstrap Latin partitions evaluations with the predictions averaged. When the bootstrap size was increased to 1000 samples, the results were not significantly affected. The FuRES predictions were consistent with those obtained by discriminant partial least squares (DPLS) classifications.

  View details for DOI 10.1016/j.aca.2007.08.007

  View details for Web of Science ID 000250023000007

  View details for PubMedID 17870284

  View details for PubMedCentralID PMC2094725

• QuickSNP: an automated web server for selection of tagSNPs NUCLEIC ACIDS RESEARCH Grover, D., Woodfield, A. S., Verma, R., Zandi, P. P., Levinson, D. F., Potash, J. B. 2007; 35: W115-W120

  Abstract

  Although large-scale genetic association studies involving hundreds to thousands of SNPs have become feasible, the associated cost is substantial. Even with the increased efficiency introduced by the use of tagSNPs, researchers are often seeking ways to maximize resource utilization given a set of SNP-based gene-mapping goals. We have developed a web server named QuickSNP in order to provide cost-effective selection of SNPs, and to fill in some of the gaps in existing SNP selection tools. One useful feature of QuickSNP is the option to select only gene-centric SNPs from a chromosomal region in an automated fashion. Other useful features include automated selection of coding non-synonymous SNPs, SNP filtering based on inter-SNP distances and information regarding the availability of genotyping assays for SNPs and whether they are present on whole genome chips. The program produces user-friendly summary tables and results, and a link to a UCSC Genome Browser track illustrating the position of the selected tagSNPs in relation to genes and other genomic features. We hope the unique combination of features of this server will be useful for researchers aiming to select markers for their genotyping studies. The server is freely available and can be accessed at the URL http://bioinformoodics.jhmi.edu/quickSNP.pl.

  View details for DOI 10.1093/nar/gkm329

  View details for Web of Science ID 000255311500023

  View details for PubMedID 17517769

  View details for PubMedCentralID PMC1933212

• A comparison of the familiality of chronic depression in recurrent early-onset depression pedigrees using different definitions of chronicity JOURNAL OF AFFECTIVE DISORDERS Mondimore, F. M., Zandi, P. P., MacKinnon, D. F., McInnis, M. G., Miller, E. B., Schweizer, B., Crowe, R. P., Scheftner, W. A., Weissman, M. A., Levinson, D. F., DePaulo, J. R., Potash, J. B. 2007; 100 (1-3): 171-177

  Abstract

  The study of chronicity in the course of major depression has been complicated by varying definitions of this illness feature. Because familial clustering is one component of diagnostic validity we compared family clustering of chronicity as defined in the DSM-IV to that of chronicity determined by an assessment of lifetime course of depressive illness.In 1750 affected subjects from 652 families recruited for a genetic study of recurrent, early-onset depression, we applied several definitions of chronicity. Odds ratios were determined for the likelihood of chronicity in a proband predicting chronicity in an affected relative.There was greater family clustering of chronicity as determined by assessment of lifetime course (OR=2.54) than by DSM-IV defined chronic major depressive episode (MDE) (OR=1.93) or dysthymic disorder (OR=1.76). In families with probands who had preadolescent onset of MDD, familiality was increased by all definitions, with a much larger increase observed for chronicity by lifetime course (ORs were 6.14 for lifetime chronicity, 2.43 for chronic MDE, and 3.42 for comorbid dysthymic disorder). Agreement between these definitions of chronicity was only fair.The data used to determine chronicity were collected retrospectively and not blindly to relatives' status, and assessment of lifetime course was based on global clinical impressions gathered during a semi-structured diagnostic interview. Also, it can be difficult to determine whether individuals with recurrent major depressive episodes who frequently experience long periods of low grade depressive symptoms meet the strict timing requirements of DSM-IV dysthymic disorder.An assessment of lifetime symptom course identifies a more familial, and thus possibly a more valid, type of chronic depression than the current DSM-IV categories which are defined in terms of particular cross-sectional features of illness.

  View details for DOI 10.1016/j.jad.2006.10.011

  View details for Web of Science ID 000247704400021

  View details for PubMedID 17126912

  View details for PubMedCentralID PMC1950152

• Familiality of reproductive cycle associated mood symptoms in families with major depression and bipolar disorder 62nd Annual Meeting of the Society-of-Biological-Psychiatry Payne, J. L., Mondimore, F. M., Schweizer, B., MacKinnon, D. F., Zamoiski, R. B., McMahon, F. J., Levinson, D. F., Weissman, M. M., Numberger, J. I., Rice, J. P., Scheftner, W., Coryell, W., Berrettini, W. H., Kelsoe, J. R., Byerley, W., Gershon, E. S., Murphy-Eberenz, K., DePaulo, J. R., Potash, J. B. ELSEVIER SCIENCE INC. 2007: 8S–8S

  View details for Web of Science ID 000245698100023

• Data acquisition for meta-analysis of genome-wide linkage studies using the genome search meta-analysis method 34th European Mathematical Genetics Meeting Forabosco, P., Ng, M. Y., Bouzigon, E., Fisher, S. A., Levinson, D. F., Lewis, C. M. KARGER. 2007: 74–81

  Abstract

  The Genome Search Meta-Analysis (GSMA) method enables researchers to pool results across genome-wide linkage studies, to increase the power to detect linkage. Results from individual studies must be extracted, with the maximum evidence for linkage placed into bins, usually of 30 cM width, and ranked within the study. Ranks are then summed across studies, with high summed ranks potentially showing evidence for linkage in the meta-analysis.In this paper we study the properties of the GSMA method considering two different issues: (1) data binning from genome-wide results when indexed markers or graphs are available, based on either predefined boundary markers, or equal-length bins; (2) the use of selected instead of genome-wide results, using simulation to estimate power and type I error rates of GSMA. This is relevant when published papers show only summary results (e.g. with NPL score >1). Results: Using digitizing software to extract linkage statistics from graphs and assigning equal bin length is accurate, with the resulting ranking of bins similar to those defined through boundary markers. Simulation results show that power can fall substantially when genome-wide results are not available, particularly when only results from a single marker are available in a linked region. However there is no increase in false positive findings.The GSMA method is robust across different bin definitions and methods of data presentation and extraction. Using studies based on only the top ranked bins does not produce false positive results, but lacks power to detect genes conferring a modest increase in risk. Therefore, we advise that effort should be made to obtain genome-wide results from investigators or from published papers to avoid limiting the utility of the GSMA.

  View details for DOI 10.1159/000101425

  View details for Web of Science ID 000246211300008

  View details for PubMedID 17483599

• Reproductive cycle-associated mood symptoms in women with major depression and bipolar disorder JOURNAL OF AFFECTIVE DISORDERS Payne, J. L., Roy, P. S., Murphy-Eberenz, K., Weismann, M. M., Swartz, K. L., McInnis, M. G., Nwulia, E., Mondimore, F. M., MacKinnon, D. F., Miller, E. B., Nurnberger, J. I., Levinson, D. F., DePaulo, J. R., Potash, J. B. 2007; 99 (1-3): 221-229

  Abstract

  We sought to determine the prevalence of, and association between, reproductive cycle-associated mood symptoms in women with affective disorders. We hypothesized that symptoms would correlate with each other across a woman's reproductive life span in both major depression (MDD) and bipolar I disorder (BP).2412 women with, MDD or BP were asked standardized questions about mood symptoms prior to menstruation, within a month of childbirth and during perimenopause. Lifetime rates for each of these symptom types were determined and an odds ratio was calculated correlating each of the types with the others.Of 2524 women with mood disorders, 67.7% reported premenstrual symptoms. Of those at risk, 20.9% reported postpartum symptoms and 26.4% reported perimenopausal symptoms. The rates did not differ between women with MDD and BP but were significantly different from women who were never ill. The symptoms were significantly correlated in women with MDD with odds ratios from 1.66 to 1.82, but were not in women with BP.This is a secondary analysis of a sample that was collected for other purposes and is based upon retrospective reporting.Reproductive cycle-associated mood symptoms were commonly reported in women with mood disorders and did not differ based on diagnosis. In MDD, but not BP, the occurrence of these symptoms was trait-like as the presence of one predicted the occurrence of the others. Further prospective study is required to clarify the determinants of this trait.

  View details for DOI 10.1016/j.jad.2006.08.013

  View details for Web of Science ID 000245154300027

  View details for PubMedID 17011632

• A genome-wide scan for schizophrenia and psychosis susceptibility loci in families of Mexican and Central American ancestry AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Escamilla, M. A., Ontiveros, A., Nicolini, H., Raventos, H., Mendoza, R., Medina, R., MUNOZ, R., Levinson, D., Peralta, J. M., Dassori, A., Almasy, L. 2007; 144B (2): 193-199

  Abstract

  Schizophrenia is a complex psychiatric disorder, likely to be caused in part by multiple genes. In this study, linkage analyses were performed to identify chromosomal regions most likely to be associated with schizophrenia and psychosis in multiplex families of Mexican and Central American origin. Four hundred and fifty-nine individuals from 99 families, containing at least two siblings with hospital diagnoses of schizophrenia or schizoaffective disorder, were genotyped. Four hundred and four microsatellite markers were genotyped for all individuals and multipoint non-parametric linkage analyses were performed using broad (any psychosis) and narrow (schizophrenia and schizoaffective disorder) models. Under the broad model, three chromosomal regions (1pter-p36, 5q35, and 18p11) exhibited evidence of linkage with non-parametric lod (NPL) scores greater than 2.7 (equivalent to empirical P values of less than 0.001) with the peak multipoint NPL = 3.42 (empirical P value = 0.00003), meeting genomewide evidence for significant linkage in the 1pter-p36 region. Under the narrow model, the same three loci showed (non-significant) evidence of linkage. These linkage findings (1pter-p36, 18p11, and 5q35) highlight where genes for psychosis and schizophrenia are most likely to be found in persons of Mexican and Central American ancestry, and correspond to recent linkages of schizophrenia or psychosis in other populations which were formed in part from emigrants from the Spanish empire of the 15th and 16th centuries.

  View details for DOI 10.1002/ajmg.b.30411

  View details for Web of Science ID 000244729000006

  View details for PubMedID 17044102

• Genetics of recurrent early-onset major depression (GenRED): Significant linkage on chromosome 15q25-q26 after fine mapping with single nucleotide polymorphism markers AMERICAN JOURNAL OF PSYCHIATRY Levinson, D. F., Evgrafov, O. V., Knowles, J. A., Potash, J. B., Weissman, M. M., Scheftner, W. A., DePaulo, J. R., Crowe, R. R., Murphy-Eberenz, K., Marta, D. H., McInnis, M. G., Adams, P., Gladis, M., Miller, E. B., Thomas, J., Holmans, P. 2007; 164 (2): 259-264

  Abstract

  The authors studied a dense map of single nucleotide polymorphism (SNP) DNA markers on chromosome 15q25-q26 to maximize the informativeness of genetic linkage analyses in a region where they previously reported suggestive evidence for linkage of recurrent early-onset major depressive disorder.In 631 European-ancestry families with multiple cases of recurrent early-onset major depressive disorder, 88 SNPs were genotyped, and multipoint allele-sharing linkage analyses were carried out. Marker-marker linkage disequilibrium was minimized, and a simulation study with founder haplotypes from these families suggested that linkage scores were not inflated by linkage disequilibrium.The dense SNP map increased the information content of the analysis from around 0.7 to over 0.9. The maximum evidence for linkage was the Z likelihood ratio score statistic of Kong and Cox (Z(LR))=4.69 at 109.8 cM. The exact p value was below the genomewide significance threshold. By contrast, in the genome scan with microsatellite markers at 9 cM spacing, the maximum Z(LR) for European-ancestry families was 3.43 (106.53 cM). It was estimated that the linked locus or loci in this region might account for a 20% or less populationwide increase in risk to siblings of cases.This region has produced modestly positive evidence for linkage to depression and related traits in other studies. These results suggest that DNA sequence variations in one or more genes in the 15q25-q26 region can increase susceptibility to major depression and that efforts are warranted to identify these genes.

  View details for PubMedID 17267788

• Genetics of recurrent early-onset major depression (GenRED): Final genome scan report AMERICAN JOURNAL OF PSYCHIATRY Holmans, P., Weissman, M. M., Zubenko, G. S., Scheftner, W. A., Crowe, R. R., DePaulo, J. R., Knowles, J. A., Zubenko, W. N., Murphy-Eberenz, K., Marta, D. H., Boutelle, S., McInnis, M. G., Adams, P., Gladis, M., Steele, J., Miller, E. B., Potash, J. B., MacKinnon, D. F., Levinson, D. F. 2007; 164 (2): 248-258

  Abstract

  The authors carried out a genomewide linkage scan to identify chromosomal regions likely to contain genes that contribute to susceptibility to recurrent early-onset major depressive disorder, the form of the disorder with the greatest reported risk to relatives of index cases.Microsatellite DNA markers were studied in 656 families with two or more such cases (onset before age 31 in probands and age 41 in other relatives), including 1,494 informative "all possible" affected relative pairs (there were 894 independent affected sibling pairs). Analyses included a primary multipoint allele-sharing analysis (with ALLEGRO) and a secondary logistic regression analysis taking the sex of each relative pair into account (male-male, male-female, female-female).Genomewide suggestive evidence for linkage was observed on chromosome 15q25-q26 (at 105.4 centimorgans [cM]). The authors previously reported genomewide significant linkage in this region in the first 297 families. In the secondary analysis, after empirical genomewide correction for multiple testing, suggestive linkage results were observed on chromosome 17p12 (28.0 cM, excess sharing in male-male and male-female pairs) and on chromosome 8p22-p21.3 (25.1 cM, excess sharing in male-male pairs).These regions of chromosomes 15q, 17p, and 8p might contain genes that contribute to susceptibility to major depression and related disorders. Evidence for linkage has been reported independently in the same regions of chromosome 15q for major depression and of chromosome 8p for related personality traits.

  View details for PubMedID 17267787

• Statistical corrections of linkage data suggest predominantly cis regulations of gene expression. BMC proceedings Shi, J., Siegmund, D. O., Levinson, D. F. 2007; 1: S145-?

  Abstract

  Morley et al. (Nature 2004, 430:743-747) detected significant linkages to the expression levels of 142 genes (of 3554) at a reported threshold of genome-wide p = 0.001 (LOD asymptotically equal to 5.3), using 14 three-generation Centre d'Etude du Polymorphisme Humain pedigrees. Most of the linkages (77%) were trans, i.e., more than 5 Mb from the expressed gene. However, the analysis did not account for the expected anti-conservative effect of the skewed distribution of score- or regression-based statistics in large sibships, or for the possible variance distortion due to correlations among tests. Therefore, we re-analyzed their data, using a robust score statistic for the entire pedigrees and correcting the p-values for skewness. We found that a LOD of 5.3 had a skewness-corrected genome-wide p-value of 0.016 instead of 0.001 (a result that we confirmed using simulation), with around 50 expected false positives. We then further corrected for correlation among the (skew-corrected) p-values by using Efron's method for obtaining the empirical null distribution. Setting a threshold of FDR = 10% (Z = 6.4, LOD = 8.9), we detected linkage for the expression levels of 22 genes, 19 of which are cis. Limiting the analysis to cis regions, linkage was detected to the expression levels of 46 genes with 4.6 expected false positives (FDR = 10%).

  View details for PubMedID 18466489

• Genomewide SNP linkage scan of schizophrenia in a large multicenter sample 14th World Congress on Psychiatric Genetics Levinson, D., Gejman, P. V., Laurent, C., Owen, M. J., Pulver, A. E., Riley, B., Wildenauer, D. B., Kendler, K. S., Mallet, J., Mowry, B. J., Nestadt, G., O'Donovan, M., Sanders, A. R., Schwab, S. G., Williams, N., Albus, M., Bauche, S., deMarchi, N., Dikeos, D., Duan, J., Jay, M., Lasseter, V. K., Lerer, F. B., Maier, W., Nertney, D. A., Nikolov, I., Norton, N., O'Neill, A., Papadimitriou, G., Segurado, R., Silverman, J. M., Walsh, D., Williams, H., Holmans, P. A. WILEY-BLACKWELL. 2006: 697–97

  View details for Web of Science ID 000240877700057

• Genome-wide search for linkage interactions in schizophrenia Shi, J., Gejman, P. V., Levinson, D. F. WILEY-LISS. 2006: 806

  View details for Web of Science ID 000240877700540

• Significant linkage of major depression on 15q25-q26 after SNP fine-mapping 14th World Congress on Psychiatric Genetics Levinson, D., Evgrafov, O., Knowles, J. A., Potash, J. B., Weissman, M. M., Scheftner, W. A., Raymond, R., DePaulo, J., Crowe, R. R., Murphy-Eberenz, K., Marta, D. H., McInnis, M. G., Adams, P., Gladis, M., Miller, E. B., Thomas, J., Holmans, P. A. WILEY-BLACKWELL. 2006: 694–94

  View details for Web of Science ID 000240877700043

• Comprehensive linkage disequilibrium mapping of schizophrenia candidate genes in a large European-ancestry sample 14th World Congress on Psychiatric Genetics GEJMAN, P. V., Duan, J., Martinez, M., Sanders, A. R., Burrell, G., Hou, C., He, D., Schwartz, D., Buccola, N. G., Mowry, B. J., Freedman, R., Amin, F., Black, D. W., Silverman, J. M., Byerley, W. F., Crowe, R. R., Cloninger, C. R., Levinson, D. F. WILEY-BLACKWELL. 2006: 689–89

  View details for Web of Science ID 000240877700025

• Familial aggregation of illness chronicity in recurrent, early-onset major depression pedigrees AMERICAN JOURNAL OF PSYCHIATRY Mondimore, F. M., Zandi, P. P., MacKinnon, D. F., McInnis, M. G., Miller, E. B., Crowe, R. P., Scheftner, W. A., Marta, D. H., Weissman, M. M., Levinson, D. F., Murphy-Ebenez, K. P., DePaulo, J. R., Potash, J. B. 2006; 163 (9): 1554-1560

  Abstract

  The authors used a large sample collected for genetic studies to determine whether a chronic course of illness defines a familial clinical subtype in major depressive disorder.A measure of lifetime chronicity of depressive symptoms (substantial mood symptoms most or all of the time) was tested for familial aggregation in 638 pedigrees from the Genetics of Recurrent Early-Onset Depression (GenRED) project.In subjects with chronic depression, the mean age at illness onset was lower and rates of attempted suicide, panic disorder, and substance abuse were higher than among those with nonchronic depression. Chronicity was assessed in 37.8% of affected first-degree relatives of probands with chronic depression and in 20.2% of relatives of probands with nonchronic depression. Analysis using the generalized estimating equation model yielded an odds ratio of 2.52 (SE=0.39, z=6.02, p<0.0001) for the likelihood of chronicity in a proband predicting chronicity in an affected relative. With stratification by proband age at illness onset, the odds ratio for chronicity in relatives by proband chronicity status was 6.17 (SE=2.09, z=5.35, p<0.0001) in families of probands whose illness onset was before age 13 and 1.92 (SE=0.34, z=3.72, p<0.0001) in families of probands whose illness started at age 13 or later.These findings suggest that chronicity of depressive symptoms is familial, especially in preadolescent-onset illness. Chronicity is also associated with other indicators of illness severity in recurrent, early-onset major depression. Further study using chronicity as a subtype in the genetic analysis of depressive illness is warranted. Refinement of the definition of chronicity in depressive illness may increase the power of such studies.

  View details for Web of Science ID 000240205100015

  View details for PubMedID 16946180

• Linkage disequilibrium analyses in the Costa Rican population suggests discrete gene loci for schizophrenia at 8p23.1 and 8q13.3 PSYCHIATRIC GENETICS Walss-Bass, C., Montero, A. P., Armas, R., Dassori, A., Contreras, S. A., Liu, W., Medina, R., Levinson, D., Pereira, M., Atmella, I., NeSmith, L., Leach, R., Almasy, L., Raventos, H., Escamilla, M. A. 2006; 16 (4): 159-168

  Abstract

  Linkage studies using multiplex families have repeatedly implicated chromosome 8 as involved in schizophrenia etiology. The reported areas of linkage, however, span a wide chromosomal region. The present study used the founder population of the Central Valley of Costa Rica and phenotyping strategies alternative to DSM-IV classifications in attempts to further delimitate the areas on chromosome 8 that may harbor schizophrenia susceptibility genes. A linkage disequilibrium screen of chromosome 8 was performed using family trios of individuals with a history of psychosis. Four discrete regions showing evidence of association (nominal P values less than 0.05) to the phenotype of schizophrenia were identified: 8p23.1, 8p21.3, 8q13.3 and 8q24.3. The region of 8p23.1 precisely overlaps a region showing strong evidence of linkage disequilibrium for severe bipolar disorder in Costa Rica. The same chromosomal regions were identified when the broader phenotype definition of all individuals with functional psychosis was used for analyses. Stratification of the psychotic sample by history of mania suggests that the 8q13.3 locus may be preferentially associated with non-manic psychosis. These results may be helpful in targeting specific areas to be analyzed in association-based or linkage disequilibrium-based studies, for researchers who have found evidence of linkage to schizophrenia on chromosome 8 within their previous studies.

  View details for Web of Science ID 000239474900005

  View details for PubMedID 16829783

• Association study of the dystrobrevin-binding gene with schizophrenia in Australian and Indian samples TWIN RESEARCH AND HUMAN GENETICS Holliday, E. G., Handoko, H. Y., James, M. R., McGrath, J. J., Nertney, D. A., Tirupati, S., Thara, R., Levinson, D. F., Hayward, N. K., Mowry, B. J., Nyholt, D. R. 2006; 9 (4): 531-539

  Abstract

  Numerous studies have reported association between variants in the dystrobrevin binding protein 1 (dysbindin) gene (DTNBP1) and schizophrenia. However, the pattern of results is complex and to date, no specific risk marker or haplotype has been consistently identified. The number of single nucleotide polymorphisms (SNPs) tested in these studies has ranged from 5 to 20. We attempted to replicate previous findings by testing 16 SNPs in samples of 41 Australian pedigrees, 194 Australian cases and 180 controls, and 197 Indian pedigrees. No globally significant evidence for association was observed in any sample, despite power calculations indicating sufficient power to replicate several previous findings. Possible explanations for our results include sample differences in background linkage disequilibrium and/or risk allele effect size, the presence of multiple risk alleles upon different haplotypes, or the presence of a single risk allele upon multiple haplotypes. Some previous associations may also represent false positives. Examination of Caucasian HapMap phase II genotype data spanning the DTNBP1 region indicates upwards of 40 SNPs are required to satisfactorily assess all nonredundant variation within DTNBP1 and its potential regulatory regions for association with schizophrenia. More comprehensive studies in multiple samples will be required to determine whether specific DTNBP1 variants function as risk factors for schizophrenia.

  View details for Web of Science ID 000240538800007

  View details for PubMedID 16899160

• The genetics of depression: A review BIOLOGICAL PSYCHIATRY Levinson, D. F. 2006; 60 (2): 84-92

  Abstract

  Major depressive disorder (MDD) is common and moderately heritable. Recurrence and early age at onset characterize cases with the greatest familial risk. Major depressive disorder and the neuroticism personality trait have overlapping genetic susceptibilities. Most genetic studies of MDD have considered a small set of functional polymorphisms relevant to monoaminergic neurotransmission. Meta-analyses suggest small positive associations between the polymorphism in the serotonin transporter promoter region (5-HTTLPR) and bipolar disorder, suicidal behavior, and depression-related personality traits but not yet to MDD itself. This polymorphism might also influence traits related to stress vulnerability. Newer hypotheses of depression neurobiology suggest closer study of genes related to neurotoxic and neuroprotective (neurotrophic) processes and to overactivation of the hypothalamic-pituitary axis, with mixed evidence regarding association of MDD with polymorphisms in one such gene (brain-derived neurotrophic factor [BDNF]). Several genome-wide linkage studies of MDD and related traits have been reported or are near completion. There is some evidence for convergence of linkage findings across studies, but more data are needed to permit meta-analysis. Future directions will include more intensive, systematic study of linkage candidate regions and of the whole genome for genetic association; gene expression array studies; and larger-scale studies of gene-environment interactions and of depression-related endophenotypes.

  View details for DOI 10.1016/j.biopsych.2005.08.024

  View details for Web of Science ID 000239101300002

  View details for PubMedID 16300747

• Genetics of schizophrenia: Progress and caveats 25th Congress of the Collegium-Internationale-Neuro-Psychopharmacologicum (CINP)/29th Annual Meeting of the Canadian-College-of-Neuropsychopharmacology GEJMAN, P. V., Duan, J., Sanders, A. R., Hou, C., Burrel, G., Buccola, N. G., Mowry, B. J., Amin, F., Silverman, J. M., Black, D. W., Byerley, W. F., Freedman, R., Cloninger, C. R., Levinson, D. F., Martinez, M. CAMBRIDGE UNIV PRESS. 2006: S28–S28

  View details for Web of Science ID 000239495500106

• Testing for genetic heterogeneity in the genome search meta-analysis method GENETIC EPIDEMIOLOGY Lewis, C. M., Levinson, D. E. 2006; 30 (4): 348–55

  Abstract

  The Genome Search Meta-Analysis (GSMA) method is widely used to detect linkage by pooling results of previously published genome-wide linkage studies. The GSMA uses a non-parametric summed rank statistic in 30 cM bins of the genome. Zintzaras and Ioannidis ([2005] Genet. Epidemiol. 28:123-137) developed a method of testing for heterogeneity of evidence for linkage in the GSMA, with three heterogeneity statistics (Q, Ha, B). They implement two testing procedures, restricted versus unrestricted for the summed rank within the bin. We show here that the rank-unrestricted test provides a conservative test for high heterogeneity and liberal test for low heterogeneity in linked regions. The rank-restricted test should therefore be used, despite the extensive simulations needed. In a simulation study, we show that the power to detect heterogeneity is low. For 20 studies of affected sib pairs, simulated assuming linkage in all studies to a gene with sibling relative risk of 1.3, the power to detect low heterogeneity using the Q statistic was 14%. With linkage present in 50% of the studies (to a gene with sibling relative risk of 1.4), the Q heterogeneity statistic had power of 29% to detect high heterogeneity. The power to detect linkage using the summed rank was high in both of these situations, at 98% and 79%, respectively. Although testing for heterogeneity in the GSMA is of interest, the currently available method provides little additional information to that provided by the summed rank statistic.

  View details for DOI 10.1002/gepi.20149

  View details for Web of Science ID 000237163200007

  View details for PubMedID 16586403

• Association analyses of the neuregulin 1 gene with schizophrenia and manic psychosis in a Hispanic population ACTA PSYCHIATRICA SCANDINAVICA Walss-Bass, C., Raventos, H., Monter, A. P., Armas, R., Dassori, A., Contreras, S., Liu, W., Medina, R., Levinson, D. F., PEREIRA, M., Leach, R. J., Almasy, L., Escamilla, M. A. 2006; 113 (4): 314-321

  Abstract

  This study used the population of the Central Valley of Costa Rica (CVCR) and phenotyping strategies alternative to DSMIV classifications to investigate the association of neuregulin 1 with schizophrenia.Using 134 family trios with a history of psychosis, we genotyped six of the seven markers originally identified to be associated with schizophrenia in Iceland.The neuregulin Icelandic haplotype was not associated with schizophrenia in the CVCR population. However, a novel haplotype was found to be overrepresented in subjects with functional psychosis (global P-value > 0.05). Stratification of the sample by history of mania suggests that this haplotype may be preferentially over-transmitted to persons with a history of manic psychosis.These results suggest that the neuregulin 1 gene is unlikely to play a major role in predisposing to schizophrenia in the CVCR. Further studies in the CVCR and other Latin American populations should be performed in order to corroborate these findings.

  View details for DOI 10.1111/j.1600-0447.2005.00631.x

  View details for Web of Science ID 000236474800009

  View details for PubMedID 16638076

• Genomewide linkage scan of 409 European-ancestry and African American families with schizophrenia: Suggestive evidence of linkage at 8p23.3-p21.2 and 11p13.1-q14.1 in the combined sample AMERICAN JOURNAL OF HUMAN GENETICS Suarez, B. K., Duan, J. B., Sanders, A. R., Hinrichs, A. L., Jin, C. H., Hou, C. P., Buccola, N. G., Hale, N., Weilbaecher, A. N., Nertney, D. A., Olincy, A., Green, S., Schaffer, A. W., Smith, C. J., Hannah, D. E., RICE, J. P., Cox, N. J., Martinez, M., Mowry, B. J., Amin, F., Silverman, J. M., Black, D. W., Byerley, W. F., Crowe, R. R., Freedman, R., Cloninger, C. R., Levinson, D. F., Gejman, P. V. 2006; 78 (2): 315-333

  Abstract

  We report the clinical characteristics of a schizophrenia sample of 409 pedigrees--263 of European ancestry (EA) and 146 of African American ancestry (AA)--together with the results of a genome scan (with a simple tandem repeat polymorphism interval of 9 cM) and follow-up fine mapping. A family was required to have a proband with schizophrenia (SZ) and one or more siblings of the proband with SZ or schizoaffective disorder. Linkage analyses included 403 independent full-sibling affected sibling pairs (ASPs) (279 EA and 124 AA) and 100 all-possible half-sibling ASPs (15 EA and 85 AA). Nonparametric multipoint linkage analysis of all families detected two regions with suggestive evidence of linkage at 8p23.3-q12 and 11p11.2-q22.3 (empirical Z likelihood-ratio score [Z(lr)] threshold >/=2.65) and, in exploratory analyses, two other regions at 4p16.1-p15.32 in AA families and at 5p14.3-q11.2 in EA families. The most significant linkage peak was in chromosome 8p; its signal was mainly driven by the EA families. Z(lr) scores >2.0 in 8p were observed from 30.7 cM to 61.7 cM (Center for Inherited Disease Research map locations). The maximum evidence in the full sample was a multipoint Z(lr) of 3.25 (equivalent Kong-Cox LOD of 2.30) near D8S1771 (at 52 cM); there appeared to be two peaks, both telomeric to neuregulin 1 (NRG1). There is a paracentric inversion common in EA individuals within this region, the effect of which on the linkage evidence remains unknown in this and in other previously analyzed samples. Fine mapping of 8p did not significantly alter the significance or length of the peak. We also performed fine mapping of 4p16.3-p15.2, 5p15.2-q13.3, 10p15.3-p14, 10q25.3-q26.3, and 11p13-q23.3. The highest increase in Z(lr) scores was observed for 5p14.1-q12.1, where the maximum Z(lr) increased from 2.77 initially to 3.80 after fine mapping in the EA families.

  View details for Web of Science ID 000236744900012

  View details for PubMedID 16400611

• Is perinatal depression familial? JOURNAL OF AFFECTIVE DISORDERS Murphy-Eberenz, K., Zandi, P. P., March, D., Crowe, R. R., Scheftner, W. A., Alexander, M., McInnis, M. G., Coryell, W., Adams, P., DePaulo, J. R., Miller, E. B., Marta, D. H., Potash, J. B., PAYNE, J., Levison, D. F. 2006; 90 (1): 49-55

  Abstract

  While major depressive disorder (MDD) is familial, it is not clear whether distinct familial-genetic factors influence vulnerability to depression during or after pregnancy. Here we examine familial aggregation of perinatal major depression (PND, any episode during pregnancy or the month after childbirth) and the subset of post-partum depression (PPD) in families with multiple cases of recurrent, early-onset MDD from the Genetics of Recurrent Early-Onset Depression dataset.The dataset included 691 childbearing women who could be classified as PND (27.6%) or non-PND (NPND), of whom 328 were members of 148 sibships with two or more PND or NPND women. PND and NPND subjects were compared for differences in putative predictors. Prediction of sibling PND or PPD by the proband's history was examined using logistic regression and general estimating equation methods.PND was associated with fewer episodes and younger current age. Odds ratios for prediction of sibling status were significant for PND (2.28) and PPD (3.96), particularly when current age was under 46 (2.87 and 4.39, respectively). ORs for PPD were not significantly different from those for PND. The OR for PPD (3.52), but not for PND, remained significant after current age was introduced as a covariate, but not when both current age and number of episodes were included in the model.Because detailed data were not collected for all pregnancies, we cannot determine whether current age and number of episodes mediated the observed effects due to recall bias or other factors (cohort effect, number of episodes).A familial component to PND, and particularly PPD, is suggested by the results. However more systematic study is needed to confirm this result. A greater understanding of both genetic and non-genetic familial factors could lead to improved prevention and clinical management.

  View details for DOI 10.1016/j.jad.2005.10.006

  View details for Web of Science ID 000234931100008

  View details for PubMedID 16337009

• The effect of linkage disequilibrium on linkage analysis of incomplete pedigrees 14th Genetic Analysis Workshop Levinson, D. F., Holmans, P. BIOMED CENTRAL LTD. 2005

  Abstract

  Dense SNP maps can be highly informative for linkage studies. But when parental genotypes are missing, multipoint linkage scores can be inflated in regions with substantial marker-marker linkage disequilibrium (LD). Such regions were observed in the Affymetrix SNP genotypes for the Genetic Analysis Workshop 14 (GAW14) Collaborative Study on the Genetics of Alcoholism (COGA) dataset, providing an opportunity to test a novel simulation strategy for studying this problem. First, an inheritance vector (with or without linkage present) is simulated for each replicate, i.e., locations of recombinations and transmission of parental chromosomes are determined for each meiosis. Then, two sets of founder haplotypes are superimposed onto the inheritance vector: one set that is inferred from the actual data and which contains the pattern of LD; and one set created by randomly selecting parental alleles based on the known allele frequencies, with no correlation (LD) between markers. Applying this strategy to a map of 176 SNPs (66 Mb of chromosome 7) for 100 replicates of 116 sibling pairs, significant inflation of multipoint linkage scores was observed in regions of high LD when parental genotypes were set to missing, with no linkage present. Similar inflation was observed in analyses of the COGA data for these affected sib pairs with parental genotypes set to missing, but not after reducing the marker map until r2 between any pair of markers was

  View details for DOI 10.1186/1471-2156-6-S1-S6

  View details for Web of Science ID 000236103400006

  View details for PubMedID 16451672

• GSMA: software implementation of the genome search meta-analysis method BIOINFORMATICS Pardi, F., Levinson, D. F., Lewis, C. M. 2005; 21 (24): 4430-4431

  Abstract

  Meta-analysis can be used to pool results of genome-wide linkage scans. This is of great value in complex diseases, where replication of linked regions occurs infrequently. The genome search meta-analysis (GSMA) method is widely used for this analysis, and a computer program is now available to implement the GSMA.

  View details for DOI 10.1093/bioinformatics/bti725

  View details for Web of Science ID 000233849400022

  View details for PubMedID 16249265

• Evidence of genetic overlap of schizophrenia and bipolar disorder: Linkage disequilibrium analysis of chromosome 18 in the Costa Rican population AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Walss-Bass, C., Escamilla, M. A., Raventos, H., Montero, A. P., Armas, R., Dassori, A., Contreras, S., Liu, W., Medina, R., Balderas, T. G., Levinson, D., Pereira, R., PEREIRA, M., Atmella, I., NeSmith, L., Leach, R., Almasy, L. 2005; 139B (1): 54-60

  Abstract

  The long-standing concept that schizophrenia (SC) and bipolar disorder (BP) represent two distinct illnesses has been recently challenged by findings of overlap of genetic susceptibility loci for these two diseases. We report here the results of a linkage disequilibrium (LD) analysis of chromosome 18 utilizing subjects with SC from the Central Valley of Costa Rica. Evidence of association (P < 0.05) was obtained in three chromosomal regions: 18p11.31 (D18S63), 18q12.3 (D18S474), and 18q22.3-qter (D18S1161, D18S70), all of which overlap or are in close proximity with loci previously shown to be in LD with BP, type I in this population. Since both the SC and bipolar samples contained cases with a history of mania and almost all cases of SC and BP had a history of psychosis, we performed an alternative phenotyping strategy to determine whether presence or absence of mania, in the context of psychosis, would yield distinct linkage patterns along chromosome 18. To address this issue, a cohort of psychotic patients (including a range of DSMIV diagnoses) was divided into two groups based on the presence or absence of mania. Regions that showed association with SC showed segregation of association when the sample was stratified by history of mania. Our results are compared with previous genetic studies of susceptibility to SC or BP, in Costa Rica as well as in other populations. This study illustrates the importance of detailed phenotype analysis in the search for susceptibility genes influencing complex psychiatric disorders in isolated populations and suggests that subdivision of psychoses by presence or absence of past mania syndromes may be useful to define genetic subtypes of chronic psychotic illness.

  View details for DOI 10.1002/ajmg.b.30207

  View details for Web of Science ID 000232958500013

  View details for PubMedID 16152570

• Direct profiling of the cerebellum by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry: A methodological study in postnatal and adult mouse JOURNAL OF NEUROSCIENCE RESEARCH Laurent, C., Levinson, D. F., Schwartz, S. A., Harrington, P. B., Markey, S. P., CAPRIOLI, R. M., Levitt, P. 2005; 81 (5): 613-621

  Abstract

  Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI MS) can detect substantial changes in expression of proteins in tissues, such as cancer cells. A more challenging problem is detecting the smaller changes expected in normal development or complex diseases. Here we address methodological issues regarding the acquisition and analysis of MALDI MS data from tissue sections, in a study of mouse cerebellum at different stages of development. Sections of the cerebellar cortex were analyzed at the peak of granule neuron production [postnatal day (P) 7], during synapse formation (P14), and in adults. Data were acquired (Voyager-DEtrade mark STR Biospectrometry Workstation; seven acquisitions of 50 shots per section, 3.5-50 kDa), preprocessed (Data Explorer 4.3), and averaged. Among 846 peaks detected, in at least 50% of at least one group, 122 showed significant group differences (Kruskal-Wallis ANOVA) after Bonferroni correction. Factor analyses revealed two age-related factors, possibly reflecting gradients of expression during development. Predictive analysis of microarrays generated a model from half of the sample that correctly predicted developmental groups for the second half. Intraclass correlation coefficients, measuring within-mouse consistency of peak heights from three tissue sections, were acceptable at lower m/z and for larger peaks at higher m/z. Low mass was the best predictor of significant group differences. The analysis demonstrates that MALDI MS of normal tissue sections at different ages can detect consistent, significant group differences. Further work is needed to increase the sensitivity of the methods and to apply them reliably to brain regions and to subproteomes with relevance to diverse brain functions and diseases.

  View details for DOI 10.1002/jnr.20590

  View details for Web of Science ID 000231580500002

  View details for PubMedID 16035104

• Lithium and valproic acid treatments reduce PKC activation and receptor-G protein coupling in platelets of bipolar manic patients JOURNAL OF PSYCHIATRIC RESEARCH Hahn, C. G., Umapathy, Wang, H. Y., Koneru, R., Levinson, D. F., Friedman, E. 2005; 39 (4): 355-363

  Abstract

  Dysregulated protein kinase C (PKC) distribution and activation, and abnormal receptor-G protein coupling, have been implicated in the pathophysiology of bipolar affective disorder (BD). The therapeutic effectiveness of lithium has also been correlated with its ability to reduce PKC activation and G protein-mediated signaling. We examine the cellular distribution and activation of PKC and receptor-G protein coupling in blood platelets from normal controls, patients with BD mania or schizophrenia during treatment-free state, and after lithium or valproic acid administration. PKC activity was measured under basal and 50 nM phorbol 12-myristate, 13-acetate (PMA), 1 microM serotonin or 0.5 U/ml thrombin-stimulated conditions. The coupling of G proteins to serotonin or thrombin receptors were assessed by serotonin or thrombin-mediated [35S]GTPgammaS binding to membrane Galpha proteins. The results demonstrate that membrane-associated PKC activity and stimulus-induced PKC translocation are increased in BD manic, whereas stimulus-elicited PKC translocation is attenuated in schizophrenic patients. Lithium and valproic acid treatments attenuated the stimulus-induced PKC translocations to a similar degree and decreased PKC activity in both cytosolic and membranous fractions after two weeks of drug administration. An increase in 5-HT or thrombin stimulated [35S]GTPgammaS binding to Galpha proteins was detected in BD manic but not in schizophrenic patients although basal [35S]GTPgammaS binding was not different across the diagnostic groups. Lithium and valproic acid treatments similarly reduced receptor-G protein coupling with comparable time courses. Thus, increased membrane-associated PKC, cytosol to membrane PKC translocation and receptor-G protein coupling in platelets of BD manic patients were alleviated by lithium or valproic acid treatments.

  View details for DOI 10.1016/j.jpsychires.2004.10.007

  View details for Web of Science ID 000230295900003

  View details for PubMedID 16044535

• Meta-analysis in psychiatric genetics. Current psychiatry reports Levinson, D. F. 2005; 7 (2): 143-151

  Abstract

  The article reviews literature on methods for meta-analysis of genetic linkage and association studies, and summarizes and comments on specific meta-analysis findings for psychiatric disorders. The Genome Scan Meta-Analysis and Multiple Scan Probability methods assess the evidence for linkage across studies. Multiple Scan Probability analysis suggested linkage of two chromosomal regions (13q and 22q) to schizophrenia and bipolar disorder, whereas Genome Scan Meta-Analysis on a larger sample identified at least 10 schizophrenia linkage regions, but none for bipolar disorder. Meta-analyses of pooled ORs support association of schizophrenia to the Ser311Cys polymorphism in DRD2 and the T102C polymorphism in HTR2A, and of attention deficit hyperactivity disorder to the 48-bp repeat in DRD4. The 5-HTTLPR polymorphism in the serotonin transporter gene (SLC6A4) may contribute to the risk of bipolar disorder, suicidal behavior, and neuroticism, but association to the lifetime risk of major depression has not been shown. Meta-analyses support linkage of schizophrenia to regions where replicable associations to candidate genes have been identified through positional cloning methods. There are additional supported regions where susceptibility genes are likely to be identified. Linkage meta-analysis has had less clear success for bipolar disorder based on a smaller dataset. Meta-analysis can guide the prioritization of regions for study, but proof of association requires biological confirmation of hypotheses about gene actions. Elucidation of causal mechanisms will require more comprehensive study of sequence variation in candidate genes, better statistical and meta-analytic methods to take all variation into account, and biological strategies for testing etiologic hypotheses.

  View details for PubMedID 15802092

• Comparison of single-nucleotide polymorphisms and microsatellite markers for linkage analysis in the COGA and simulated data sets for genetic analysis workshop 14: Presentation groups 1, 2, and 3 14th Genetic Analysis Workshop Wilcox, M. A., Pugh, E. W., Zhang, H. P., Zhong, X. Y., Levinson, D. E., Kennedys, G. C., Wijsman, E. M. WILEY-LISS. 2005: S7–S28

  Abstract

  The papers in presentation groups 1-3 of Genetic Analysis Workshop 14 (GAW14) compared microsatellite (MS) markers and single-nucleotide polymorphism (SNP) markers for a variety of factors, using multiple methods in both data sets provided to GAW participants. Group 1 focused on data provided from the Collaborative Study on the Genetics of Alcoholism (COGA). Group 2 focused on data simulated for the workshop. Group 3 contained analyses of both data sets. Issues examined included: information content, signal strength, localization of the signal, use of haplotype blocks, population structure, power, type I error, control of type I error, the effect of linkage disequilibrium, and computational challenges. There were several broad resulting observations. 1) Information content was higher for dense SNP marker panels than for MS panels, and dense SNP markers sets appeared to provide slightly higher linkage scores and slightly higher power to detect linkage than MS markers. 2) Dense SNP panels also gave higher type I errors, suggesting that increased test thresholds may be needed to maintain the correct error rate. 3) Dense SNP panels provided better trait localization, but only in the COGA data, in which the MS markers were relatively loosely spaced. 4) The strength of linkage signals did not vary with the density of SNP panels, once the marker density was approximately 1 SNP/cM. 5) Analyses with SNPs were computationally challenging, and identified areas where improvements in analysis tools will be necessary to make analysis practical for widespread use.

  View details for DOI 10.1002/gepi.20106

  View details for Web of Science ID 000234502000002

  View details for PubMedID 16342186

• Polymorphisms in the trace amine receptor 4 (TRAR4) gene on chromosome 6q23.2 are associated with susceptibility to schizophrenia AMERICAN JOURNAL OF HUMAN GENETICS Duan, J. B., Martinez, M., Sanders, A. R., Hou, C. P., Saitou, N., Kitano, T., Mowry, B. J., Crowe, R. R., Silverman, J. M., Levinson, D. F., Gejman, P. V. 2004; 75 (4): 624-638

  Abstract

  Several linkage studies across multiple population groups provide convergent support for a susceptibility locus for schizophrenia--and, more recently, for bipolar disorder--on chromosome 6q13-q26. We genotyped 192 European-ancestry and African American (AA) pedigrees with schizophrenia from samples that previously showed linkage evidence to 6q13-q26, focusing on the MOXD1-STX7-TRARs gene cluster at 6q23.2, which contains a number of prime candidate genes for schizophrenia. Thirty-one screening single-nucleotide polymorphisms (SNPs) were selected, providing a minimum coverage of at least 1 SNP/20 kb. The association observed with rs4305745 (P=.0014) within the TRAR4 (trace amine receptor 4) gene remained significant after correction for multiple testing. Evidence for association was proportionally stronger in the smaller AA sample. We performed database searches and sequenced genomic DNA in a 30-proband subsample to obtain a high-density map of 23 SNPs spanning 21.6 kb of this gene. Single-SNP analyses and also haplotype analyses revealed that rs4305745 and/or two other polymorphisms in perfect linkage disequilibrium (LD) with rs4305745 appear to be the most likely variants underlying the association of the TRAR4 region with schizophrenia. Comparative genomic analyses further revealed that rs4305745 and/or the associated polymorphisms in complete LD with rs4305745 could potentially affect gene expression. Moreover, RT-PCR studies of various human tissues, including brain, confirm that TRAR4 is preferentially expressed in those brain regions that have been implicated in the pathophysiology of schizophrenia. These data provide strong preliminary evidence that TRAR4 is a candidate gene for schizophrenia; replication is currently being attempted in additional clinical samples.

  View details for Web of Science ID 000223634100008

  View details for PubMedID 15329799

• Multicenter linkage study of schizophrenia loci on chromosome 22q MOLECULAR PSYCHIATRY Mowry, B. J., Holmans, P. A., Pulver, A. E., GEJMAN, P. V., Riley, B., Williams, N. M., Laurent, C., Schwab, S. G., Wildenauer, D. B., Bauche, S., Owen, M. J., Wormley, B., Sanders, A. R., Nestadt, G., Liang, K. Y., Duan, J., Ribble, R., Norton, N., Soubigou, S., Maier, W., Ewen-White, K. R., deMarchi, N., Carpenter, B., Walsh, D., Williams, H., Jay, M., Albus, M., Nertney, D. A., Papadimitriou, G., O'Neill, A., O'Donovan, M. C., DeLeuze, J. F., Lerer, F. B., Dikeos, D., Kendler, K. S., Mallet, J., Silverman, J. M., Crowe, R. R., Levinson, D. F. 2004; 9 (8): 784-795

  Abstract

  The hypothesis of the existence of one or more schizophrenia susceptibility loci on chromosome 22q is supported by reports of genetic linkage and association, meta-analyses of linkage, and the observation of elevated risk for psychosis in people with velocardiofacial syndrome, caused by 22q11 microdeletions. We tested this hypothesis by evaluating 10 microsatellite markers spanning 22q in a multicenter sample of 779 pedigrees. We also incorporated age at onset and sex into the analysis as covariates. No significant evidence for linkage to schizophrenia or for linkage associated with earlier age at onset, gender, or heterogeneity across sites was observed. We interpret these findings to mean that the population-wide effects of putative 22q schizophrenia susceptibility loci are too weak to detect with linkage analysis even in large samples.

  View details for DOI 10.1038/sj.mp.4001481

  View details for Web of Science ID 000222851700006

  View details for PubMedID 15007391

• Genomewide significant linkage to recurrent, early-onset major depressive disorder on chromosome 15q AMERICAN JOURNAL OF HUMAN GENETICS Holmans, P., Zubenko, G. S., Crowe, R. R., DePaulo, J. R., Scheftner, W. A., Weissman, M. M., Zubenko, W. N., Boutelle, S., Murphy-Eberenz, K., Mackinnon, D., McInnis, M. G., Marta, D. H., Adams, P., Knowles, J. A., Gladis, M., Thomas, J., Chellis, J., Miller, E., Levinson, D. F. 2004; 74 (6): 1154-1167

  Abstract

  A genome scan was performed on the first phase sample of the Genetics of Recurrent Early-Onset Depression (GenRED) project. The sample consisted of 297 informative families containing 415 independent affected sibling pairs (ASPs), or, counting all possible pairs, 685 informative affected relative pairs (555 ASPs and 130 other pair types). Affected cases had recurrent major depressive disorder (MDD) with onset before age 31 years for probands or age 41 years for other affected relatives; the mean age at onset was 18.5 years, and the mean number of depressive episodes was 7.3. The Center for Inherited Disease Research genotyped 389 microsatellite markers (mean spacing of 9.3 cM). The primary linkage analysis considered allele sharing in all possible affected relative pairs with the use of the Z(lr) statistic computed by the ALLEGRO program. A secondary logistic regression analysis considered the effect of the sex of the pair as a covariate. Genomewide significant linkage was observed on chromosome 15q25.3-26.2 (Zlr=4.14, equivalent LOD = 3.73, empirical genomewide P=.023). The linkage was not sex specific. No other suggestive or significant results were observed in the primary analysis. The secondary analysis produced three regions of suggestive linkage, but these results should be interpreted cautiously because they depended primarily on the small subsample of 42 male-male pairs. Chromosome 15q25.3-26.2 deserves further study as a candidate region for susceptibility to MDD.

  View details for Web of Science ID 000221651900008

  View details for PubMedID 15108123

• Examination of IMPA1 and IMPA2 genes in manic-depressive patients: association between IMPA2 promoter polymorphisms and bipolar disorder MOLECULAR PSYCHIATRY Sjoholt, G., Ebstein, R. P., Lie, R. T., Berle, J. O., Mallet, J., DeLeuze, J. F., Levinson, D. F., Laurent, C., Mujahed, M., Bannoura, I., Murad, I., Molven, A., Steen, V. M. 2004; 9 (6): 621-629

  Abstract

  Manic-depressive (bipolar) illness is a serious psychiatric disorder with a strong genetic predisposition. The disorder is likely to be multifactorial and etiologically complex, and the causes of genetic susceptibility have been difficult to unveil. Lithium therapy is a widely used pharmacological treatment of manic-depressive illness, which both stabilizes the ongoing episodes and prevents relapses. A putative target of lithium treatment has been the inhibition of the myo-inositol monophosphatase (IMPase) enzyme, which dephosphorylates myo-inositol monophosphate in the phosphatidylinositol signaling system. Two genes encoding human IMPases have so far been isolated, namely myo-inositol monophosphatase 1 (IMPA1) on chromosome 8q21.13-21.3 and myo-inositol monophosphatase 2 (IMPA2) on chromosome 18p11.2. In the present study, we have scanned for DNA variants in the human IMPA1 and IMPA2 genes in a pilot sample of Norwegian manic-depressive patients, followed by examination of selected polymorphisms and haplotypes in a family-based bipolar sample of Palestinian Arab proband-parent trios. Intriguingly, two frequent single-nucleotide polymorphisms (-461C>T and -207T>C) in the IMPA2 promoter sequence and their corresponding haplotypes showed transmission disequilibrium in the Palestinian Arab trios. No association was found between the IMPA1 polymorphisms and bipolar disorder, neither with respect to disease susceptibility nor with variation in lithium treatment response. The association between manic-depressive illness and IMPA2 variants supports several reports on the linkage of bipolar disorder to chromosome 18p11.2, and sustains the possible role of IMPA2 as a susceptibility gene in bipolar disorder.

  View details for DOI 10.1038/sj.mp.4001460

  View details for Web of Science ID 000221664300013

  View details for PubMedID 14699425

• Tumor necrosis factor haplotype analysis amongst schizophrenia probands from four distinct populations in the Asia-Pacific region AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Handoko, H. Y., Nancarrow, D. J., Hayward, N. K., Ohaeri, J. U., Aghanwa, H., McGrath, J. J., Levinson, D. F., Johns, C., Walters, M. K., Nertney, D. A., Srinivasan, T. N., Thara, R., Mowry, B. J. 2003; 121B (1): 1-6

  Abstract

  A single nucleotide polymorphism (TNF(-308A)) within the promoter region of the gene encoding tumor necrosis factor (TNF), has been significantly associated with schizophrenia in a study of Italian patients and control subjects Boin et al. [2001: Mol Psychiatry 6:79-82]. We have applied case-control analyses to examine TNF promoter haplotypes (containing TNF(-308) and two additional promoter variants: TNF(-376) and TNF(-238)) in four schizophrenia cohorts drawn from Australian, Indian Fijian, Indigenous Fijian, and Brahmin populations. In addition, we have applied the sibling transmission disequilibrium (STD) test to promoter haplotypes within 81 trios drawn from Australian Caucasian pedigrees with multiple schizophrenia cases, and 86 trios drawn from the Brahmin population of Tamil Nadu province in Southern India. Within each of these cohorts, we found no evidence of recombination between these tightly linked promoter variants, supporting previous studies which demonstrated that only a subset of the eight possible haplotypes exist. Of the four observed haplotypes, we and others have observed only one carries the TNF(-308A) variant allele. We report no significant differences in TNF promoter haplotype frequencies between the patient and control groups within each population, although the Indian Fijian cohort showed a trend towards reduced TNF(-308A) alleles amongst schizophrenia cases (P = 0.07). We found no evidence of bias in TNF promoter haplotype transmission to schizophrenia probands. Very similar results were obtained when only the TNF(-308) polymorphism was considered. Taken together, these data provide no support for the involvement of TNF promoter variants TNF(-308), TNF(-376), and TNF(-238) in schizophrenia susceptibility within four ethnically distinct cohorts.

  View details for DOI 10.1002/ajmg.b.20059

  View details for Web of Science ID 000184548900001

  View details for PubMedID 12898567

• Genome scan meta-analysis of schizophrenia and bipolar disorder, part III: Bipolar disorder AMERICAN JOURNAL OF HUMAN GENETICS Segurado, R., Detera-Wadleigh, S. D., Levinson, D. F., Lewis, C. M., Gill, M., Nurnberg, J. I., Craddock, N., DePaulo, J. R., Baron, M., Gershon, E. S., Ekholm, J., Cichon, S., Turecki, G., Claes, S., Kelsoe, J. R., Schofield, P. R., Badenhop, R. F., Morissette, J., Coon, H., Blackwood, D., McInnes, L. A., Foroud, T., Edenberg, H. J., Reich, T., RICE, J. P., Goate, A., McInnis, M. G., McMahon, F. J., Badner, J. A., Goldin, L. R., Bennett, P., Willour, V. L., Zandi, P. P., Liu, J. J., Gilliam, C., Juo, S. H., Berrettini, W. H., Yoshikawa, T., Peltonen, L., Lonnqvist, J., Nothen, M. M., Schumacher, J., Windemuth, C., Rietschel, M., Propping, P., Maier, W., Alda, M., Grof, P., Rouleau, G. A., Del-Favero, J., Van Broeckhoven, C., Mendlewicz, J., Adolfsson, R., SPENCE, M. A., Luebbert, H., Adams, L. J., Donald, J. A., Mitchell, P. B., Barden, N., Shink, E., Byerley, W., Muir, W., Visscher, P. M., MacGregor, S., Gurling, H., Kalsi, G., McQuillin, A., Escamilla, M. A., Reus, V. I., LEON, P., Freimer, N. B., Ewald, H., Kruse, T. A., Mors, O., Radhakrishna, U., Blouin, J. L., Antonarakis, S. E., Akarsu, N. 2003; 73 (1): 49-62

  Abstract

  Genome scans of bipolar disorder (BPD) have not produced consistent evidence for linkage. The rank-based genome scan meta-analysis (GSMA) method was applied to 18 BPD genome scan data sets in an effort to identify regions with significant support for linkage in the combined data. The two primary analyses considered available linkage data for "very narrow" (i.e., BP-I and schizoaffective disorder-BP) and "narrow" (i.e., adding BP-II disorder) disease models, with the ranks weighted for sample size. A "broad" model (i.e., adding recurrent major depression) and unweighted analyses were also performed. No region achieved genomewide statistical significance by several simulation-based criteria. The most significant P values (<.01) were observed on chromosomes 9p22.3-21.1 (very narrow), 10q11.21-22.1 (very narrow), and 14q24.1-32.12 (narrow). Nominally significant P values were observed in adjacent bins on chromosomes 9p and 18p-q, across all three disease models on chromosomes 14q and 18p-q, and across two models on chromosome 8q. Relatively few BPD pedigrees have been studied under narrow disease models relative to the schizophrenia GSMA data set, which produced more significant results. There was no overlap of the highest-ranked regions for the two disorders. The present results for the very narrow model are promising but suggest that more and larger data sets are needed. Alternatively, linkage might be detected in certain populations or subsets of pedigrees. The narrow and broad data sets had considerable power, according to simulation studies, but did not produce more highly significant evidence for linkage. We note that meta-analysis can sometimes provide support for linkage but cannot disprove linkage in any candidate region.

  View details for Web of Science ID 000183904900005

  View details for PubMedID 12802785

• Genome scan meta-analysis of schizophrenia and bipolar disorder, part II: Schizophrenia AMERICAN JOURNAL OF HUMAN GENETICS Lewis, C. M., Levinson, D. F., Wise, L. H., DeLisi, L. E., Straub, R. E., Hovatta, I., Williams, N. M., Schwab, S. G., Pulver, A. E., Faraone, S. V., Brzustowicz, L. M., Kaufmann, C. A., Garver, D. L., Gurling, H. M., Lindholm, E., Coon, H., Moises, H. W., Byerley, W., Shaw, S. H., Mesen, A., Sherrington, R., O'Neill, F. A., Walsh, D., Kendler, K. S., Ekelund, J., Paunio, T., Lonnqvist, J., Peltonen, L., O'Donovan, M. C., Owen, M. J., Wildenauer, D. B., Maier, W., Nestadt, G., Blouin, J. L., Antonarakis, S. E., Mowry, B. J., Silverman, J. M., Crowe, R. R., Cloninger, C. R., Tsuang, M. T., Malaspina, D., Harkavy-Friedman, J. M., Svrakic, D. M., Bassett, A. S., Holcomb, J., Kalsi, G., McQuillin, A., Brynjolfson, J., Sigmundsson, T., Petursson, H., Jazin, E., Zoega, T., Helgason, T. 2003; 73 (1): 34-48

  Abstract

  Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (R(avg)) and then weighted for sample size (N(sqrt)[affected casess]). A permutation test was used to compute the probability of observing, by chance, each bin's average rank (P(AvgRnk)) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (P(ord)). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (PAvgRnk<.000417). Two aggregate criteria for linkage were also met (clusters of nominally significant P values that did not occur in 1,000 replicates of the entire data set with no linkage present): 12 consecutive bins with both P(AvgRnk) and P(ord)<.05, including regions of chromosomes 5q, 3p, 11q, 6p, 1q, 22q, 8p, 20q, and 14p, and 19 consecutive bins with P(ord)<.05, additionally including regions of chromosomes 16q, 18q, 10p, 15q, 6q, and 17q. There is greater consistency of linkage results across studies than has been previously recognized. The results suggest that some or all of these regions contain loci that increase susceptibility to schizophrenia in diverse populations.

  View details for Web of Science ID 000183904900004

  View details for PubMedID 12802786

• Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis AMERICAN JOURNAL OF HUMAN GENETICS Levinson, D. F., Levinson, M. D., Segurado, R., Lewis, C. M. 2003; 73 (1): 17-33

  Abstract

  This is the first of three articles on a meta-analysis of genome scans of schizophrenia (SCZ) and bipolar disorder (BPD) that uses the rank-based genome scan meta-analysis (GSMA) method. Here we used simulation to determine the power of GSMA to detect linkage and to identify thresholds of significance. We simulated replicates resembling the SCZ data set (20 scans; 1,208 pedigrees) and two BPD data sets using very narrow (9 scans; 347 pedigrees) and narrow (14 scans; 512 pedigrees) diagnoses. Samples were approximated by sets of affected sibling pairs with incomplete parental data. Genotypes were simulated and nonparametric linkage (NPL) scores computed for 20 180-cM chromosomes, each containing six 30-cM bins, with three markers/bin (or two, for some scans). Genomes contained 0, 1, 5, or 10 linked loci, and we assumed relative risk to siblings (lambda(sibs)) values of 1.15, 1.2, 1.3, or 1.4. For each replicate, bins were ranked within-study by maximum NPL scores, and the ranks were averaged (R(avg)) across scans. Analyses were repeated with weighted ranks ((sqrt)N[genotyped cases] for each scan). Two P values were determined for each R(avg): P(AvgRnk) (the pointwise probability) and P(ord) (the probability, given the bin's place in the order of average ranks). GSMA detected linkage with power comparable to or greater than the underlying NPL scores. Weighting for sample size increased power. When no genomewide significant P values were observed, the presence of linkage could be inferred from the number of bins with nominally significant P(AvgRnk), P(ord), or (most powerfully) both. The results suggest that GSMA can detect linkage across multiple genome scans.

  View details for Web of Science ID 000183904900003

  View details for PubMedID 12802787

• Genetics of recurrent early-onset depression (GenRED): Design and preliminary clinical characteristics of a repository sample for genetic linkage studies AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Levinson, D. F., Zubenko, G. S., Crowe, R. R., DePaulo, R. J., Scheftner, W. S., Weissman, M. M., Holmans, P., Zubenko, W. N., Boutelle, S., Murphy-Eberenz, K., Mackinnon, D., McInnis, M. G., Marta, D. H., Adams, P., Sassoon, S., Knowles, J. A., Thomas, J., Chellis, J. 2003; 119B (1): 118-130

  Abstract

  This is an initial report on a six-site collaborative project, Genetics of Recurrent Early-Onset Depression (GenRED). This is a study of a large sample of families with recurrent major depressive disorder (DSM-IV) beginning by the age 30 in probands or 40 in relatives. Evidence suggests that early onset and recurrence of depressive episodes predict substantially increased risk of depression in first-degree relatives compared with the general population, suggesting that susceptibility genes might be mapped with this phenotype. The projected sample of 800-1,000 affected sibling pairs (ASPs) and other relatives will be studied using genome scan methods. Biological materials and blinded clinical data will be made available through the NIMH cell repository program. The sample should have good-to-excellent power to detect a locus associated with a 24% or greater population-wide increase in risk to siblings. We describe 838 affected individuals from the first 305 families containing 434 independent ASPs, or 613 ASPs counting all possible pairs. The mean age at the onset was 18.5 years, with a mean of 7.3 episodes and longest episode of 655 days. Almost all subjects had experienced at least 4 weeks of depression with five or more additional symptom criteria. Frequencies of symptoms and psychiatric and medical comorbid are provided. Substance use was more common in males, and panic disorder in females. Within pairs of affected siblings, correlations were significant for age at onset, substance abuse/dependence, panic disorder, obsessive-compulsive disorder and nicotine initiation and persistence. We replicated previously reported associations among comorbid panic disorder and social phobia, chronicity of depression and suicidal behavior. This suggests comparability of our cases to those in earlier large family studies. This dataset should prove useful for genetic studies of a highly familial form of major depressive disorder.

  View details for DOI 10.1002/ajmg.b.20009

  View details for Web of Science ID 000182548100022

  View details for PubMedID 12707949

• CAG repeat Polymorphisms in KCNN3 (HSKCa3) and PPP2R2B show no association or linkage to schizophrenia AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS Laurent, C., Niehaus, D., Bauche, S., Levinson, D. F., Soubigou, S., Pimstone, S., Hayden, M., Mbanga, I., Emsley, R., DeLeuze, J. F., Mallet, J. 2003; 116B (1): 45-50

  Abstract

  The purpose of this study was to determine whether genetic linkage or association could be observed between schizophrenia (SZ) and the CAG repeat polymorphisms within the genes KCNN3 (known previously as hSKCa3) and PPP2R2B (linked to Spino-Cerebellar Atrophy 12) in the Xhosa population in South Africa. Neither locus has been studied previously in African populations. The polymorphisms were genotyped in 589 individuals to form samples for Transmission Disequilibrium Test (TDT) analysis (176 unrelated probands, 145 with both parents and 30 with one parent genotyped), linkage analysis (49 families with 54 independent affected sib pairs [ASPs]), and case-control analyses (67 familial cases with a first-degree SZ relative, 101 sporadic cases with no affected first- or second-degree relative, and 90 control cases). No significant differences were found among familial cases, sporadic cases and controls in allele sizes (Kruskal-Wallis tests) or the numbers of alleles with sizes above and below the mean size for each polymorphism. Allele size was not correlated with age of onset (Spearman correlation). No significant evidence for association was observed using TDT analyses for all triads and separately for the familial triads. No significant evidence for linkage was observed for either locus with affected sib pair analysis using the possible triangle method or with Non-Parametric Linkage (NPL) analysis of the multiplex families. In conclusion, no significant evidence for linkage or association with SZ was observed for either polymorphism in this population.

  View details for DOI 10.1002/ajmg.b.10797

  View details for Web of Science ID 000182399800009

  View details for PubMedID 12497613

• Reduction in inpatient length of stay and changes in mental health care in Israel over four decades: A national case register study ISRAEL JOURNAL OF PSYCHIATRY AND RELATED SCIENCES Levinson, D., Lerner, Y., Lichtenberg, P. 2003; 40 (4): 240-247

  Abstract

  The purpose of the present study was to investigate trends over the past 40 years in the accumulated length of hospital stay, and to consider how these trends might have been affected by changes in the provision of mental health care in Israel from 1960 to 1997.The national psychiatric case register was used to follow four cohorts of all new admissions in 1960, 1970, 1980 and 1990 diagnosed with schizophrenia or affective disorders for the first seven years following the index admission.Most of the changes in length of stay occurred among patients with schizophrenia. The overall accumulated length of stay decreased by 50% between 1960 and 1980. The largest reduction was observed among long-stay patients with schizophrenia. Number of admissions did not change for the four cohorts.The interpretation of the data remains speculative, as we are attempting to establish causality between parallel trends.The general trend in the findings of this study corresponds with changes that took place between 1970 and 1990 in the outpatient care for the mentally ill. These innovations facilitated the discharge of patients with chronic schizophrenia and altered the case mix of the newly admitted patients.

  View details for Web of Science ID 000188125100003

  View details for PubMedID 14971125

• Polymorphisms in the 5 '-untranslated region of the human serotonin receptor 1B (HTR1B) gene affect gene expression MOLECULAR PSYCHIATRY Duan, J., Sanders, A. R., Vander Molen, J., Martinolich, L., Mowry, B. J., Levinson, D. F., Crowe, R. R., Silverman, J. M., GEJMAN, P. V. 2003; 8 (11): 901-910

  Abstract

  We present evidence of complex balancing regulation of HTR1B transcription by common polymorphisms in its promoter. Computational analysis of the HTR1B gene predicted that a 5' segment, spanning common DNA sequence variations, T-261G, A-161T, and -182INS/DEL-181, contained a putative functional promoter. Using a secreted alkaline phosphatase (SEAP) reporter gene system, we found that the haplotype -261G_-182INS-181_A-161 enhanced transcriptional activity 2.3-fold compared with the haplotype T-261_-182INS-181_A-161. Conversely, -161T reversed this, and the net effect when -261G and -161T were in the same haplotype (-261G_-182INS-181_-161T) was equivalent to the major haplotype (T-261_-182INS-181_A-161). Electrophoretic mobility shift experiments showed that -261G and -161T modify the binding of transcription factors (TFs): -261G generates a new AP2 binding site, while alleles A-161 and -161T exhibit different binding characteristics to AP1. T-261G and A-161T were found to be in linkage disequilibrium (LD) with G861C in a European ancestry population. Interestingly, G861C has been reported to be associated with several psychiatric disorders. Our results indicate that HTR1B is the target of substantial transcriptional genetic regulation by common haplotypes, which are in LD with the HTR1B single-nucleotide polymorphism (SNP) most commonly used in association studies.

  View details for DOI 10.1038/sj.mp.4001403

  View details for Web of Science ID 000186453900004

  View details for PubMedID 14593427

• No major schizophrenia locus detected on chromosome 1q in a large multicenter sample SCIENCE Levinson, D. F., Holmans, P. A., Laurent, C., Riley, B., Pulver, A. E., GEJMAN, P. V., Schwab, S. G., Williams, N. M., Owen, M. J., Wildenauer, D. B., Sanders, A. R., Nestadt, G., Mowry, B. J., Wormley, B., Bauche, S., Soubigou, S., Ribble, R., Nertney, D. A., Liang, K. Y., Martinolich, L., Maier, W., Norton, N., Williams, H., Albus, M., Carpenter, E. B., deMarchi, N., Ewen-White, K. R., Walsh, D., Jay, M., DeLeuze, J. F., O'Neill, F. A., Papadimitriou, G., Weilbaecher, A., Lerer, B., O'Donovan, M. C., Dikeos, D., Silverman, J. M., Kendler, K. S., Mallet, J., Crowe, R. R., Walters, M. 2002; 296 (5568): 739-741

  Abstract

  Reports of substantial evidence for genetic linkage of schizophrenia to chromosome 1q were evaluated by genotyping 16 DNA markers across 107 centimorgans of this chromosome in a multicenter sample of 779 informative schizophrenia pedigrees. No significant evidence was observed for such linkage, nor for heterogeneity in allele sharing among the eight individual samples. Separate analyses of European-origin families, recessive models of inheritance, and families with larger numbers of affected cases also failed to produce significant evidence for linkage. If schizophrenia susceptibility genes are present on chromosome 1q, their population-wide genetic effects are likely to be small.

  View details for Web of Science ID 000175281700056

  View details for PubMedID 11976456

• The Lifetime Dimensions of Psychosis Scale (LDPS): Description and interrater reliability SCHIZOPHRENIA BULLETIN Levinson, D. F., Mowry, B. J., Escamilla, M. A., Faraone, S. V. 2002; 28 (4): 683-695

  Abstract

  A new rating scale, the Lifetime Dimensions of Psychosis Scale (LDPS), is described. The LDPS creates a profile of the lifetime characteristics of each case based on retrospective ratings, encompassing the positive, bizarre, negative, and disorganized symptom factors identified by previous studies of psychotic disorders, plus mood-related symptomatology, degree of deterioration, and complicating factors over the course of illness. A preliminary 39-item scale and instruction manual were developed. Intraclass correlation coefficients (ICCs) for positive symptom and mood item total scores were 0.76 to 0.87 (mean of 0.70 for all items). Highly intercorrelated (tau-b coefficients) or unreliable items were eliminated to create the final 20-item version 2. Good-excellent reliability was observed in a second study using different raters. The LDPS is designed for use by experienced clinicians or researchers who have access to comprehensive clinical information, including semistructured diagnostic interviews, psychiatric records, and family history reports. Dimensional scores and multidimensional patterns might prove useful in studying the relationship of clinical phenotype to genotypes, treatment response, and other variables. They may also be useful in clinical practice.

  View details for Web of Science ID 000182910400009

  View details for PubMedID 12795498

• Protecting the privacy of family members in research JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Levinson, D. F., Reich, T., Todd, R. D., Weissman, M. M., Crowe, R. R., Delisi, L., Faraone, S. V., Folstein, S., Pelias, M. K., Pulver, A. E., Silverman, J. M. 2001; 285 (15): 1960-1961

  View details for Web of Science ID 000167995900015

  View details for PubMedID 11308424

• Genetic diversity of the human serotonin receptor 1B (HTR1B) gene GENOMICS Sanders, A. R., Cao, Q. H., Taylor, J., Levin, T. E., Badner, J. A., Cravchik, A., Comeron, J. M., Naruya, S., del Rosario, A., Salvi, D. A., Walczyk, K. A., Mowry, B. J., Levinson, D. F., Crowe, R. R., Silverman, J. M., Gejman, P. V. 2001; 72 (1): 1-14

  Abstract

  We systematically and comprehensively investigated polymorphisms of the HTR1B gene as well as their linkage disequilibrium and ancestral relationships. We have detected the following polymorphisms in our sample via denaturing gradient gel electrophoresis, database comparisons, and/or previously published assays: G-511T, T-261G, -182INS/DEL-181, A-161T, C129T, T371G, T655C, C705T, G861C, A1099G, G1120A, and A1180G. The results of the intermarker analyses showed strong linkage disequilibrium between the C129T and the G861C polymorphisms and revealed four common haplotypes: ancestral (via chimpanzee comparisons), 129T/861C, -161T, and -182DEL-181. The results of association tests with schizophrenia were negative, although A-161T had a nominal P = 0.04 via ASPEX/sib_tdt. The expressed missense substitutions, Phe124Cys, Phe219Leu, Ile367Val, and Glu374Lys, could potentially affect ligand binding or interaction with G proteins and thus modify drug response in carriers of these variants. On average, the human cSNPs and differences among other primates clustered in the more thermodynamically unstable regions of the mRNA, which suggests that the evolutionary survival of nucleotide sequence variation may be influenced by the mRNA structure of this gene.

  View details for DOI 10.1006/geno.2000.6411

  View details for Web of Science ID 000167553700001

  View details for PubMedID 11247661

• Simulation studies of detection of a complex disease in a partially isolated population AMERICAN JOURNAL OF MEDICAL GENETICS Levinson, D. F., Kirby, A., Slepner, S., Nolte, I., Spijker, G. T., te Meerman, G. 2001; 105 (1): 65-70

  Abstract

  Simulation studies were undertaken with POPGEN, a new population simulation program, to explore strategies for detecting loci underlying rare and common disorders in a small population that has been partially isolated for 10 generations. Haplotype-sharing analysis (HSA) and non-parametric linkage analysis (NPL) were applied to the simulated haplotype and pedigree data for 100 cases, 100 controls, and an average of 28 multiplex pedigrees from cases' families, for a 2-5 cM map of markers. When identity by descent (IBD) status was known (using unique founder marker allele designations assigned during simulation), a linkage disequilibrium (LD) signal could be detected under disease-generating models predicting relative risk to sibs of 11.8 (high-RR) or 2.67 (mod-RR). Detection was more difficult when marker alleles were down-coded to resemble microsatellites (heterozygosities 0.75-0.80). False-positive peaks on nondisease chromosomes were uncommon. NPL analysis was more powerful than HSA at this marker density using down-coded alleles and assuming availability of all affected relatives. LD mapping of common disorders is likely to require denser maps of highly polymorphic markers to approximate full IBD information. LD and linkage mapping provide independent information, and strategies that combine these two methods could be useful in studies of small isolated populations.

  View details for Web of Science ID 000166286300023

  View details for PubMedID 11425003

• Haplotype sharing tests of linkage disequilibrium in a Hutterite asthma data set Genetic Analysis Workshop 12 (GAW12) Levinson, D. F., Nolte, I., Meerman, G. J. WILEY-BLACKWELL. 2001: S308–S311

  Abstract

  The Genetic Analysis Workshop 12 genome scan data set for "strict" asthma in a Hutterite population was analyzed using haplotype sharing analysis (HSA), which tests for differences in mean length of haplotype sharing around each marker for pairs of chromosomes in cases versus controls. The regions of chromosome 1 and 8 where evidence for linkage was observed in published analyses were negative by HSA. HSA yielded positive results on chromosomes 7, 12, 16, 18, and 21 (p = 0.003 on 21q). Although there are reports of support for linkage to asthma in some of these regions, it is not known whether any represent true positives. Further study is needed of the possible role of length-based measures of linkage disequilibrium in recent population isolates.

  View details for Web of Science ID 000171462700058

  View details for PubMedID 11793689

• Introduction: Linkage disequilibrium and combined linkage and LD mapping of asthma-related genes GENETIC EPIDEMIOLOGY Levinson, D. F. 2001; 21: S290-S291

  View details for Web of Science ID 000171462700054

  View details for PubMedID 11793684

• Second stage of a genome scan of schizophrenia: Study of five positive regions in an expanded sample AMERICAN JOURNAL OF MEDICAL GENETICS Mowry, B. J., Ewen, K. R., Nancarrow, D. J., Lennon, D. P., Nertney, D. A., Jones, H. L., O'Brien, M. S., Thornley, C. E., Walters, M. K., Crowe, R. R., Silverman, J. M., Endicott, J., Sharpe, L., Hayward, N. K., Gladis, M. M., Foote, S. J., Levinson, D. F. 2000; 96 (6): 864-869

  Abstract

  In a previous genome scan of 43 schizophrenia pedigrees, nonparametric linkage (NPL) scores with empirically derived pointwise P-values less than 0.01 were observed in two regions (chromosomes 2q12-13 and 10q23) and less than 0.05 in three regions (4q22-23, 9q22, and 11q21). Markers with a mean spacing of about 5 cM were typed in these regions in an expanded sample of 71 pedigrees, and NPL analyses carried out. No region produced significant genomewide evidence for linkage. On chromosome 10q, the empirical P-value remained at less than 0.01 for the entire sample (D10S168), evidence in the original 43 pedigrees was slightly increased, and a broad peak of positive results was observed. P-values less than 0.05 were observed on chromosomes 2q (D2S436) and 4q (D4S2623), but not on chromosomes 9q or 11q. It is concluded that this sample is most supportive of linkage on chromosome 10q, with less consistent support on chromosomes 2q and 4q. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:864-869, 2000.

  View details for Web of Science ID 000165717300035

  View details for PubMedID 11121199

• Evidence for linkage by transmission disequilibrium test analysis of a chromosome 22 microsatellite marker D22S278 and bipolar disorder in a Palestinian Arab population AMERICAN JOURNAL OF MEDICAL GENETICS Mujaheed, M., Corbex, M., Lichtenberg, P., Levinson, D. F., DeLeuze, J. F., Mallet, J., Ebstein, R. P. 2000; 96 (6): 836-838

  Abstract

  A number of linkage studies suggest a schizophrenia susceptibility locus on chromosome 22, particularly with microsatellite marker D22S278 (22q12). In addition to some evidence for linkage to schizophrenia in this region, linkage to bipolar disorder using this marker has also been reported. We tested a group of 60 Bipolar I triads and an expanded group of 79 Bipolar I and Bipolar II triads recruited from a Palestinian Arab population for linkage with the D22S278 marker. Significant linkage was observed using the extended transmission disequilibrium test for multiallelic markers (ETDT) for both Bipolar I (P = 0.031) and the expanded group of Bipolar I and Bipolar II (P = 0.041). These weakly positive results are at least consistent with the hypothesis that this region of chromosome 22 might harbor a susceptibility locus for both major psychoses and should be considered for more intensive study. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:836-838, 2000.

  View details for Web of Science ID 000165717300028

  View details for PubMedID 11121192

• Identification and analysis of error types in high-throughput genotyping AMERICAN JOURNAL OF HUMAN GENETICS Ewen, K. R., Bahlo, M., Treloar, S. A., Levinson, D. F., Mowry, B., Barlow, J. W., Foote, S. J. 2000; 67 (3): 727-736

  Abstract

  Although it is clear that errors in genotyping data can lead to severe errors in linkage analysis, there is as yet no consensus strategy for identification of genotyping errors. Strategies include comparison of duplicate samples, independent calling of alleles, and Mendelian-inheritance-error checking. This study aimed to develop a better understanding of error types associated with microsatellite genotyping, as a first step toward development of a rational error-detection strategy. Two microsatellite marker sets (a commercial genomewide set and a custom-designed fine-resolution mapping set) were used to generate 118,420 and 22,500 initial genotypes and 10,088 and 8,328 duplicates, respectively. Mendelian-inheritance errors were identified by PedManager software, and concordance was determined for the duplicate samples. Concordance checking identifies only human errors, whereas Mendelian-inheritance-error checking is capable of detection of additional errors, such as mutations and null alleles. Neither strategy is able to detect all errors. Inheritance checking of the commercial marker data identified that the results contained 0.13% human errors and 0.12% other errors (0.25% total error), whereas concordance checking found 0.16% human errors. Similarly, Mendelian-inheritance-error checking of the custom-set data identified 1.37% errors, compared with 2.38% human errors identified by concordance checking. A greater variety of error types were detected by Mendelian-inheritance-error checking than by duplication of samples or by independent reanalysis of gels. These data suggest that Mendelian-inheritance-error checking is a worthwhile strategy for both types of genotyping data, whereas fine-mapping studies benefit more from concordance checking than do studies using commercial marker data. Maximization of error identification increases the likelihood of linkage when complex diseases are analyzed.

  View details for Web of Science ID 000089002300018

  View details for PubMedID 10924406

• Multicenter linkage study of schizophrenia candidate regions on chromosomes 5q, 6q, 10p, and 13q: Schizophrenia linkage collaborative group III AMERICAN JOURNAL OF HUMAN GENETICS Levinson, D. F., Holmans, P., Straub, R. E., Owen, M. J., Wildenauer, D. B., GEJMAN, P. V., Pulver, A. E., Laurent, C., Kendler, K. S., Walsh, D., Norton, N., Williams, N. M., Schwab, S. G., Lerer, B., Mowry, B. J., Sanders, A. R., Antonarakis, S. E., Blouin, J. L., DeLeuze, J. F., Mallet, J. 2000; 67 (3): 652-663

  Abstract

  Schizophrenia candidate regions 33-51 cM in length on chromosomes 5q, 6q, 10p, and 13q were investigated for genetic linkage with mapped markers with an average spacing of 5.64 cM. We studied 734 informative multiplex pedigrees (824 independent affected sibling pairs [ASPs], or 1,003 ASPs when all possible pairs are counted), which were collected in eight centers. Cases with diagnoses of schizophrenia or schizoaffective disorder (DSM-IIIR criteria) were considered affected (n=1,937). Data were analyzed with multipoint methods, including nonparametric linkage (NPL), ASP analysis using the possible-triangle method, and logistic-regression analysis of identity-by-descent (IBD) sharing in ASPs with sample as a covariate, in a test for intersample heterogeneity and for linkage with allowance for intersample heterogeneity. The data most supportive for linkage to schizophrenia were from chromosome 6q; logistic-regression analysis of linkage allowing for intersample heterogeneity produced an empirical P value <.0002 with, or P=.0004 without, inclusion of the sample that produced the first positive report in this region; the maximum NPL score in this region was 2.47 (P=.0046), the maximum LOD score (MLS) from ASP analysis was 3.10 (empirical P=.0036), and there was significant evidence for intersample heterogeneity (empirical P=.0038). More-modest support for linkage was observed for chromosome 10p, with logistic-regression analysis of linkage producing an empirical P=. 045 and with significant evidence for intersample heterogeneity (empirical P=.0096).

  View details for Web of Science ID 000089002300012

  View details for PubMedID 10924404

• Is akathisia associated with poor clinical response to antipsychotics during acute hospital treatment? GENERAL HOSPITAL PSYCHIATRY Luthra, V., Pinninti, N. R., Yoder, K., Musthaq, M. S., Umapathy, C., Levinson, D. F. 2000; 22 (4): 276-280

  Abstract

  Previous studies have suggested that akathisia is associated with poor acute clinical response to antipsychotics and that low serum iron levels are associated with emergence of akathisia. To examine these relationships during routine clinical treatment, we studied patients with DSM-IV schizophrenia or schizoaffective disorder undergoing hospital treatment for acute psychotic exacerbations with doctor's choice medications. There were 34 subjects observed for at least 2 weeks. They were assessed at baseline and weekly by one rater with the Anchored Brief Psychiatric Rating Scale and by another rater with the Barnes Rating Scale for akathisia, with the two raters blind to each other's ratings. Serum ferritin and transferrin levels were obtained at baseline. Seventeen subjects developed akathisia. Subjects with and without akathisia did not differ in change in thinking disturbance or anxiety-depression scores over 2 weeks, or in serum ferritin or transferrin levels. We conclude that mild akathisia by itself is not strongly associated with initial response to low to moderate doses of antipsychotics in the acute clinical setting. Limitations of the study are discussed.

  View details for Web of Science ID 000088835200008

  View details for PubMedID 10936635

• No support for linkage to the bipolar regions on chromosomes 4p, 18p, or 18q in 43 schizophrenia pedigrees AMERICAN JOURNAL OF MEDICAL GENETICS Nancarrow, D. J., Levinson, D. F., Taylor, J. M., Hayward, N. K., Walters, M. K., Lennon, D. P., Nertney, D. A., Jones, H. L., Mahtani, M. M., Kirby, A., Kruglyak, L., Brown, D. M., Crowe, R. R., Andreasen, N. C., Black, D. W., Silverman, J. M., Mohs, R. C., Siever, L. J., Endicott, J., Sharpe, L., Mowry, B. J. 2000; 96 (2): 224-227

  View details for Web of Science ID 000086176100019

  View details for PubMedID 10893501

• Psychiatric adverse events during vigabatrin therapy NEUROLOGY Levinson, D. F., Devinsky, O. 1999; 53 (7): 1503-1511

  Abstract

  To determine the incidence of psychiatric adverse events associated with vigabatrin therapy, we reviewed data from US and non-US double-blind, placebo-controlled trials of vigabatrin as add-on therapy for treatment-refractory partial epilepsy."Verbatim" terms from investigators' reports had been translated into standard "preferred" terms using an adverse event dictionary. Terms for psychiatric events were then combined into categories for analysis of rates during vigabatrin versus placebo treatment.Compared with placebo, vigabatrin subjects had a higher incidence of events coded as depression (12.1% versus 3.5%, p < 0.001) and psychosis (2.5% versus 0.3%, p = 0.028); there were no significant differences between treatment groups for aggressive reaction, manic symptoms, agitation, emotional lability, anxiety, or suicide attempt. Although depression and psychosis were typically observed during the first 3 months, most studies were 12 to 18 weeks long, so that definitive conclusions could not be reached about timing of events. Psychosis was generally transient and reported to be responsive to reduction or discontinuation of vigabatrin or to neuroleptic treatment. Depression was typically mild. Serious depression, defined as discontinued from the study, hospitalized, or suicide attempt, or coded as psychotic depression, occurred in only 9 of the 49 vigabatrin-treated patients with depression.Vigabatrin use in treatment-refractory partial epilepsy is associated with increased occurrence of depression and of psychosis, although the frequency of psychosis is apparently lower than previously reported. Clinical experience suggests that these adverse events respond to reduction of vigabatrin dose or to counteractive psychotropic treatment.

  View details for Web of Science ID 000083180400023

  View details for PubMedID 10534259

• Follow-up study on a susceptibility locus for schizophrenia on chromosome 6q AMERICAN JOURNAL OF MEDICAL GENETICS Martinez, M., Goldin, L. R., Cao, Q. H., Zhang, J., Sanders, A. R., Nancarrow, D. J., Taylor, J. M., Levinson, D. F., Kirby, A., Crowe, R. R., Andreasen, N. C., Black, D. W., Silverman, J. M., Lennon, D. P., Nertney, D. A., Brown, D. M., Mowry, B. J., Gershon, E. S., GEJMAN, P. V. 1999; 88 (4): 337-343

  Abstract

  Evidence for suggestive linkage to schizophrenia with chromosome 6q markers was previously reported from a two-stage approach. Using nonparametric affected sib pairs (ASP) methods, nominal p-values of 0.00018 and 0.00095 were obtained in the screening (81 ASPs; 63 independent) and the replication (109 ASPs; 87 independent) data sets, respectively. Here, we report a follow-up study of this 50cM 6q region using 12 microsatellite markers to test for linkage to schizophrenia. We increased the replication sample size by adding an independent sample of 43 multiplex pedigrees (66 ASPs; 54 independent). Pairwise and multipoint nonparametric linkage analyses conducted in this third data set showed evidence consistent with excess sharing in this 6q region, though the statistical level is weaker (p=0.013). When combining both replication data sets (total of 141 independent ASPs), an overall nominal p-value=0.000014 (LOD=3. 82) was obtained. The sibling recurrence risk (lambdas) attributed to this putative 6q susceptibility locus is estimated to be 1.92. The linkage region could not be narrowed down since LOD score values greater than three were observed within a 13cM region. The length of this region was only slightly reduced (12cM) when using the total sample of independent ASPs (204) obtained from all three data sets. This suggests that very large sample sizes may be needed to narrow down this region by ASP linkage methods. Study of the etiological candidate genes in this region is ongoing.

  View details for Web of Science ID 000081581400009

  View details for PubMedID 10402499

• Treatment of schizoaffective disorder and schizophrenia with mood symptoms AMERICAN JOURNAL OF PSYCHIATRY Levinson, D. F., Umapathy, C., Musthaq, M. 1999; 156 (8): 1138-1148

  Abstract

  Patients with concurrent schizophrenic and mood symptoms are often treated with antipsychotics plus antidepressant or thymoleptic drugs. The authors review the literature on treatment of two overlapping groups of patients: those with schizoaffective disorder and those with schizophrenia and concurrent mood symptoms.MEDLINE searches (from 1976 onward) were undertaken to identify treatment studies of both groups, and references in these reports were checked. Selection of studies for review was based on the use of specified diagnostic criteria and of parallel-group, double-blind design (or, where few such studies addressed a particular issue, large open studies). A total of 18 treatment studies of schizoaffective disorder and 15 of schizophrenia with mood symptoms were selected for review.For acute exacerbations of schizoaffective disorder or of schizophrenia with mood symptoms, antipsychotics appeared to be as effective as combination treatments, and there was some evidence for superior efficacy of atypical antipsychotics. There was evidence supporting adjunctive antidepressant treatment for schizophrenic and schizoaffective patients who develop a major depressive syndrome after remission of acute psychosis, but there were mixed results for treatment of subsyndromal depression. There was little evidence to support adjunctive lithium for depressive symptoms and no evidence concerning its use for manic symptoms in patients with schizophrenia.Empirical data suggest that both groups of patients are best treated by optimizing antipsychotic treatment and that atypical antipsychotics may prove to be most effective. Adjunctive antidepressants may be useful for patients with major depression who are not acutely ill. Careful longitudinal assessment is required to ensure identification of primary mood disorders.

  View details for Web of Science ID 000081923300003

  View details for PubMedID 10450252

• Chromosome Workshop: Chromosomes 11, 14, and 15 VIth World Congress of Psychiatric Genetics Craddock, N., Lendon, C., Cichon, S., Culverhouse, R., Detera-Wadleigh, S., Devon, R., Faraone, S., Foroud, T., Gejman, P., Leonard, S., McInnis, M., Owen, M. J., Riley, B., Armstrong, C., Barden, N., Van Broeckhoven, C., Ewald, H., Folstein, S., Gerhard, D., Goldman, D., Gurling, H., Kelsoe, J., Levinson, D., Muir, W., Philippe, A., Pulver, A., Wildenauer, D. WILEY-LISS. 1999: 244–54

  Abstract

  This report describes linkage data presented at the Workshop on Chromosomes 11, 14, and 15 at the Sixth World Congress of Psychiatric Genetics in Bonn, Germany, together with relevant linkage data submitted to the chair and co-chair, and it is presented in the context of the previous literature concerning these chromosomes. We have attempted to collate current linkage data to provide a guide to potentially interesting findings on chromosomes 11, 14, and 15 for the phenotypes of bipolar disorder, schizophrenia, alcoholism, autism, and spelling and reading disability. We discuss methodological limitations and provide chromosome ideograms and tables summarizing findings to date. The most promising region currently appears to be 15q13-q15 in the region of the alpha 7 nicotinic receptor for the phenotype of schizophrenia (and, perhaps, more generally for functional psychosis). Additionally, 15q11-q13 in the region of GABRB3 holds interest as a potential site of a susceptibility gene for autism. Two regions on chromosome 11, 11p15 in the region of tyrosine hydroxylase gene and 11q22-q23 in the region of DRD2, continue to retain some interest for functional psychosis.

  View details for Web of Science ID 000080555500007

  View details for PubMedID 10374739

• Sixth World Congress of Psychiatric Genetics X Chromosome Workshop VIth World Congress of Psychiatric Genetics Paterson, A. D., Delisi, L., Faraone, S. V., GEJMAN, P. V., Goossens, D., Hovatta, I., Kaufmann, C. A., Klauck, S. M., Kunugi, H., Levinson, D. F., Mors, O., Norton, N., Smalley, S. L. WILEY-LISS. 1999: 279–86

  Abstract

  At the X chromosome workshop of the Sixth World Congress on Psychiatric Genetics, new data regarding psychiatric phenotypes and the X chromosome were presented. In the last year a number of groups have published linkage results for the X chromosome in schizophrenia, which provide no significant evidence for linkage. Presentations by groups from Cardiff, Oxford, State University of New York (SUNY), and Finland provide weak nonsignificant evidence for linkage of markers on the Xp11.4-p11.3, Xq21, and Xq26 with schizophrenia. However, the presence of a male-specific transmission ratio distorter (DMS1) that maps to Xp11.4-21.2 [Naumova et al., 1998: Am. J. Hum. Genet. 62:1493-1499] makes the interpretation of linkage findings in brother-brother pairs difficult in this region. Regarding bipolar affective disorder, little new data were reported, but previous reports provide evidence for linkage to Xq25-q26. Summary tables of linkage results for schizophrenia and bipolar disorder can be obtained from http://www.camh.net/ research/x-chromosome/. No linkage or transmission disequilibrium of polymorphisms of MAOA and MAOB in attention deficit hyperactivity disorder was seen. Negative results for transmission disequilibrium of polymorphisms of HTR2C and MAOA with autism were provided from German and Austrian families.

  View details for Web of Science ID 000080555500014

  View details for PubMedID 10374746

• Increased membrane-associated protein kinase C activity and translocation in blood platelets from bipolar affective disorder patients JOURNAL OF PSYCHIATRIC RESEARCH Wang, H. Y., Markowitz, P., Levinson, D., Undie, A. S., FRIEDMAN, E. 1999; 33 (2): 171-179

  Abstract

  recent investigations have suggested that the phosphoinositide (PI) signal transduction system may be involved in the pathophysiology of bipolar affective disorders. Earlier studies in our laboratory have implicated altered PKC-mediated phosphorylation in bipolar affective disorder and in the clinical action of lithium. In the present study, we compared PKC activity and its translocation in platelets from subjects with bipolar affective disorder and three other groups.subjects included 44 with bipolar disorder (acute manic episode), 25 with acute major depression, 23 with schizophrenia in acute exacerbation and 43 controls free of personal or family history of an Axis I disorder. Blood platelet membrane and cytosol PKC activity was measured before and after in vitro stimulation with serotonin (5-HT), thrombin and the direct PKC activator, PMA. In addition, we examined 5-HT-, thrombin- and PMA-elicited translocations of PKC isozymes from cytosol to the membrane in platelets of control subjects.in the basal state, manic subjects demonstrated higher membrane PKC activity than depressive and control subjects. The ratio of membrane to cytosol PKC activity was significantly higher in manic (1.10), as compared to control (0.84), depressed (0.93) or schizophrenic (0.93) subjects. Stimulation of platelets with 5-HT in vitro, resulted in greater membrane to cytosol ratio in the manic subjects compared to the three other groups. The responsiveness of platelets to PMA and thrombin was greater for manic subjects than for depressed and schizophrenic subjects, but not greater than the controls. In this measure both the schizophrenic and depressive groups were less active than controls. The results also demonstrate that platelets contain alpha-, beta-, delta- and zeta-PKC isozymes. While alpha- and beta-PKC isoforms were translocated from cytosol to membrane in response to serotonin, PMA and thrombin, serotonin also elicited the redistribution of delta-PKC and thrombin also activated zeta-PKC.the results demonstrate that a heightened PKC-mediated signal transduction is associated with acute mania and suggest a decreased transduction in patients with unipolar depression or schizophrenia.

  View details for Web of Science ID 000079476100011

  View details for PubMedID 10221749

• Burden and well-being of caregivers for the severely mentally ill: the role of coping style and social support SCHIZOPHRENIA RESEARCH Webb, C., Pfeiffer, M., Mueser, K. T., Gladis, M., Mensch, E., DeGirolamo, J., Levinson, D. F. 1998; 34 (3): 169-180

  Abstract

  Caregivers of persons with severe mental illness often experience a significant burden in coping with patients' symptoms. Several factors have been hypothesized to mediate the impact of caring for a mentally ill relative, including cognitive appraisal, coping strategies, and social support. The present study examined the relationships between these factors, and subjective burden and well-being in caregivers of persons with a severe mental illness. Higher levels of subjective burden were related to (1) greater perceived frequency of positive and negative symptom behaviors, (2) a tendency to use problem-focused oriented coping for dealing with negative symptom behaviors, and (3) a tendency not to use problem-solving oriented coping for dealing with positive symptom behaviors. Well-being was also related to lower perceived frequency of positive symptom behaviors and social support, but not to coping style. The implications of the findings for interventions designed to reduce caregiver subjective burden are discussed.

  View details for Web of Science ID 000077100500006

  View details for PubMedID 9850983

• A transmission disequilibrium and linkage analysis of D22S278 marker alleles in 574 families: further support for a susceptibility locus for schizophrenia at 22q12 SCHIZOPHRENIA RESEARCH Vallada, H., Curtis, D., Sham, P., Kunugi, H., Zhao, J. H., Murray, R., McGuffin, P., Nanko, S., Owen, M., Gill, M., Collier, D. A., Antonarakis, S., Housman, D., Kazazian, H., Nestadt, G., Pulver, A. E., Straub, R. E., MacLean, C. J., Walsh, D., Kendler, K. S., Delisi, L., Polymeropoulos, M., Coon, H., Byerley, W., Lofthouse, R., Gershon, E., GOLDIN, L., Freedman, R., Laurent, C., Bodeau-Pean, S., D'Amato, T., Jay, M., CAMPION, D., Mallet, J., Wildenauer, D. B., Lerer, B., Albus, M., Ackenheil, M., Ebstein, R. P., Hallmayer, J., Maier, W., Gurling, H., Curtis, D., Kalsi, G., Brynjolfsson, J., Sigmundson, T., Petursson, H., Blackwood, D., Muri, W., StClair, D., He, L., Maguire, S., Moises, H. W., Hwu, H. G., Yang, L., Wiese, C., Kristbjarnarson, H., Levinson, D. F., Mowry, B. J., Donis-Keller, H., Hayward, N. K., Crowe, R. R., Silverman, J. M., Nancarrow, D. J., Read, C. M. 1998; 32 (2): 115-121

  View details for Web of Science ID 000075204800007

• Chromosome 22 workshop. Psychiatric genetics Levinson, D. F., Coon, H. 1998; 8 (2): 115-120

  View details for PubMedID 9686434

• Genome scan of schizophrenia AMERICAN JOURNAL OF PSYCHIATRY Levinson, D. F., Mahtani, M. M., Nancarrow, D. J., Brown, D. M., Kruglyak, L., Kirby, A., Hayward, N. K., Crowe, R. R., Andreasen, N. C., Black, D. W., Silverman, J. M., Endicott, J., Sharpe, L., Mohs, R. C., Siever, L. J., Walters, M. K., Lennon, D. P., Jones, H. L., Nertney, D. A., Daly, M. J., Gladis, M., Mowry, B. J. 1998; 155 (6): 741-750

  Abstract

  The goal of this study was to identify chromosomal regions likely to contain schizophrenia susceptibility genes.A genomewide map of 310 microsatellite DNA markers with average spacing of 11 centimorgans was genotyped in 269 individuals--126 of them with schizophrenia-related psychoses--from 43 pedigrees. Nonparametric linkage analysis was used to assess the pattern of allele sharing at each marker locus relative to the presence of disease.Nonparametric linkage scores did not reach a genomewide level of statistical significance for any marker. There were five chromosomal regions in which empirically derived p values reached nominal levels of significance at eight marker locations. There were p values less than 0.01 at chromosomes 2q (with the peak value in this region at D2S410) and 10q (D10S1239), and there were p values less than 0.05 at chromosomes 4q (D4S2623), 9q (D9S257), and 11q (D11S2002).The results do not support the hypothesis that a single gene causes a large increase in the risk of schizophrenia. The sample (like most others being studied for psychiatric disorders) has limited power to detect genes of small effect or those that are determinants of risk in a small proportion of families. All of the most positive results could be due to chance, or some could reflect weak linkage (genes of small effect). Multicenter studies may be useful in the effort to identify chromosomal regions most likely to contain schizophrenia susceptibility genes.

  View details for Web of Science ID 000073952700006

  View details for PubMedID 9619145

• The molecular genetics of schizophrenia: an update AUSTRALIAN AND NEW ZEALAND JOURNAL OF PSYCHIATRY Mowry, B. J., Nancarrow, D. J., Levinson, D. F. 1997; 31 (5): 704-713

  Abstract

  This paper aims to summarise the latest molecular genetic findings in schizophrenia, while providing background information on a number of relevant methodological issues.Accumulative genetic data indicate that schizophrenia is a genetically complex disease with an unclear mode of transmission. The development and rapid progression of molecular genetics have provided a wide variety of methods to search for genes predisposing to human disease. The genetic basis for a number of the simpler diseases has been identified and characterised using these methods. More recently, progress has been made in identifying genes predisposing to the genetically more complex diseases such as diabetes mellitus, multiple sclerosis, bipolar disorder and schizophrenia.The latest findings on chromosomes 3, 6, 8, 13, 18 and 22 and on the X chromosome are reviewed.There is now suggestive support for three susceptibility loci (6p24-22, 8p22-21 and 22q12-q13.1) for schizophrenia, and it is likely that other regions will emerge from studies now in progress. Finding and then characterising genes within these loci will require long-term commitment and systematic efforts in clinical, laboratory and analytical fields.

  View details for Web of Science ID A1997YC40500012

  View details for PubMedID 9400877

• A linkage study of schizophrenia to markers within Xp11 near the MAOB gene. Psychiatry research Dann, J., DeLisi, L. E., Devoto, M., Laval, S., Nancarrow, D. J., Shields, G., Smith, A., Loftus, J., Peterson, P., Vita, A., Comazzi, M., Invernizzi, G., Levinson, D. F., Wildenauer, D., Mowry, B. J., Collier, D., Powell, J., Crowe, R. R., Andreasen, N. C., Silverman, J. M., Mohs, R. C., Murray, R. M., Walters, M. K., Lennon, D. P., Crow, T. J. 1997; 70 (3): 131-143

  Abstract

  A sex chromosome locus for psychosis has been considered on the basis of some sex differences in genetic risk and expression of illness, and an association with X-chromosome anomalies. Previous molecular genetic studies produced weak evidence for linkage of schizophrenia to the proximal short arm of the X-chromosome, while some other regions were not ruled out. Here we report an attempt to expand the Xp findings in: (i) a multicenter collaboration focusing on 92 families with a maternal pattern of inheritance (Study I), and (ii) an independent sample of 34 families unselected for parental mode of transmission (Study II). In the multicenter study, a parametric analysis resulted in positive lod scores (highest of 1.97 for dominant and 1.19 for recessive inheritance at a theta of 0.20) for locus DXS7, with scores below 0.50 for other markers in this region (MAOB, DXS228, and ARAF1). Significant allele sharing among affected sibling pairs was present at DXS7. In the second study, positive lod scores were observed at MAOB (highest of 2.16 at a theta of 0.05 for dominant and 1.64 at a theta of 0.00 for recessive models) and ALAS2 (the highest of 1.36 at a theta of 0.05 for a recessive model), with significant allele sharing (P = 0.003 and 0.01, respectively) at these two loci. These five markers are mapped within a small region of Xp11. Thus, although substantial regions of the X-chromosome have been investigated without evidence for linkage being found, a locus predisposing to schizophrenia in the proximal short arm of the X-chromosome is not excluded.

  View details for PubMedID 9211575

• Linkage study of schizophrenia to markers within Xp11 near the MAOB gene PSYCHIATRY RESEARCH Dann, J., DeLisi, L. E., Devoto, M., Laval, S., Nancarrow, D. J., Shields, G., Smith, A., Loftus, J., Peterson, P., Vita, A., Comazzi, M., Invernizzi, G., Levinson, D. F., Wildenauer, D., Mowry, B. J., Collier, D., Powell, J., Crowe, R. R., Andreasen, N. C., Silverman, J. M., Mohs, R. C., Murray, R. M., Walters, M. K., Lennon, D. P., Hayward, N. K., Albus, M., Lerer, B., Maier, W., Crow, T. J. 1997; 70 (3): 131-143

  View details for Web of Science ID A1997XG32600001

• Pragmatics and statistics in psychiatric genetics AMERICAN JOURNAL OF MEDICAL GENETICS Levinson, D. F. 1997; 74 (2): 220-222

  View details for Web of Science ID A1997WV79700024

  View details for PubMedID 9129731

• Linkage analysis of complex disorders with multiple phenotypic categories: Simulation studies and application to bipolar disorder data Genetic Analysis Workshop 10 (GAW10) Levinson, D. F. WILEY-BLACKWELL. 1997: 653–58

  Abstract

  The problem of linkage analysis of disorders with multiple possible phenotypes (diagnostic spectrum) is considered. A modification is proposed to Ott's [1994] method of down-weighting the contribution of broader diagnoses by reducing penetrance ratios for affected cases. A "robust weighting" strategy considers only the robustness of a set of ratios across a range of true genetic models. Practical models for lod-score analysis will typically employ a high penetrance ratio (> 10) for "core" cases, and ratios between 2 and 5 for broader cases. Results suggest that an additive parametric analysis correlates highly with dominant, recessive and nonparametric linkage (NPL) analyses. A weighted, additive model is then applied to a modified NIMH bipolar chromosome 18 data set (Genetic Analysis Workshop 10) and compared with NPL analyses under narrow and broad diagnostic models. The weighted model performed well. The introduction of similar weights into nonparametric analyses may prove more useful.

  View details for Web of Science ID 000071121800018

  View details for PubMedID 9433558

• Additional support for schizophrenia linkage on chromosomes 6 and 8: A multicenter study AMERICAN JOURNAL OF MEDICAL GENETICS Levinson, D. F., Wildenauer, D. B., Schwab, S. G., Albus, M., Hallmayer, J., Lerer, B., Maier, W., Blackwood, D., Muir, W., StClair, D., Morris, S., Moises, H. W., Yang, L., Kristbjarnarson, H., Helgason, T., Wiese, C., Collier, D. A., Holmans, P., Daniels, J., Rees, M., Asherson, P., Roberts, Q., Cardno, A., Arranz, M. J., Vallada, H., McGuffin, D., Owen, M. J., Pulver, A. E., Antonarakis, S. E., Babb, R., Blouin, J. L., deMarchi, N., Dombroski, B., Housman, D., Karayiorgou, M., Ott, J., Kasch, L., Kazazian, H., Lasseter, V. K., Loetscher, E., Luebbert, H., Nestadt, G., Ton, C., Wolyniec, P. S., Laurent, C., deChaldee, M., Thibaut, F., Jay, M., Samolyk, D., Petit, M., CAMPION, D., Mallet, J., Straub, R. E., MacLean, C. J., Easter, S. M., ONEILL, F. A., Walsh, D., Kendler, K. S., GEJMAN, P. V., Cao, Q. H., Gershon, E., Badner, J., Beshah, E., Zhang, J., Riley, B. P., Rajagopalan, S., MOGUDICARTER, M., Jenkins, T., Williamson, R., DeLisi, L. E., Garner, C., Kelly, M., Leduc, C., Cardon, L., Lichter, J., Harris, T., Loftus, J., Shields, G., Comasi, M., Vita, A., Smith, A., Dann, J., Joslyn, G., Gurling, H., Kalsi, G., Brynjolfsson, J., Curtis, D., Sigmundsson, T., Butler, R., Read, T., Murphy, P., Chen, A. C., Petursson, H., Byerley, B., Hoff, M., Holik, J., Coon, H., Nancarrow, D. J., Crowe, R. R., Andreasen, N., Silverman, J. M., Mohs, R. C., Siever, L. J., Endicott, J., Sharpe, L., Walters, M. K., Lennon, D. P., Hayward, N. K., Sandkuijl, L. A., Mowry, B. J., Aschauer, H. N., Meszaros, K., Lenzinger, E., Fuchs, K., Heiden, A. M., Kruglyak, L., Daly, M. J., Matise, T. C. 1996; 67 (6): 580-594

  View details for Web of Science ID A1996VV13800011

• Family burden of schizophrenia and bipolar disorder: Perceptions of relatives and professionals PSYCHIATRIC SERVICES Mueser, K. T., Webb, C., Pfeiffer, M., Gladis, M., Levinson, D. F. 1996; 47 (5): 507-511

  Abstract

  The study compared the burden that specific problem behaviors of patients with schizophrenia or bipolar disorder placed on relatives and evaluated the accuracy of mental health professionals' judgment of the burden.A questionnaire was developed to assess the burden of 20 common problem behaviors associated with manic, positive, and negative symptoms. The questionnaire was given to 48 relatives of patients with schizophrenia or bipolar disorder. In addition, 39 mental health professionals completed separate questionnaires indicating the amount of burden they believed relatives experienced due to these behaviors.Relatives of patients with bipolar disorder rated manic symptoms as more burdensome than did relatives of patients with schizophrenia, but relatives of patients in the two groups did not differ in their ratings of burden associated with positive or negative symptoms. Professionals' perceptions of the burden associated with manic symptoms were relatively accurate, but they tended to underestimate the burden of positive and negative symptoms experienced by relative of patients with bipolar disorder.Psychiatric diagnosis may be of limited value in understanding the burden relatives experience due to specific psychiatric symptoms. Professionals are encouraged to assess the burden that is associated with specific problem behaviors regardless of psychiatric diagnosis.

  View details for Web of Science ID A1996UJ28500011

  View details for PubMedID 8740492

• A combined analysis of D22S278 marker alleles in affected sib-pairs: Support for a susceptibility locus for schizophrenia at chromosome 22q12 AMERICAN JOURNAL OF MEDICAL GENETICS Gill, M., Vallada, H., Collier, D., Sham, P., Holmans, P., Murray, R., McGuffin, P., Nanko, S., Owen, M., Antonarakis, S., Housman, D., Kazazian, H., Nestadt, G., Pulver, A. E., Straub, R. E., MacLean, C. J., Walsh, D., Kendler, K. S., Delisi, L., Polymeropoulos, M., Coon, H., Byerley, W., Lofthouse, R., Gershon, E., Golden, L., Crow, T., Freedman, R., Laurent, C., BodeauPean, S., DAMATO, T., Jay, M., CAMPION, D., Mallet, J., Wildenauer, D. B., Lerer, B., Albus, M., Ackenheil, M., Ebstein, R. P., Hallmayer, J., Maier, W., Gurling, H., Curtis, D., Kalsi, G., Brynjolfsson, J., Sigmundson, T., Petursson, H., Blackwood, D., Muir, W., StClair, D., He, L., Maguire, S., Moises, H. W., Hwu, H. G., Yang, L., Wiese, C., Tao, L., Liu, X. H., KRISTBJARNASON, H., Levinson, D. F., Mowry, B. J., DONISKELLER, H., Hayward, N. K., Crowe, R. R., Silverman, J. M., Nancarrow, D. J., Read, C. M. 1996; 67 (1): 40-45

  View details for Web of Science ID A1996TY40300007

• Penetrance of schizophrenia-related disorders in multiplex families after correction for ascertainment GENETIC EPIDEMIOLOGY Levinson, D. F., Mowry, B. J., Sharpe, L., Endicott, J. 1996; 13 (1): 11-21

  Abstract

  Penetrance of schizophrenia and related disorders was calculated in 27 multiplex pedigrees ascertained by a consistent set of screening and selection criteria. The rationale for the study was that single major locus linkage models are frequently used on a pragmatic basis to analyze data for schizophrenia which is most likely to have a polygenic mechanism. Penetrance estimates assuming Mendelian inheritance represent maximum values and thus can provide guidance for construction of appropriate linkage models. Four diagnostic models were considered: narrow (schizophrenia and chronic schizoaffective disorder), intermediate (including other non-affective psychoses), broad (including schizotypal and paranoid personality disorders), and broad + suspected (including suspected schizophrenia spectrum disorders). Penetrance was calculated in the youngest affected adult sibship, under both dominant and recessive inheritance assumptions, either without correction, or with a correction that excluded individuals necessary to meet pedigree selection criteria. Without correction, penetrance values ranged from 0.70 to 0.90 assuming dominant and 1.0 to > 1.0 assuming recessive inheritance. After correction, the ranges were 0.30-0.51 for dominant and 0.47-0.59 for recessive models. The corrected values are likely to be overestimates given that the penetrance of any one locus in a multilocus model must be lower. It is suggested that lod score analyses of schizophrenia should attempt to derive information primarily from affected diagnoses, because information derived from unaffecteds under high penetrance models is likely to be spurious.

  View details for Web of Science ID A1996TY22700002

  View details for PubMedID 8647375

• FLUPHENAZINE PLASMA-LEVELS, DOSAGE, EFFICACY, AND SIDE-EFFECTS AMERICAN JOURNAL OF PSYCHIATRY Levinson, D. F., Simpson, G. M., Lo, E. S., COOPER, T. B., Singh, H., Yadalam, K., STEPHANOS, M. J. 1995; 152 (5): 765-771

  Abstract

  The authors sought to determine whether fluphenazine dose or plasma level predicts clinical improvement or side effects during acute treatment.Oral fluphenazine was given in fixed, randomized, double-blind doses (10, 20, or 30 mg/day) for 4 weeks to 72 inpatients with acute schizophrenic exacerbations. Outcome measures included percentage improvement in ratings of positive symptoms (hallucinations, delusions, and thought disorder), percentage improvement in negative symptoms, and maximum score for extrapyramidal symptoms. Response was defined as an improvement in positive symptoms of 40% or more.The 42 responders had a shorter duration of illness, less chronic course, and lower rate of akathisia. Plasma level and dose did not differentiate responders and nonresponders, but they did predict percentage improvement in positive symptoms within the responder subgroup. Akathisia was more common and extrapyramidal symptoms were more severe at higher plasma levels.Responders showed the greatest improvement at fluphenazine plasma levels above 1.0 ng/ml and doses above 0.20-0.25 mg/kg per day. Since the literature suggests that optimal plasma levels are similar during acute and maintenance treatment, monitoring of plasma levels may thus be useful. Conditions for applying the "responder-only" analytic strategy in future studies are discussed.

  View details for Web of Science ID A1995QV32400016

  View details for PubMedID 7726317

• Detection of vulnerability loci by association and sib-pair methods Genetic Analysis Workshop 9 - Analysis of Complex Oligogenic Traits (GAW9) Levinson, D. F. WILEY-LISS. 1995: 631–35

  Abstract

  A haplotype-based haplotype relative risk (HHRR) analysis of simulated data for 200 affected offspring and their parents (Genetic Analysis Workshop 9, Problem 1) detected linkage disequilibrium at 2 of 360 marker loci. An additive model was suggested but not proven by haplotypes of affected vs. unaffected offspring. These findings were consistent with the generating model. Affected sib pair analysis failed to detect additional loci. Discussion among workshop participants suggested that the chi-square test used here (2 [transmitted vs. nontransmitted] x n [alleles] for each locus) was invalid because of the nonindependence of proportions of transmitted alleles. In post-workshop analyses, transmission disequilibrium tests (TDTs) for each allele at each locus detected only the true associations if p values were corrected by one of two methods: Bonferroni correction for 2,035 TDTs, or correcting each test for n (number of tests at the locus) minus 1 and then for the number of loci tested. Screening loci for linkage disequilibrium requires careful attention to correction for multiple comparisons.

  View details for Web of Science ID A1995TP13700016

  View details for PubMedID 8787985

• DELUSIONS IN SCHIZOPHRENIA SPECTRUM DISORDERS - DIAGNOSTIC ISSUES SCHIZOPHRENIA BULLETIN Gladis, M. M., Levinson, D. F., Mowry, B. J. 1994; 20 (4): 747-754

  Abstract

  Family studies of schizophrenia frequently include relatives of schizophrenia probands with diagnoses falling within the schizophrenia spectrum. As part of an ongoing genetic linkage study of schizophrenia, the authors examined case material from 50 relatives (of schizophrenia probands) who received a DSM-III-R diagnosis of a nonaffective psychotic disorder or schizotypal or paranoid personality disorder. Eleven exhibited episodic or chronic delusions that resulted in diagnostic dilemmas, often arising from issues pertaining to the classification of delusional phenomena. Four of these cases are presented here. Unusual beliefs were often difficult to classify as odd beliefs versus full delusions, brief/transient versus persistent delusions, bizarre versus non-bizarre delusions. It is suggested that these might be considered continuous rather than dichotomous dimensions. Several possible implications for genetic studies of schizophrenia are discussed.

  View details for Web of Science ID A1994PW03300012

  View details for PubMedID 7701280

• SCHIZOTYPAL AND PARANOID PERSONALITY-DISORDER IN THE RELATIVES OF PATIENTS WITH SCHIZOPHRENIA AND AFFECTIVE-DISORDERS - A REVIEW SCHIZOPHRENIA RESEARCH Webb, C. T., Levinson, D. F. 1993; 11 (1): 81-92

  Abstract

  This review considers the possible familial relationship of schizotypal and paranoid personality disorders (SPD, PPD) to schizophrenia (SCZ) and affective disorders (AD). There have been few controlled studies on familial risk of SPD and PPD based on direct semi-structured interviews of relatives, blind to proband diagnosis. Three of six studies reported increased familial risk of SPD for SCZ probands, but with considerable variability in estimates of this risk. None of four studies reported a significant relationship between AD and familial SPD. There is substantial but less consistent evidence for a familial relationship between PPD and SCZ: three of six studies supported such a relationship, but one large study reported increased familial risk of PPD for AD and not for SCZ probands. There is also some evidence that negative symptoms are most characteristic of SPD in relatives of SCZ probands. Also discussed are issues concerning the adequacy of current criteria for defining schizophrenia spectrum pathology, and of diagnostic methods in this area.

  View details for Web of Science ID A1993MJ76600011

  View details for PubMedID 8297808

• CONTINUITY AND DISCONTINUITY OF AFFECTIVE-DISORDERS AND SCHIZOPHRENIA - RESULTS OF A CONTROLLED FAMILY STUDY ARCHIVES OF GENERAL PSYCHIATRY Maier, W., Lichtermann, D., Minges, J., Hallmayer, J., Heun, R., Benkert, O., Levinson, D. F. 1993; 50 (11): 871-883

  Abstract

  It is widely acknowledged that the genetic diatheses for schizophrenia and affective disorders are independent. However, there are increasing doubts about this classic view, and empirical evidence for a dichotomy of these two prototypes of functional psychoses is limited. A controlled family study of consecutive admissions was conducted to determine whether familial risks for schizophrenic (SCZ) and affective disorders were independent or overlapping.Index probands met Research Diagnostic Criteria for SCZ (n = 146), schizoaffective (SA [n = 115]), bipolar (BP [n = 80]), or unipolar major depressive (UP [n = 184]) disorder. Comparison probands met Research Diagnostic Criteria for alcoholism (n = 64) or were sampled from the general population (n = 109). A total of 2845 first-degree relatives were blindly diagnosed from interview, informant, and/or record data, with direct interviews completed in 2070 (82% of living first-degree relatives).By Cox's proportional hazards analysis, SCZ, SA, BP, and UP disorders were familial, in that each group of relatives had an increased lifetime morbid risk (vs those with alcoholism and those from the general population) for the proband's diagnosis. The SCZ and BP disorders were transmitted independently: only probands with manic disorders (BP or SA-BP subtype) showed increased familial risks of BP disorder, and only probands with prominent SCZ features (SCZ or SA) showed increased familial risks of SCZ disorder. However, SCZ probands had an increased familial risk for UP disorder (as did SA, BP, and UP probands) and for the SA-UP subtype. Aggregation of depression in families of SCZ probands could not be explained by the subtype of depression, broad or narrow definition of SCZ disorder, presence or absence of history of depression in SCZ probands, whether onset of depression in a relative occurred before or after onset of a proband's SCZ disorder, or assortative mating.These data suggest that there could be a familial relationship between the predispositions to schizophrenia and to major depression. We discuss a number of alternative hypotheses about the nature of this possible relationship.

  View details for Web of Science ID A1993MG30600004

  View details for PubMedID 8215813

• POWER TO DETECT LINKAGE WITH HETEROGENEITY IN SAMPLES OF SMALL NUCLEAR FAMILIES AMERICAN JOURNAL OF MEDICAL GENETICS Levinson, D. F. 1993; 48 (2): 94-102

  Abstract

  Computer simulation methods were used to investigate the power of genetically homogeneous or heterogeneous samples of nuclear families to detect linkage of a rare dominant disease allele to flanking DNA markers (three-point analysis, admixture text). Phase was assumed to be unknown (no grandparents available), and unaffected siblings were not considered. A sample of 95 families with an ill parent and two ill offspring, or 45 families with three ill offspring, demonstrated 90% power to detect a lod score of 3.0 when 50% of families were assumed to be segregating for a disease allele located midway between two DNA markers (PIC = .70) that were .05 M apart. When the proportion of linked families (alpha) = .25, 90% power required 380 and 160 families, respectively. For alpha < .25, samples size requirements become prohibitive. Issues are reviewed concerning the use of the admixture test in the case of more complex disease models. Screening of the genome with adequate sample sizes for low values of alpha is likely to require multiple large collaborative efforts.

  View details for Web of Science ID A1993LP02700007

  View details for PubMedID 8362931

• GENETIC-LINKAGE AND SCHIZOPHRENIA - METHODS, RECENT FINDINGS AND FUTURE-DIRECTIONS AUSTRALIAN AND NEW ZEALAND JOURNAL OF PSYCHIATRY Mowry, B. J., Levinson, D. F. 1993; 27 (2): 200-218

  Abstract

  Family, twin and adoption studies have shown that familial clustering in schizophrenia is predominantly due to genetic factors. On the basis of segregation analyses of the illness distribution in relatives of patients, various models of the mode of transmission have been put forward but as yet there is no consensus. Linkage analysis based on molecular genetic techniques provides a more direct approach to discovering precisely what is inherited (one gene, a small number of genes or many genes?) that generates vulnerability to schizophrenia. To date there has been no sufficiently replicated finding of one or more linked genes and many methodological complexities remain. However, the rate of progress in addressing these issues gives hope that genetic linkage analysis of schizophrenia will provide some answers.

  View details for Web of Science ID A1993LM59300003

  View details for PubMedID 8363530

• ALTERED PLATELET PROTEIN-KINASE-C ACTIVITY IN BIPOLAR AFFECTIVE-DISORDER, MANIC EPISODE BIOLOGICAL PSYCHIATRY FRIEDMAN, E., Wang, H. Y., Levinson, D., CONNELL, T. A., Singh, H. 1993; 33 (7): 520-525

  Abstract

  Protein kinase C (PKC) activity and PKC translocation in response to serotonin were investigated in platelets obtained from bipolar affective disorder subjects before and during lithium treatment. Ratios of platelet membrane-bound to cytosolic PKC activities were elevated in the manic subjects. In addition, serotonin-elicited platelet PKC translocation was found to be enhanced in those subjects. Lithium treatment for up to 2 weeks resulted in a reduction in cytosolic and membrane-associated PKC activities and in an attenuated PKC translocation in response to serotonin. These preliminary results suggest that alteration in platelet PKC is associated with the manic phase of bipolar illness. The results also suggest that lithium treatment reduces the sensitivity of platelets to PKC translocation induced by activation of serotonin-2 receptors.

  View details for Web of Science ID A1993LD10300006

  View details for PubMedID 8513036

• THE TREATMENT AND MANAGEMENT OF NEUROLEPTIC MALIGNANT SYNDROME PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY Gratz, S. S., Levinson, D. F., Simpson, G. M. 1992; 16 (4): 425-443

  Abstract

  1. The neuroleptic malignant syndrome was initially described as a disorder specifically related to neuroleptic usage with frequent fatal outcome. The observations of variant or mild cases of this syndrome as well as case reports on neuroleptic-malignant-like syndromes in the absence of neuroleptics raises the issue of the usefulness of this terminology and highlights the potential for inappropriate management of this "malignant" syndrome. It has been suggested that hypothalamic thermoregulatory responses may involve an interplay among noradrenergic, cholinergic and serotonergic pathways. Out treatment strategy is based on the pharmacology of neuroleptics and empirical data, verified in our own clinical practice and considers that it is often difficult to determine whether certain physiologic states are a consequence to or specific triggering factors. 2. If a patient's temperature is less than 101, we emphasize vigorous treatment with anticholinergic agents, while simultaneously assessing the psychiatric need for neuroleptics versus medical risks. Given that the severe rigidity of NMS represents severe extrapyramidal effects of dopamine blockade, there is no reason to withhold anticholinergics in the absence of higher temperatures. Neuroleptics can be stopped at the discretion of the clinician even during circumstances when there is fever below 101. 3. In cases of severe EPS with fever greater than or equal to 101, we recommend stopping neuroleptics, treating with anticholinergics and starting with dopamine agonists. In the event of a poor response to dopamine agonists, a brief trial of dantrolene and/or benzodiazepines is recommended. Dantrolene should not be introduced for prolonged periods, since abnormal liver function studies have been observed in approximately 1.8% of patients. 4. In cases of extreme hyperpyrexia (fever greater than 103), clinicians should consider transfer to an ICU or another medical support. Extreme temperatures have been associated with potentially irreversible cerebellar or other brain damage, if not aggressively treated. If neuroleptics are later indicated, a 2 week interval after resolution of symptoms should be maintained before reinstituting neuroleptics. 5. In patients with severe EPS without fever, we emphasize aggressive use of anticholinergic therapy, while simultaneously considering the psychiatric need for neuroleptics versus medical risks. In all cases where a patient's swallowing, respirations or physical mobility is severely compromised, we suggest stopping neuroleptics. Anticholinergic agents should be continued for 7 days after neuroleptics are stopped. If anticholinergic agents are unsuccessful after 2-3 dosages, dopamine agonists may be added, while simultaneously monitoring vital signs. It should be emphasized that severe EPS sometimes takes days to improve even after neuroleptic cessation and the addition of anticholinergics.(ABSTRACT TRUNCATED AT 400 WORDS)

  View details for Web of Science ID A1992HY86500001

  View details for PubMedID 1641490

• TIMING OF ACUTE CLINICAL-RESPONSE TO FLUPHENAZINE BRITISH JOURNAL OF PSYCHIATRY Levinson, D. F., Singh, H., Simpson, G. M. 1992; 160: 365-371

  Abstract

  The time course of clinical improvement was studied in 41 schizophrenic and schizoaffective acute in-patients treated for 28 days with 10, 20 or 30 mg/day of oral fluphenazine hydrochloride in a double-blind, randomised study. Significant improvement was seen in the four BPRS factors: thinking disturbance, hostile-suspiciousness, withdrawal-retardation and anxious depression. The first two of these factors were improved by day 5. Significant improvement was seen up to day 22 for three of the four factors, but without significant improvement during the last week (although scores continued to drop). The half of the sample showing greater overall improvement did not improve faster than the sample as a whole. These more improved subjects did not differ significantly from the less improved subjects in the thinking disturbance factor until day 15, suggesting that at least a two-week neuroleptic trial would be necessary to begin to differentiate more and less responsive patients. The longer-term course of improvement cannot be determined from these data. The withdrawal-retardation and anxious depression factors showed their greatest improvement later than the 'positive' symptom factors, suggesting that the former may improve as a result of change in the latter.

  View details for Web of Science ID A1992HJ10300009

  View details for PubMedID 1562863

• SKIN-CONDUCTANCE ORIENTING RESPONSE IN UNMEDICATED RDC SCHIZOPHRENIC, SCHIZOAFFECTIVE, DEPRESSED, AND CONTROL SUBJECTS BIOLOGICAL PSYCHIATRY Levinson, D. F. 1991; 30 (7): 663-683

  Abstract

  In an evaluation of the skin conductance orienting response (SCOR) as a marker for schizophrenia, skin conductance (SC) activity was studied in 36 Research Diagnostic Criteria (RDC) schizophrenic (SCZ), 17 schizoaffective--mainly schizophrenic (SA), 24 depressed (DEP), and 25 psychiatrically well control (CONT) subjects. All subjects were unmedicated. Data are presented from four paradigms: a series of 1 s 70 dB tones in a no-task habituation paradigm; a similar series of 103 dB tones; a series of tones with a button-press (reaction time) task; and a loud white noise stimulus (without task). The proportion of SCOR nonresponse to the first 70 dB tone was 39% for SCZ, 82% for SA, 46% for DEP, and 36% for CONT subjects; the response rate for SA subjects was significantly lower than for all other groups. The CONT group was less responsive than in most previous studies. SCZ subjects did not show increased responsivity to more intense and to task-relevant stimuli, although SA subjects did show such increases. DEP subjects showed some evidence of autonomic hyperarousal (higher tonic SC level, trend toward more spontaneous SC responses). The overall pattern of results does not support SCOR to neutral, moderate-intensity tones as a specific marker for schizophrenia, although there was some evidence for a generalized decrease in autonomic responsivity to stimuli.

  View details for Web of Science ID A1991GH68900003

  View details for PubMedID 1683584

• PHARMACOLOGICAL TREATMENT OF SCHIZOPHRENIA CLINICAL THERAPEUTICS Levinson, D. F. 1991; 13 (3): 326-352

  Abstract

  The literature on the pharmacologic treatment of schizophrenia and schizoaffective disorders is reviewed (116 references). All clinically active antipsychotic drugs share the ability to block postsynaptic dopamine receptors in the central nervous system. Their potencies vary, chlorpromazine and thioridazine being the least potent and fluphenazine and haloperidol the most potent. The adverse effects of the neuroleptics include acute dystonia, parkinsonian symptoms (extrapyramidal symptoms), akathisia, tardive dyskinesia, and tardive dystonia. When used at equipotent doses, all classic neuroleptics now available are equally effective in the treatment of schizophrenia. Choice of drug is based on adverse effects and patient response. The neuroleptics are effective in most acute exacerbations of schizophrenia and for the prevention or mitigation of relapse. Their effects are more pronounced on the positive symptoms of schizophrenia, such as hallucinations, delusions, disordered thinking, and paranoia, than on the negative symptoms, such as deficits in social interaction, emotional expression, and motivation. Strategies for acute and maintenance treatment and for the management of treatment-resistant patients are reviewed. The pharmacology and clinical use of the newer atypical neuroleptics, particularly clozapine, and their adverse effects are discussed.

  View details for Web of Science ID A1991FV21200001

  View details for PubMedID 1683269

• DEFINING THE SCHIZOPHRENIA SPECTRUM - ISSUES FOR GENETIC-LINKAGE STUDIES SCHIZOPHRENIA BULLETIN Levinson, D. F., Mowry, B. J. 1991; 17 (3): 491-514

  Abstract

  Genetic linkage studies of schizophrenia depend on accurate psychiatric diagnosis of relatives within multiply affected families. Each investigator makes a series of explicit or implicit decisions to define which relatives will be assumed to share a schizophrenia-related genotype, that is, who is an "affected relative." In this article we delineate issues that we believe should be considered in such studies and review the relevant literature. Issues include criteria for selecting probands; whether broader criteria should be used to select affected relatives; approaches to including or excluding diagnoses for which family study data suggest a relationship to schizophrenia or to affective disorders or other psychiatric disorders; clarification of diagnostic hierarchy; and issues related to substance abuse and neurological disorders. Also discussed are whether relatives without spectrum diagnoses should be considered unaffected or undiagnosed in linkage analyses, how bilateral familial affectedness should be defined, and provision for independent review of study diagnoses. As an illustration, the clinical model for the authors' schizophrenia linkage study is described.

  View details for Web of Science ID A1991GF46700019

  View details for PubMedID 1947874

• ACUTE DYSTONIA DURING FIXED-DOSE NEUROLEPTIC TREATMENT JOURNAL OF CLINICAL PSYCHOPHARMACOLOGY Singh, H., Levinson, D. F., Simpson, G. M., Lo, E. S., FRIEDMAN, E. 1990; 10 (6): 389-396

  Abstract

  Eighty-six patients with acute psychotic exacerbations were treated with fixed dosage regimens of oral fluphenazine up to 10-30 mg/day in randomized, double-blind studies. Dystonic reactions occurred in 33.8% of the subjects at risk. Of these, 58% occurred by the third day, 88% by the fourth day, and 100% by the ninth day of treatment; most occurred later in the interdose interval. Significant predictors of dystonic reactions were higher fluphenazine mg/kg dosage and younger age. There was a trend toward a lower risk of dystonia in patients who received amobarbital sodium for agitation. Results are discussed in relation to possible mechanisms of neuroleptic-induced dystonia.

  View details for Web of Science ID A1990EN64100003

  View details for PubMedID 2286708

• SINGLE-DOSE PHARMACOKINETICS OF FLUPHENAZINE AFTER FLUPHENAZINE DECANOATE ADMINISTRATION JOURNAL OF CLINICAL PSYCHOPHARMACOLOGY Simpson, G. M., YADALAM, K. G., Levinson, D. F., STEPHANOS, M. J., Lo, E. S., COOPER, T. B. 1990; 10 (6): 417-421

  Abstract

  Fluphenazine decanoate is commonly used as part of maintenance treatment of schizophrenia, but its pharmacokinetics are poorly understood. We administered a single intramuscular dose of fluphenazine decanoate to nine patients and found that plasma fluphenazine level did not decline to 50% of the peak level by day 26 in any of the patients. This means that it has a long half-life measurable in months rather than weeks.

  View details for Web of Science ID A1990EN64100008

  View details for PubMedID 2286711

• FLUPHENAZINE DOSE, CLINICAL-RESPONSE, AND EXTRAPYRAMIDAL SYMPTOMS DURING ACUTE TREATMENT ARCHIVES OF GENERAL PSYCHIATRY Levinson, D. F., Simpson, G. M., Singh, H., Yadalam, K., Jain, A., STEPHANOS, M. J., Silver, P. 1990; 47 (8): 761-768

  Abstract

  Fifty-three patients with acute exacerbations of Research Diagnostic Criteria schizophrenic, schizoaffective (mainly schizophrenic), and other nonaffective psychoses completed 24 or 28 days of treatment with randomized, fixed, double-blind doses of 10, 20, or 30 mg of oral fluphenazine hydrochloride daily. In the sample as a whole, improvement was not predicted by dose but was negatively related to duration of illness and of lifetime hospitalization, and to the presence of akathisia during the study (which was unrelated to chronicity). But among patients showing 40% or greater improvement in positive symptoms, percent improvement was predicted by dose and dose per kilogram of body weight; this was not the case for negative symptoms. Severity of acute extrapyramidal symptoms (excluding acute dystonia, dyskinesia, and akathisia) was significantly correlated with dosage per kilogram. Doses greater than 0.2 mg/kg per day were associated with greater clinical improvement but also with a high incidence of extrapyramidal symptoms; doses over 0.3 mg/kg per day were associated with more severe extrapyramidal symptoms. These preliminary results suggest that there is a linear relationship between fluphenazine dosage and acute outcome, and that this relationship is observed in patients whose conditions improve to a criterion level. It is suggested that the nonresponder group may include many patients in whom dose is not relevant because they are unable (for a variety of reasons) to respond to the study treatment conditions; excluding them from analysis may allow a significant dose-response relationship to be observed. Akathisia deserves further study as a possible predictor of nonresponse.

  View details for Web of Science ID A1990DT45700008

  View details for PubMedID 2378547

• PREVALENCE OF SUBSTANCE ABUSE IN SCHIZOPHRENIA - DEMOGRAPHIC AND CLINICAL CORRELATES SCHIZOPHRENIA BULLETIN Mueser, K. T., Yarnold, P. R., Levinson, D. F., Singh, H., Bellack, A. S., Kee, K., Morrison, R. L., YADALAM, K. G. 1990; 16 (1): 31-56

  Abstract

  Methodological issues involved in assessing the prevalence of substance abuse in schizophrenia are discussed, and previous research in this area is comprehensively reviewed. Many studies suffer from methodological shortcomings, including the lack of diagnostic rigor, adequate sample sizes, and simultaneous assessment of different types of substance abuse (e.g., stimulants, sedatives). In general, the evidence suggests that the prevalence of substance abuse in schizophrenia is comparable to that in the general population, with the possible exceptions of stimulant and hallucinogen abuse, which may be greater in patients with schizophrenia. Data are presented on the association of substance abuse with demographics, diagnosis, history of illness, and symptoms in 149 recently hospitalized DSM-III-R schizophrenic, schizophreniform, and schizoaffective disorder patients. Demographic characteristics were strong predictors of substance abuse, with gender, age, race, and socioeconomic status being most important. Stimulant abusers tended to have their first hospitalization at an earlier age and were more often diagnosed as having schizophrenia, but did not differ in their symptoms from nonabusers. A history of cannabis abuse was related to fewer symptoms and previous hospitalizations, suggesting that more socially competent patients were prone to cannabis use. The findings show that environmental factors may be important determinants of substance abuse among schizophrenic-spectrum patients and that clinical differences related to abuse vary with different types of drugs.

  View details for Web of Science ID A1990CV84100007

  View details for PubMedID 2333480

• What HMOs should tell their subscribers, and what you can do about it. Consultant Levinson, D. F. 1989; 29 (5): 118-?

  Abstract

  All health maintenance organization (HMO) plans try to control costs by restricting choice of physicians and regulating utilization of service. Have some plans gone too far? Patient and physician can become caught in a complex web of gatekeepers and capitation arrangements, withholds, bonuses, and penalties. Patients are almost always unaware of the details of these pressures on the physician. For the free market system to operate, potential subscribers should receive all of the facts about their HMOs. This article offers practical suggestions for concerned physicians, including information about proposals for legislative requirements of disclosure statements and a list of questions patients should ask before joining an HMO.

  View details for PubMedID 10292916

• TWIN STUDIES AND GENETIC MODELS OF SCHIZOPHRENIA ARCHIVES OF GENERAL PSYCHIATRY Levinson, D. F. 1988; 45 (9): 876-877

  View details for Web of Science ID A1988P938300015

  View details for PubMedID 3415430

• NEUROLEPTIC PLASMA-LEVEL MAY PREDICT RESPONSE IN PATIENTS WHO MEET A CRITERION FOR IMPROVEMENT ARCHIVES OF GENERAL PSYCHIATRY Levinson, D. F., Simpson, G. M., Singh, H., COOPER, T. B., LASKA, E. V., MIDHA, K. K. 1988; 45 (9): 878-879

  View details for Web of Science ID A1988P938300017

  View details for PubMedID 3415431

• EXACERBATION OF PANIC DISORDER DURING PROPRANOLOL THERAPY JOURNAL OF CLINICAL PSYCHOPHARMACOLOGY Levinson, D. F., Acquaviva, J. 1988; 8 (3): 193-195

  Abstract

  Two patients experienced new onset or worsening of panic disorder during treatment with propranolol for tachycardia or palpitations associated with a diagnosis of mitral valve prolapse. Both patients had a family history of panic disorder; one also had a family history of mitral valve prolapse and depression. As antidepressant drugs can treat both depression and panic disorder, it would not be inconsistent that propranolol might exacerbate either disorder. Other possible interpretations of these two cases are discussed.

  View details for Web of Science ID A1988N573200007

  View details for PubMedID 3379142

• TOWARD FULL DISCLOSURE OF REFERRAL RESTRICTIONS AND FINANCIAL INCENTIVES BY PREPAID HEALTH PLANS NEW ENGLAND JOURNAL OF MEDICINE Levinson, D. F. 1987; 317 (27): 1729-1731

  View details for Web of Science ID A1987L432700008

  View details for PubMedID 3696180

• SCHIZOAFFECTIVE MANIA RECONSIDERED AMERICAN JOURNAL OF PSYCHIATRY Levinson, D. F., LEVITT, M. E. 1987; 144 (4): 415-425

  Abstract

  Schizoaffective mania refers to a heterogeneous group of disorders characterized by mixtures of schizophrenic and manic (or bipolar) symptoms. Of the proposed diagnostic criteria, the Research Diagnostic Criteria (RDC) most clearly distinguish relevant subgroups. Family, clinical, and treatment studies suggest that the RDC's mainly affective subtype of schizoaffective mania is a variant of psychotic bipolar disorder. Limited available data suggest that the mainly schizophrenic subtype has a poorer prognosis and includes cases more closely related to schizophrenia. Schizoaffective mania also overlaps with proposed categories such as reactive and cycloid psychosis. It is premature to assume that all schizoaffective manic disorder represents a bipolar variant. Further studies that differentiate patients according to subtype, drug response, and course are needed.

  View details for Web of Science ID A1987G674800001

  View details for PubMedID 3551637

• SEQUELAE OF NEUROLEPTIC MALIGNANT SYNDROME BIOLOGICAL PSYCHIATRY Levinson, D. F., Simpson, G. 1987; 22 (2): 237-238

  View details for Web of Science ID A1987F562000018

  View details for PubMedID 3814675

• METHYLPHENIDATE CHALLENGE IN A MANIC BOY BIOLOGICAL PSYCHIATRY Schmidt, K., Delaney, M. A., Jensen, M., Levinson, D. F., LeWitt, M. 1986; 21 (11): 1107-1109

  View details for Web of Science ID A1986D430400024

  View details for PubMedID 3741930

• NEUROLEPTIC-INDUCED EXTRAPYRAMIDAL SYMPTOMS WITH FEVER - HETEROGENEITY OF THE NEUROLEPTIC MALIGNANT SYNDROME ARCHIVES OF GENERAL PSYCHIATRY Levinson, D. F., Simpson, G. M. 1986; 43 (9): 839-848

  Abstract

  From 39 reported cases of the "neuroleptic malignant syndrome," three groups were identified: those with concurrent medical problems that could cause fever that accompanied the extrapyramidal symptoms; those with medical problems less clearly related to fever; and those without other medical disorders. Dehydration, infection, pulmonary embolus, and rhabdomyolysis were the common complications of untreated extrapyramidal symptoms. Three patients died, all with medical complications. In 14 cases, no medical cause of fever was identified. Hypotheses about mechanisms for fever include psychiatric illness, disruption of dopaminergic aspects of thermoregulation, and peripheral and central effects on muscle contraction leading to excess heat production. Neuroleptic-induced rigidity should be treated vigorously, with prompt discontinuation of neuroleptic therapy and administration of dopamine agonists in severe cases with or without fever. The cases of extrapyramidal symptoms with fever are too heterogeneous to justify the assumption of a unitary and "malignant" syndrome.

  View details for Web of Science ID A1986D779300003

  View details for PubMedID 2875701

• THE SKIN-CONDUCTANCE ORIENTING RESPONSE IN NEUROLEPTIC-FREE SCHIZOPHRENICS - REPLICATION OF THE SCORING CRITERIA EFFECT BIOLOGICAL PSYCHIATRY Levinson, D. F., Edelberg, R., Maricq, H. R. 1985; 20 (6): 646-653

  Abstract

  It has been suggested that the use of invalid scoring criteria might be responsible for the finding of excessive nonhabituation of the skin conductance orienting response (SCOR) in schizophrenia. Certain criteria may confuse SCOR and spontaneous SC activity in subjects with high rates of the latter (Levinson et al. 1984). To replicate this finding, data were reanalyzed from a study of 25 neuroleptic-free schizophrenic patients and 23 normal male subjects. Analysis of response latency and amplitude during a habituation paradigm of 11 78.5-dB tones confirmed the predictions. Broad scoring criteria (SCOR onset 1-5 sec poststimulus, and a three-no-response-trials habituation criterion) produced significantly different habituation scores than more restrictive criteria (1.6-3.0 sec latency window and a two-trials habituation criterion). Nonhabituation was scored in five patients and six normals by the former criteria, but in no patient and one normal by the latter. Nonhabituators, defined by using the broad criteria, had higher rates of spontaneous activity. The narrow latency window contained significantly more responses than could be explained by the spontaneous activity rate, but this was not true for the added time permitted by the broad window. It is concluded that the use of more restrictive scoring criteria may help to clarify the validity of SCOR nonresponse or hyporesponse as a marker for a type of schizophrenic illness.

  View details for Web of Science ID A1985AMZ9100008

  View details for PubMedID 3995111

• SCORING CRITERIA FOR RESPONSE LATENCY AND HABITUATION IN ELECTRODERMAL RESEARCH - A CRITIQUE PSYCHOPHYSIOLOGY Levinson, D. F., Edelberg, R. 1985; 22 (4): 417-426

  View details for Web of Science ID A1985ANH4800006

  View details for PubMedID 4023153

• THE ORIENTING RESPONSE IN SCHIZOPHRENIA - PROPOSED RESOLUTION OF A CONTROVERSY BIOLOGICAL PSYCHIATRY Levinson, D. F., Edelberg, R., BRIDGER, W. H. 1984; 19 (4): 489-507

  Abstract

  The habituation of the skin conductance orienting response ( SCOR ) was studied in 36 schizophrenic and 11 normal male subjects. Scoring criteria significantly influenced results: more inclusive criteria (used in most SCOR studies) scored 56% of patients as nonresponders and 19% as slow habituators . More restrictive criteria scored 75% of patients as nonresponders, and the remainder as faster habituators than normals. The faster habituation of patient responders could be explained by the effects of low response amplitude. Evidence is given for the greater validity of the restrictive scoring criteria; on this basis the schizophrenic patients in this study were SCOR nonresponders or fast habituators . The data suggest that the more inclusive scoring criteria can confuse spontaneous and orienting activity. Clinical and theoretical implications are discussed.

  View details for Web of Science ID A1984SP47200003

  View details for PubMedID 6733171

• THE VALUE OF CLINICAL-PREDICTIONS OF DANGEROUSNESS AMERICAN JOURNAL OF PSYCHIATRY Levinson, D. F. 1983; 140 (5): 657-657

  View details for Web of Science ID A1983QP59000081

  View details for PubMedID 6846613

• Recurrent large-group phenomena: studies of an adolescent therapeutic community. Adolescent psychiatry Crabtee, L. H., Levinson, D. F. 1980; 8: 512-528

  View details for PubMedID 7223997

• WARD TENSION AND STAFF LEADERSHIP IN A THERAPEUTIC-COMMUNITY FOR HOSPITALIZED ADOLESCENTS PSYCHIATRY-INTERPERSONAL AND BIOLOGICAL PROCESSES Levinson, D. F., CRABTREE, L. H. 1979; 42 (3): 220-239

  Abstract

  Mental health workers on inpatient units spend a great deal of time trying to cope with interpersonal tensions that disrupt ward life. We have focused our attention on two aspects of this problem. The first is clarifying the nature of the social processes that underlie periods of increased tension and conflict on wards. The second is clarifying the kinds of staff leadership required to manage these tensions. We are sure that those who have worked on interactive treatment wards will recognize this situation: for a period of weeks or more there is an uneasy tension; patient cliques form and disruption occurs between cliques and with the staff. Often there is a climax of disruptive behavior, such as a day or weekend when a large number of patients break ward rules. Trouble seems to be contagious. Throughout the period staff members disagree about how to manage the patients and the disruption, and usually this disagreement is tinged with old philosophical or personal differences. No one feels very confident about taking leadership initiatives, and the formal leaders are blamed for various failures and lacks. Eventually, often after a climactic disturbance is resolved, ward life returns to "normal" and people feel much better about living and working on the ward. In this paper we review previous work on this kind of ward process and discuss some of the problems involved in conceptualizing it. We report on two period of ward observation that illustrate the sequence from low to high tension and back to relative calm. We then discuss our ideas about the kinds of staff leadership needed to manage different phases of this sequence and the problems of developing and integrating multiple ward leadership roles.

  View details for Web of Science ID A1979HE61900003

  View details for PubMedID 461595

• ORGANIZATION DEVELOPMENT PRO AND CON .3. DISCUSSION PROFESSIONAL PSYCHOLOGY LEVINSON 1973; 4 (2): 200-208

  View details for Web of Science ID A1973P570700018