Honors & Awards
Chairman’s Award: Advancing Science, Stanford Psychiatry and Behavioral Sciences (2020)
Excellence in Teaching Award, Stanford Psychiatry Residency (2019)
Reviewer’s Choice Award, American Society for Human Genetics (2017)
ISPG Travel Award, World Congress of Psychiatric Genetics (2012)
Oral Presentation Award Finalist, World Congress of Psychiatric Genetics (2012)
Fulker Award, Best paper in Behavioral Genetics (2010)
University Scholarship, University of Georgia (2004)
Presidential Scholar, University of Georgia (2003)
Foundation Fellowship (full scholarship + international travel), University of Georgia (1998)
Governor's Scholarship, University of Georgia (1998)
National Merit Scholarship, University of Georgia (1998)
Robert C. Byrd Honors Scholarship, University of Georgia (1998)
Scholar Athlete Award, Rotary Club (1998)
Postdoc, Harvard Medical School, Statistical Genetics (2016)
Internship, Harvard Medical School, Clinical Psychology (2011)
PhD, University of Colorado, PhDs Clinical Psychology & Neuroscience (2011)
BS, University of Georgia, Honors Interdisciplinary Studies (2003)
Current Research and Scholarly Interests
We study genetic and environmental effects on mental health. Much of our work is computational and it relies upon genetic data, collected from millions of individuals, from around the world. We use genetic approaches because the overall goal of the lab is to discover fundamental information about psychiatric disorders, and ultimately to build more rational approaches to classification, prevention, and treatment.
- The Personal Genomics Revolution: Focus on Mental Health
PSYC 56N (Aut)
- Independent Studies (5)
Postdoctoral Research Mentor
Yaffa Serur Schwarzman
- HOT FLASH: A GWAS WITH NOTABLE INTERPRETABILITY AND PSYCHIATRIC RELEVANCE ELSEVIER. 2021: E45
Shared Genetic Effects may Partially Explain Higher Depression and PTSD Prevalence Among Women Using Hormone Therapy (HT)
ELSEVIER SCIENCE INC. 2021: S101-S102
View details for Web of Science ID 000645683800242
Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits.
BACKGROUND: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits.METHODS: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (rg < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations.RESULTS: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, although <1 for educational attainment and risk-taking behavior. We identified 4 genes with significant sex-differentiated effects across 3 traits. Several trait pairs shared sex-differentiated effects. The top genes with sex-differentiated effects were enriched for multiple gene sets, including neuron- and synapse-related sets. Most between-trait genetic correlation estimates were not significantly different between sexes, with exceptions (educational attainment and risk-taking behavior).CONCLUSIONS: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.
View details for DOI 10.1016/j.biopsych.2020.12.024
View details for PubMedID 33648717
Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia.
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
Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.
Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10-8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10-6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10-7; rs73033497, p = 8.8 × 10-7; rs7914279, p = 6.4 × 10-7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10-7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10-7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10-7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
View details for DOI 10.1016/j.biopsych.2021.02.972
View details for PubMedID 34099189
Higher Depression and PTSD Prevalence Among Women Using Hormone Replacement Therapy (HRT) May Be Due to Shared Genetic Effects
SPRINGERNATURE. 2020: 9
View details for Web of Science ID 000596371000019
Shared Molecular Genetic Risk of Alcohol Dependence and Posttraumatic Stress Disorder (PTSD)
PSYCHOLOGY OF ADDICTIVE BEHAVIORS
2020; 34 (5): 613–19
Alcohol use disorder (AUD) and posttraumatic stress disorder (PTSD) frequently co-occur, highlighting the importance of understanding the etiology of these comorbid conditions. Although AUD and PTSD are moderately heritable with modest overlap in genetic risk as estimated from family studies, there has been a paucity of work using molecular genetic data to estimate shared genetic effects on these conditions. This study used large-scale genomewide molecular data to examine shared genetic risk for AUD, specifically alcohol dependence (AD), and PTSD through cross-trait linkage disequilibrium (LD) score regression (LDSC; also known as LDSR). Summary statistics came from the Psychiatric Genomics Consortium (PGC) PTSD Workgroup Freeze 2 European ancestry (EA) participants (N = 174,659) and AD summary statistics in EA participants (N = 38,686) came from the PGC Substance Use Disorders (SUD) Workgroup. We performed LDSC to estimate genetic correlation between AD and PTSD using HapMap3 variants and LD scores from the 1000 Genomes project. A moderate, significant correlation was observed between AD and PTSD (rg = .35, p = .02), with sex differences identified through stratified analyses. Our results are the first to demonstrate evidence of a shared molecular genetic etiology for AD and PTSD. Further research is needed to better understand possible sex differences in shared heritability and extend these results to additional populations. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
View details for DOI 10.1037/adb0000568
View details for Web of Science ID 000557765000006
View details for PubMedID 32191043
View details for PubMedCentralID PMC7394716
Short-term mental health sequelae of bereavement predict long-term physical health decline in older adults: US Health and Retirement Study Analysis.
The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVE: Spousal death is a common late-life event with health-related sequelae. Evidence linking poor mental health to disease suggests the hypothesis that poor mental health following death of a spouse could be a harbinger of physical health decline. Thus, identification of bereavement-related mental health symptoms could provide an opportunity for prevention.METHODS: We analyzed data from N=39,162 individuals followed from 1994-2016 in the US Health and Retirement Study; N=5,061 were widowed during follow-up. We tested change in mental and physical health from pre-bereavement through the 5-years following spousal death.RESULTS: Bereaved spouses experienced an increase in depressive symptoms following their spouses' deaths but the depressive shock attenuated within one year. Bereaved spouses experienced increases in disability, chronic-disease morbidity, and hospitalization, which grew in magnitude over time, especially among older respondents. Bereaved spouses were at increased risk of death compared to non-bereaved respondents. The magnitude of depressive symptoms in the immediate aftermath of spousal death predicted physical-health decline and mortality risk over 5 years of follow-up.DISCUSSION: Bereavement-related depressive symptoms indicate a risk for physical health decline and death in older adults. Screening for depressive symptoms in bereaved older adults may represent an opportunity for intervention to preserve healthy lifespan.
View details for DOI 10.1093/geronb/gbaa044
View details for PubMedID 32246152
Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.
Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
View details for DOI 10.1111/adb.12880
View details for PubMedID 32064741
Genomic influences on self-reported childhood maltreatment.
2020; 10 (1): 38
Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to (1) identify genetic variation associated with self-reported childhood maltreatment, (2) estimate SNP-based heritability (h2snp), (3) assess predictive value of polygenic risk scores (PRS) for childhood maltreatment, and (4) quantify genetic overlap of childhood maltreatment with mental and physical health-related phenotypes, and condition the top hits from our analyses when such overlap is present. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n=124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder group (PGC-PTSD) (n=26,290). h2snp for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression. PRS was calculated using PRSice and mtCOJO was used to perform conditional analysis. Two genome-wide significant loci associated with childhood maltreatment (rs142346759, p=4.35*10-8, FOXP1; rs10262462, p=3.24*10-8, FOXP2) were identified in the discovery dataset but were not replicated in PGC-PTSD. h2snp for childhood maltreatment was ~6% and the PRS derived from the UKBB was significantly predictive of childhood maltreatment in PGC-PTSD (r2=0.0025; p=1.8*10-15). The most significant genetic correlation of childhood maltreatment was with depressive symptoms (rg=0.70, p=4.65*10-40), although we show evidence that our top hits may be specific to childhood maltreatment. This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. Speculatively, FOXP genes might influence externalizing traits and so be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with a range of phenotypes, may ultimately be useful in in developing targeted treatment and prevention strategies.
View details for DOI 10.1038/s41398-020-0706-0
View details for PubMedID 32066696
Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts.
2020; 31 (9): 107716
To reveal post-traumatic stress disorder (PTSD) genetic risk influences on tissue-specific gene expression, we use brain and non-brain transcriptomic imputation. We impute genetically regulated gene expression (GReX) in 29,539 PTSD cases and 166,145 controls from 70 ancestry-specific cohorts and identify 18 significant GReX-PTSD associations corresponding to specific tissue-gene pairs. The results suggest substantial genetic heterogeneity based on ancestry, cohort type (military versus civilian), and sex. Two study-wide significant PTSD associations are identified in European and military European cohorts; ZNF140 is predicted to be upregulated in whole blood, and SNRNP35 is predicted to be downregulated in dorsolateral prefrontal cortex, respectively. In peripheral leukocytes from 175 marines, the observed PTSD differential gene expression correlates with the predicted differences for these individuals, and deployment stress produces glucocorticoid-regulated expression changes that include downregulation of both ZNF140 and SNRNP35. SNRNP35 knockdown in cells validates its functional role in U12-intron splicing. Finally, exogenous glucocorticoids in mice downregulate prefrontal Snrnp35 expression.
View details for DOI 10.1016/j.celrep.2020.107716
View details for PubMedID 32492425
Polygenic prediction and GWAS of depression, PTSD, and suicidal ideation/self-harm in a Peruvian cohort.
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Genome-wide approaches including polygenic risk scores (PRSs) are now widely used in medical research; however, few studies have been conducted in low- and middle-income countries (LMICs), especially in South America. This study was designed to test the transferability of psychiatric PRSs to individuals with different ancestral and cultural backgrounds and to provide genome-wide association study (GWAS) results for psychiatric outcomes in this sample. The PrOMIS cohort (N = 3308) was recruited from prenatal care clinics at the Instituto Nacional Materno Perinatal (INMP) in Lima, Peru. Three major psychiatric outcomes (depression, PTSD, and suicidal ideation and/or self-harm) were scored by interviewers using valid Spanish questionnaires. Illumina Multi-Ethnic Global chip was used for genotyping. Standard procedures for PRSs and GWAS were used along with extra steps to rule out confounding due to ancestry. Depression PRSs significantly predicted depression, PTSD, and suicidal ideation/self-harm and explained up to 0.6% of phenotypic variation (minimum p = 3.9 × 10-6). The associations were robust to sensitivity analyses using more homogeneous subgroups of participants and alternative choices of principal components. Successful polygenic prediction of three psychiatric phenotypes in this Peruvian cohort suggests that genetic influences on depression, PTSD, and suicidal ideation/self-harm are at least partially shared across global populations. These PRS and GWAS results from this large Peruvian cohort advance genetic research (and the potential for improved treatments) for diverse global populations.
View details for DOI 10.1038/s41386-020-0603-5
View details for PubMedID 31926482
Molecular genetic overlap between posttraumatic stress disorder and sleep phenotypes.
STUDY OBJECTIVES: Sleep problems are common, serving as both a predictor and symptom of posttraumatic stress disorder (PTSD), with these bidirectional relationships well established in the literature. While both sleep phenotypes and PTSD are moderately heritable, there has been a paucity of investigation into potential genetic overlap between sleep and PTSD. Here, we estimate genetic correlations between multiple sleep phenotypes (including insomnia symptoms, sleep duration, daytime sleepiness, and chronotype) and PTSD, using results from the largest genome-wide association study (GWAS) to date of PTSD, as well as publicly available GWAS results for sleep phenotypes within UK Biobank data (23 variations, encompassing four main phenotypes).METHODS: Genetic correlations were estimated utilizing linkage disequilibrium score regression (LDSC), an approach that uses GWAS summary statistics to compute genetic correlations across traits, and Mendelian randomization (MR) analyses were conducted to follow up on significant correlations.RESULTS: Significant, moderate genetic correlations were found between insomnia symptoms (rg range 0.36-0.49), oversleeping (rg range 0.32-0.44), undersleeping (rg range 0.48-0.49), and PTSD. In contrast, there were mixed results for continuous sleep duration and daytime sleepiness phenotypes, and chronotype was not correlated with PTSD. MR analyses did not provide evidence for casual effects of sleep phenotypes on PTSD.CONCLUSION: Sleep phenotypes, particularly insomnia symptoms and extremes of sleep duration, have shared genetic etiology with PTSD, but causal relationships were not identified. This highlights the importance of further investigation into the overlapping influences on these phenotypes as sample sizes increase and new methods to investigate directionality and causality become available.
View details for DOI 10.1093/sleep/zsz257
View details for PubMedID 31802129
Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations.
Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.
View details for DOI 10.1016/j.cell.2019.08.051
View details for PubMedID 31607513
- How genome-wide association studies (GWAS) made traditional candidate gene studies obsolete NEUROPSYCHOPHARMACOLOGY 2019; 44 (9): 1518–23
Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.
Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992cases of anorexia nervosa and 55,525controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.
View details for DOI 10.1038/s41588-019-0439-2
View details for PubMedID 31308545
- Statistical inference and reproducibility in geobiology GEOBIOLOGY 2019; 17 (3): 261–71
Association of Economic Status and Educational Attainment With Posttraumatic Stress Disorder A Mendelian Randomization Study
JAMA NETWORK OPEN
2019; 2 (5): e193447
There is a well-established negative association of educational attainment (EA) and other traits related to cognitive ability with posttraumatic stress disorder (PTSD), but the underlying mechanisms are poorly understood.To investigate the association of PTSD with traits related to EA.Genetic correlation, polygenic risk scoring, and mendelian randomization (MR) were conducted including 23 185 individuals with PTSD and 151 309 control participants from the Psychiatric Genomics Consortium for PTSD and up to 1 131 881 individuals assessed for EA and related traits from UK Biobank, 23andMe, and the Social Science Genetic Association Consortium. Data were analyzed from July 3 through November 19, 2018.Genetic correlation obtained from linkage disequilibrium score regression, phenotypic variance explained by polygenic risk scores, and association estimates from MR.Summary association data from multiple genome-wide association studies were available for a total of 1 180 352 participants (634 391 [53.7%] women). Posttraumatic stress disorder showed negative genetic correlations with EA (rg = -0.26; SE = 0.05; P = 4.60 × 10-8). Mendelian randomization analysis, conducting considering a random-effects inverse-variance weighted method, indicated that EA has a negative association with PTSD (β = -0.23; 95% CI, -0.07 to -0.39; P = .004). Investigating potential mediators of the EA-PTSD association, propensity for trauma exposure and risk-taking behaviors were observed as risk factors for PTSD independent of EA (trauma exposure: β = 0.37; 95% CI, 0.19 to 0.52; P = 2.57 × 10-5; risk-taking: β = 0.76; 95% CI, 0.38 to 1.13; P = 1.13 × 10-4), while income may mediate the association of EA with PSTD (MR income: β = -0.18; 95% CI, -0.29 to -0.07; P = .001; MR EA: β = -0.23; 95% CI, -0.39 to -0.07; P = .004; multivariable MR income: β = -0.32; 95% CI, -0.57 to 0.07; P = .02; multivariable MR EA: β = -0.04; 95% CI, -0.29 to 0.21; SE, 0.13; P = .79).Large-scale genomic data sets add further evidence to the negative association of EA with PTSD, also supporting the role of economic status as a mediator in the association observed.
View details for DOI 10.1001/jamanetworkopen.2019.3447
View details for Web of Science ID 000476806200031
View details for PubMedID 31050786
View details for PubMedCentralID PMC6503495
Statistical inference and reproducibility in geobiology.
View details for PubMedID 30747493
International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.
2019; 10 (1): 4558
The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.
View details for DOI 10.1038/s41467-019-12576-w
View details for PubMedID 31594949
Robust Findings From 25Years of PSTD Genetics Research.
Current psychiatry reports
2018; 20 (12): 115
PURPOSE OF REVIEW: The purpose of this review is to contextualize findings from the first 25years of PTSD genetics research, focusing on the most robust findings and interpreting results in light of principles that have emerged from modern genetics studies.RECENT FINDINGS: Genome-wide association studies (GWAS) encompassing tens of thousands of participants enabled the first molecular genetic heritability and genetic correlation estimates for PTSD in 2017. In 2018, highly promising loci for PTSD were reported, including variants in and near the CAMKV, KANSL1, and TCF4 genes. Twin studies from 25years ago established that PTSD is genetically influenced and foreshadowed the molecular genetic findings of today. Discoveries that were impossible with smaller studies have been achieved via collaborative/team-science efforts. Most promisingly, individual genomic loci offer entirely novel clues about PTSD etiology, providing the raw material for transformative discoveries, and the future of PTSD research is bright.
View details for PubMedID 30350223
Chromosomes to Social Contexts: Sex and Gender Differences in PTSD.
Current psychiatry reports
2018; 20 (12): 114
PURPOSE OF REVIEW: This review highlights recent research on sex- and gender-related factors in the prevalence, symptom expression, and treatment of PTSD. Further discoveries about the underlying mechanisms of sex and gender effects have the potential to shape innovative directions for research.RECENT FINDINGS: The prevalence of PTSD is substantially higher among women, but women show a modest advantage with respect to treatment response. There is evidence of greater heritability among females. Women are more likely to experience sexual and intimate violence, childhood trauma exposure, and repeated trauma exposures. Specific characteristics of social contexts act as gender-linked risks for PTSD. Among individuals diagnosed with PTSD, men and women are similar in phenotypic expression. Though research has yet to fully account for the factors that explain sex- and gender- related effects on PTSD, emerging research suggests these effects occur across multiple levels. Shared risk factors for trauma exposure and PTSD merit further investigation. Both social and biological contexts merit investigation to understand sex-linked differences in heritability.
View details for PubMedID 30345456
The Anorexia Nervosa Genetics Initiative (ANGI): Overview and methods.
Contemporary clinical trials
2018; 74: 61–69
BACKGROUND: Genetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13,000 individuals with AN and ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research.METHODS: ANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H.RESULTS: Blood samples and clinical information were collected from 13,363 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable.CONCLUSIONS: Our multi-pronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.govNCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3.
View details for PubMedID 30287268
Analysis of shared heritability in common disorders of the brain
2018; 360 (6395): 1313-+
Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
View details for PubMedID 29930110
- Largest GWAS of PTSD (N=20,070) Yields Genetic Overlap with Schizophrenia and Sex Differences in Heritability Molecular Psychiatry 2017
- Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa American Journal of Psychiatry 2017
Genetic Correlation Profile of Schizophrenia Mirrors Epidemiological Results and Suggests Link Between Polygenic and Rare Variant (22q11.2) Cases of Schizophrenia.
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
Analysis of protein-coding genetic variation in 60,706 humans
2016; 536 (7616): 285-?
Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.
View details for DOI 10.1038/nature19057
View details for Web of Science ID 000381804900026
View details for PubMedID 27535533
- Research Letter: PTSD has shared polygenic contributions with bipolar disorder and schizophrenia in women PSYCHOLOGICAL MEDICINE 2016; 46 (3): 669-671
An atlas of genetic correlations across human diseases and traits
2015; 47 (11): 1236-?
Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique-cross-trait LD Score regression-for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.
View details for DOI 10.1038/ng.3406
View details for Web of Science ID 000363988200006
View details for PubMedID 26414676
View details for PubMedCentralID PMC4797329
- Large Scale Genetic Research on Neuropsychiatric Disorders in African Populations is Needed. EBioMedicine 2015; 2 (10): 1259-1261
The Psychiatric Genomics Consortium Posttraumatic Stress Disorder Workgroup: Posttraumatic Stress Disorder Enters the Age of Large-Scale Genomic Collaboration
2015; 40 (10): 2287-2297
The development of posttraumatic stress disorder (PTSD) is influenced by genetic factors. Although there have been some replicated candidates, the identification of risk variants for PTSD has lagged behind genetic research of other psychiatric disorders such as schizophrenia, autism, and bipolar disorder. Psychiatric genetics has moved beyond examination of specific candidate genes in favor of the genome-wide association study (GWAS) strategy of very large numbers of samples, which allows for the discovery of previously unsuspected genes and molecular pathways. The successes of genetic studies of schizophrenia and bipolar disorder have been aided by the formation of a large-scale GWAS consortium: the Psychiatric Genomics Consortium (PGC). In contrast, only a handful of GWAS of PTSD have appeared in the literature to date. Here we describe the formation of a group dedicated to large-scale study of PTSD genetics: the PGC-PTSD. The PGC-PTSD faces challenges related to the contingency on trauma exposure and the large degree of ancestral genetic diversity within and across participating studies. Using the PGC analysis pipeline supplemented by analyses tailored to address these challenges, we anticipate that our first large-scale GWAS of PTSD will comprise over 10 000 cases and 30 000 trauma-exposed controls. Following in the footsteps of our PGC forerunners, this collaboration-of a scope that is unprecedented in the field of traumatic stress-will lead the search for replicable genetic associations and new insights into the biological underpinnings of PTSD.
View details for DOI 10.1038/npp.2015.118
View details for Web of Science ID 000359493700001
View details for PubMedID 25904361
The Evaluation of Tools Used to Predict the Impact of Missense Variants Is Hindered by Two Types of Circularity
2015; 36 (5): 513-523
Prioritizing missense variants for further experimental investigation is a key challenge in current sequencing studies for exploring complex and Mendelian diseases. A large number of in silico tools have been employed for the task of pathogenicity prediction, including PolyPhen-2, SIFT, FatHMM, MutationTaster-2, MutationAssessor, Combined Annotation Dependent Depletion, LRT, phyloP, and GERP++, as well as optimized methods of combining tool scores, such as Condel and Logit. Due to the wealth of these methods, an important practical question to answer is which of these tools generalize best, that is, correctly predict the pathogenic character of new variants. We here demonstrate in a study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. We show that comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.
View details for DOI 10.1002/humu.22768
View details for Web of Science ID 000353357300004
View details for PubMedID 25684150
View details for PubMedCentralID PMC4409520
Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
2015; 18 (2): 199-209
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
The Human Ortholog of Acid-Sensing Ion Channel Gene ASIC1a Is Associated With Panic Disorder and Amygdala Structure and Function
2014; 76 (11): 902-910
Individuals with panic disorder (PD) exhibit a hypersensitivity to inhaled carbon dioxide, possibly reflecting a lowered threshold for sensing signals of suffocation. Animal studies have shown that carbon dioxide-mediated fear behavior depends on chemosensing of acidosis in the amygdala via the acid-sensing ion channel ASIC1a. We examined whether the human ortholog of the ASIC1a gene, ACCN2, is associated with the presence of PD and with amygdala structure and function.We conducted a case-control analysis (n = 414 PD cases and 846 healthy controls) of ACCN2 single nucleotide polymorphisms and PD. We then tested whether variants showing significant association with PD are also associated with amygdala volume (n = 1048) or task-evoked reactivity to emotional stimuli (n = 103) in healthy individuals.Two single nucleotide polymorphisms at the ACCN2 locus showed evidence of association with PD: rs685012 (odds ratio = 1.32, gene-wise corrected p = .011) and rs10875995 (odds ratio = 1.26, gene-wise corrected p = .046). The association appeared to be stronger when early-onset (age ≤ 20 years) PD cases and when PD cases with prominent respiratory symptoms were compared with controls. The PD risk allele at rs10875995 was associated with increased amygdala volume (p = .035) as well as task-evoked amygdala reactivity to fearful and angry faces (p = .0048).Genetic variation at ACCN2 appears to be associated with PD and with amygdala phenotypes that have been linked to proneness to anxiety. These results support the possibility that modulation of acid-sensing ion channels may have therapeutic potential for PD.
View details for DOI 10.1016/j.biopsych.2013.12.018
View details for Web of Science ID 000344733200013
View details for PubMedID 24529281
Clozapine-induced agranulocytosis is associated with rare HLA-DQB1 and HLA-B alleles
Clozapine is a particularly effective antipsychotic medication but its use is curtailed by the risk of clozapine-induced agranulocytosis/granulocytopenia (CIAG), a severe adverse drug reaction occurring in up to 1% of treated individuals. Identifying genetic risk factors for CIAG could enable safer and more widespread use of clozapine. Here we perform the largest and most comprehensive genetic study of CIAG to date by interrogating 163 cases using genome-wide genotyping and whole-exome sequencing. We find that two loci in the major histocompatibility complex are independently associated with CIAG: a single amino acid in HLA-DQB1 (126Q) (P=4.7 × 10(-14), odds ratio (OR)=0.19, 95% confidence interval (CI)=0.12-0.29) and an amino acid change in the extracellular binding pocket of HLA-B (158T) (P=6.4 × 10(-10), OR=3.3, 95% CI=2.3-4.9). These associations dovetail with the roles of these genes in immunogenetic phenotypes and adverse drug responses for other medications, and provide insight into the pathophysiology of CIAG.
View details for DOI 10.1038/ncomms5757
View details for Web of Science ID 000342927300001
View details for PubMedID 25187353
Personality Pathology Factors Predict Recurrent Major Depressive Disorder in Emerging Adults
JOURNAL OF CLINICAL PSYCHOLOGY
2014; 70 (6): 536-545
Prior investigations consistently indicate that personality pathology is a risk factor for recurrence of major depressive disorder (MDD). Lack of emipircal support, however, for the Diagnostic and Statistical Manual of Mental Disorders (DSM) Fourth Edition organization of Axis II disorders supports the investigation of empirically derived factors of personality pathology as predictors of recurrence.A sample of 130 previously depressed emerging adults (80% female; aged 18 to 21 years) were assessed for personality disorder symptoms at baseline. Participants were then followed for 18 months to identify MDD recurrence during the first 2 years of college.Based on a previous factor analysis of DSM personality disorder criteria, eight personality pathology factors were examined as predictors of MDD recurrence. Survival analysis indicated that factors of interpersonal hypersensitivity, antisocial conduct, and social anxiety were associated with increased risk of MDD recurrence.These findings suggest that an empirically based approach to personality pathology organization may yield useful predictors of MDD recurrence during emerging adulthood.
View details for DOI 10.1002/jclp.22028
View details for Web of Science ID 000334846400005
View details for PubMedID 23852879
Mind the Gap Why Many Geneticists and Psychological Scientists Have Discrepant Views About Gene-Environment Interaction (GXE) Research
2014; 69 (3): 249-268
As our field seeks to elucidate the biopsychosocial etiologies of mental health disorders, many traditional psychological and social science researchers have added, or plan to add, genetic components to their programs of research. An understanding of the history, methods, and perspectives of the psychiatric genetics community is useful in this pursuit. In this article we provide a brief overview of psychiatric genetic methods and findings. This overview lays the groundwork for a more thorough review of gene-environment interaction (G×E) research and the candidate gene approach to G×E research that remains popular among many psychologists and social scientists. We describe the differences in perspective between psychiatric geneticists and psychological scientists that have contributed to a growing divide between the research cited and conducted by these two related disciplines. Finally, we outline a strategy for the future of research on gene-environment interactions that capitalizes on the relative strengths of each discipline. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
View details for DOI 10.1037/a0036320
View details for Web of Science ID 000334685500003
View details for PubMedID 24750075
Pathway Analyses Implicate Glial Cells in Schizophrenia
2014; 9 (2)
The quest to understand the neurobiology of schizophrenia and bipolar disorder is ongoing with multiple lines of evidence indicating abnormalities of glia, mitochondria, and glutamate in both disorders. Despite high heritability estimates of 81% for schizophrenia and 75% for bipolar disorder, compelling links between findings from neurobiological studies, and findings from large-scale genetic analyses, are only beginning to emerge.Ten publically available gene sets (pathways) related to glia, mitochondria, and glutamate were tested for association to schizophrenia and bipolar disorder using MAGENTA as the primary analysis method. To determine the robustness of associations, secondary analyses were performed with: ALIGATOR, INRICH, and Set Screen. Data from the Psychiatric Genomics Consortium (PGC) were used for all analyses. There were 1,068,286 SNP-level p-values for schizophrenia (9,394 cases/12,462 controls), and 2,088,878 SNP-level p-values for bipolar disorder (7,481 cases/9,250 controls).The Glia-Oligodendrocyte pathway was associated with schizophrenia, after correction for multiple tests, according to primary analysis (MAGENTA p = 0.0005, 75% requirement for individual gene significance) and also achieved nominal levels of significance with INRICH (p = 0.0057) and ALIGATOR (p = 0.022). For bipolar disorder, Set Screen yielded nominally and method-wide significant associations to all three glial pathways, with strongest association to the Glia-Astrocyte pathway (p = 0.002).Consistent with findings of white matter abnormalities in schizophrenia by other methods of study, the Glia-Oligodendrocyte pathway was associated with schizophrenia in our genomic study. These findings suggest that the abnormalities of myelination observed in schizophrenia are at least in part due to inherited factors, contrasted with the alternative of purely environmental causes (e.g. medication effects or lifestyle). While not the primary purpose of our study, our results also highlight the consequential nature of alternative choices regarding pathway analysis, in that results varied somewhat across methods, despite application to identical datasets and pathways.
View details for DOI 10.1371/journal.pone.0089441
View details for Web of Science ID 000331880700045
View details for PubMedID 24586781
View details for PubMedCentralID PMC3933626
A polygenic burden of rare disruptive mutations in schizophrenia
2014; 506 (7487): 185-?
Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease.
View details for DOI 10.1038/nature12975
View details for Web of Science ID 000331107700030
View details for PubMedID 24463508
View details for PubMedCentralID PMC4136494
- Genetic Predictors of Risk and Resilience in Psychiatric Disorders: A Cross-Disorder Genome-Wide Association Study of Functional Impairment in Major Depressive Disorder, Bipolar Disorder, and Schizophrenia AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS 2013; 162 (8): 779-788
- From Candidate Genes to Genome-wide Association: The Challenges and Promise of Posttraumatic Stress Disorder Genetic Studies BIOLOGICAL PSYCHIATRY 2013; 74 (9): 634-636
- Paying Attention to All Results, Positive and Negative JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY 2013; 52 (5): 462-465
- Conceptual Issues in Psychiatric Gene-Environment Interaction Research Response AMERICAN JOURNAL OF PSYCHIATRY 2012; 169 (2): 223-223
A Critical Review of the First 10 Years of Candidate Gene-by-Environment Interaction Research in Psychiatry
AMERICAN JOURNAL OF PSYCHIATRY
2011; 168 (10): 1041-1049
Gene-by-environment interaction (G×E) studies in psychiatry have typically been conducted using a candidate G×E (cG×E) approach, analogous to the candidate gene association approach used to test genetic main effects. Such cG×E research has received widespread attention and acclaim, yet cG×E findings remain controversial. The authors examined whether the many positive cG×E findings reported in the psychiatric literature were robust or if, in aggregate, cG×E findings were consistent with the existence of publication bias, low statistical power, and a high false discovery rate.The authors conducted analyses on data extracted from all published studies (103 studies) from the first decade (2000-2009) of cG×E research in psychiatry.Ninety-six percent of novel cG×E studies were significant compared with 27% of replication attempts. These findings are consistent with the existence of publication bias among novel cG×E studies, making cG×E hypotheses appear more robust than they actually are. There also appears to be publication bias among replication attempts because positive replication attempts had smaller average sample sizes than negative ones. Power calculations using observed sample sizes suggest that cG×E studies are underpowered. Low power along with the likely low prior probability of a given cG×E hypothesis being true suggests that most or even all positive cG×E findings represent type I errors.In this new era of big data and small effects, a recalibration of views about groundbreaking findings is necessary. Well-powered direct replications deserve more attention than novel cG×E findings and indirect replications.
View details for DOI 10.1176/appi.ajp.2011.11020191
View details for Web of Science ID 000295481200011
View details for PubMedID 21890791
Understanding the Complex Etiologies of Developmental Disorders: Behavioral and Molecular Genetic Approaches
JOURNAL OF DEVELOPMENTAL AND BEHAVIORAL PEDIATRICS
2010; 31 (7): 533-544
This article has 2 primary goals. First, a brief tutorial on behavioral and molecular genetic methods is provided for readers without extensive training in these areas. To illustrate the application of these approaches to developmental disorders, etiologically informative studies of reading disability (RD), math disability (MD), and attention-deficit hyperactivity disorder (ADHD) are then reviewed. Implications of the results for these specific disorders and for developmental disabilities as a whole are discussed, and novel directions for future research are highlighted.Previous family and twin studies of RD, MD, and ADHD are reviewed systematically, and the extensive molecular genetic literatures on each disorder are summarized. To illustrate 4 novel extensions of these etiologically informative approaches, new data are presented from the Colorado Learning Disabilities Research Center, an ongoing twin study of the etiology of RD, ADHD, MD, and related disorders.RD, MD, and ADHD are familial and heritable, and co-occur more frequently than expected by chance. Molecular genetic studies suggest that all 3 disorders have complex etiologies, with multiple genetic and environmental risk factors each contributing to overall risk for each disorder. Neuropsychological analyses indicate that the 3 disorders are each associated with multiple neuropsychological weaknesses, and initial evidence suggests that comorbidity between the 3 disorders is due to common genetic risk factors that lead to slow processing speed.
View details for DOI 10.1097/DBP.0b013e3181ef42a1
View details for Web of Science ID 000281561700003
View details for PubMedID 20814254
Are Extended Twin Family Designs Worth the Trouble? A Comparison of the Bias, Precision, and Accuracy of Parameters Estimated in Four Twin Family Models
2010; 40 (3): 377-393
The classical twin design (CTD) uses observed covariances from monozygotic and dizygotic twin pairs to infer the relative magnitudes of genetic and environmental causes of phenotypic variation. Despite its wide use, it is well known that the CTD can produce biased estimates if its stringent assumptions are not met. By modeling observed covariances of twins' relatives in addition to twins themselves, extended twin family designs (ETFDs) require less stringent assumptions, can estimate many more parameters of interest, and should produce less biased estimates than the CTD. However, ETFDs are more complicated to use and interpret, and by attempting to estimate a large number of parameters, the precision of parameter estimates may suffer. This paper is a formal investigation into a simple question: Is it worthwhile to use more complex models such as ETFDs in behavioral genetics? In particular, we compare the bias, precision, and accuracy of estimates from the CTD and three increasingly complex ETFDs. We find the CTD does a decent job of estimating broad sense heritability, but CTD estimates of shared environmental effects and the relative importance of additive versus non-additive genetic variance can be biased, sometimes wildly so. Increasingly complex ETFDs, on the other hand, are more accurate and less sensitive to assumptions than simpler models. We conclude that researchers interested in characterizing the environment or the makeup of genetic variation should use ETFDs when possible.
View details for DOI 10.1007/s10519-009-9320-x
View details for Web of Science ID 000276603900011
View details for PubMedID 20013306
Variation in brain-derived neurotrophic factor (BDNF) gene is associated with symptoms of depression
JOURNAL OF AFFECTIVE DISORDERS
2009; 115 (1-2): 215-219
Brain-derived neurotrophic factor (BDNF) is putatively involved in the pathophysiology of depression. This study examined associations between BDNF genotype at the Val66Met locus, depression symptoms, and serum BDNF levels.Twenty-eight subjects in the primary study (25 female, 3 male) completed diagnostic interviews, self-report questionnaires, and provided blood samples for serum BDNF quantification and buccal cell samples for genotyping. Data from a second sample of 189 subjects (94 female, 95 male) were also analyzed.The Val/Val genotype was associated with higher scores on the Cognitive-Affective factor of the Beck Depression Inventory-II (BDI-II) in the primary sample. No evidence was found for association between genotype and serum BDNF in this sample. Consistent with the primary study, Val/Val genotype was associated with higher total BDI-II scores, Cognitive-Affective factor scores, and Somatic-Vegetative factor scores, in the second sample. Serum BDNF measures were not available for the second sample.The mechanism through which BDNF genotype translates into (putative) differences in depression symptoms is not known.In contrast to case-control association studies, we demonstrate two changes in the operationalization of the phenotype. Additionally, we found an association between Val/Val genotype and higher levels of depression symptoms. This result is distinct from an association between BDNF genotype and diagnosis of depression, and it may help to clarify our understanding of genetic liability to depression, which will ultimately lead to more nuanced and effective treatment strategies.
View details for DOI 10.1016/j.jad.2008.08.016
View details for Web of Science ID 000265319900027
View details for PubMedID 18842305
Modeling Extended Twin Family Data I: Description of the Cascade Model
TWIN RESEARCH AND HUMAN GENETICS
2009; 12 (1): 8-18
The classical twin design uses data on the variation of and covariation between monozygotic and dizygotic twins to infer underlying genetic and environmental causes of phenotypic variation in the population. By using data from additional relative classes, such as parents, extended twin family designs more comprehensively describe the causes of phenotypic variation. This article introduces an extension of previous extended twin family models, the Cascade model, which uses information on twins as well as their siblings, spouses, parents, and children to differentiate two genetic and six environmental sources of phenotypic variation. The Cascade also relaxes assumptions regarding mating and cultural transmission that existed in previous extended twin family designs. The estimation of additional parameters and relaxation of assumptions is potentially important, not only because it allows more fine-grained descriptions of the causes of phenotypic variation, but more importantly, because it can reduce the biases in parameter estimates that exist in earlier designs.
View details for Web of Science ID 000263635000002
View details for PubMedID 19210175
Experimental vesicular stomatitis virus infection in horses: Effect of route of inoculation and virus serotype
2006; 43 (6): 943-955
Horses were inoculated with Vesicular stomatitis New Jersey and Indiana viruses by routes simulating contact and vector transmission. Clinical signs, lesions, antibody development, viral shedding and persistence, and viremia were monitored. Horses were infected with both viruses by all routes as confirmed by seroconversion. Salivation, primary lesions at inoculation sites, and secondary oral lesions were the most common clinical findings. Viral shedding was most often from the oral cavity, followed by the nasal cavity; titers were highest from oral cavity samples. Virus was rarely isolated from the conjunctival sac and never from feces or blood. Development of neutralizing antibody coincided with cessation of lesion development and detection of virus by isolation. Circulating virus-specific IgM, IgG, IgA, and neutralizing antibodies developed in most animals postinoculation (PI) days 6 to 12, depending on the route of inoculation. At postmortem (PI days 12 to 15), lesions were healing, were not vesicular, and did not contain detectable virus by isolation, reverse transcriptase polymerase chain reaction, or immunohistochemistry. Numerous infiltrating lymphocytes and plasma cells suggested that lesion resolution was partially due to local immunity. Detection of viral RNA from tonsil and lymph nodes of head at necropsy suggests that these tissues play a role in the pathogenesis of the disease; molecular techniques targeting these tissues may be useful for confirming infection in resolving stages of disease. The routes of inoculation used in this study reflect the diversity of transmission routes that may occur during outbreaks and can be used to further study contact and vector transmission, vaccine development, and clarify pathogenesis of the disease in horses.
View details for Web of Science ID 000242225800009
View details for PubMedID 17099151