Instructor, Psychiatry and Behavioral Sciences
Postdoc, Harvard Medical School, Statistical Genetics (2016)
Internship, Harvard Medical School, Clinical Psychology (2011)
PhD, University of Colorado, PhDs Clinical Psychology & Neuroscience (2011)
MS, 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.
If you’re interested in joining the lab, let us know!
- Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa American Journal of Psychiatry 2017
- Largest GWAS of PTSD (N=20,070) Yields Genetic Overlap with Schizophrenia and Sex Differences in Heritability Molecular Psychiatry 2017
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
- 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
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
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
- 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