Virginia Commonwealth University

About: Virginia Commonwealth University is a education organization based out in Richmond, Virginia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 23822 authors who have published 49587 publications receiving 1787046 citations. The organization is also known as: VCU.

Largest GWAS of PTSD (N=20 070) yields genetic overlap with schizophrenia and sex differences in heritability

Abstract: The Psychiatric Genomics Consortium-Posttraumatic Stress Disorder group (PGC-PTSD) combined genome-wide case–control molecular genetic data across 11 multiethnic studies to quantify PTSD heritability, to examine potential shared genetic risk with schizophrenia, bipolar disorder, and major depressive disorder and to identify risk loci for PTSD. Examining 20 730 individuals, we report a molecular genetics-based heritability estimate (h2SNP) for European-American females of 29% that is similar to h2SNP for schizophrenia and is substantially higher than h2SNP in European-American males (estimate not distinguishable from zero). We found strong evidence of overlapping genetic risk between PTSD and schizophrenia along with more modest evidence of overlap with bipolar and major depressive disorder. No single-nucleotide polymorphisms (SNPs) exceeded genome-wide significance in the transethnic (overall) meta-analysis and we do not replicate previously reported associations. Still, SNP-level summary statistics made available here afford the best-available molecular genetic index of PTSD—for both European- and African-American individuals—and can be used in polygenic risk prediction and genetic correlation studies of diverse phenotypes. Publication of summary statistics for ∼10 000 African Americans contributes to the broader goal of increased ancestral diversity in genomic data resources. In sum, the results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples. As has been the case with schizophrenia and other complex genetic disorders, larger sample sizes are needed to identify specific risk loci.

Anorexia nervosa and major depression: shared genetic and environmental risk factors.

Abstract: OBJECTIVE: The authors sought to derive heritability estimates for anorexia nervosa and to explore the etiology of the comorbid relationship between anorexia nervosa and major depression. METHOD: They applied bivariate structural equation modeling to a broad definition of anorexia nervosa and lifetime major depression as assessed in a population-based sample of 2,163 female twins. RESULTS: Anorexia nervosa was estimated to have a heritability of 58% (95% confidence interval=33%–84%). The authors were unable to completely rule out a contribution of shared environment. The comorbidity between anorexia nervosa and major depression is likely due to genetic factors that influence the risk for both disorders. CONCLUSIONS: Although the study was limited by the small number of affected twins, the results suggest that genetic factors significantly influence the risk for anorexia nervosa and substantially contribute to the observed comorbidity between anorexia nervosa and major depression.

Genomewide association for schizophrenia in the CATIE study: results of stage 1

Abstract: Little is known for certain about the genetics of schizophrenia. The advent of genomewide association has been widely anticipated as a promising means to identify reproducible DNA sequence variation associated with this important and debilitating disorder. A total of 738 cases with DSM-IV schizophrenia (all participants in the CATIE study) and 733 group-matched controls were genotyped for 492 900 single-nucleotide polymorphisms (SNPs) using the Affymetrix 500K two-chip genotyping platform plus a custom 164K fill-in chip. Following multiple quality control steps for both subjects and SNPs, logistic regression analyses were used to assess the evidence for association of all SNPs with schizophrenia. We identified a number of promising SNPs for follow-up studies, although no SNP or multimarker combination of SNPs achieved genomewide statistical significance. Although a few signals coincided with genomic regions previously implicated in schizophrenia, chance could not be excluded. These data do not provide evidence for the involvement of any genomic region with schizophrenia detectable with moderate sample size. However, a planned genomewide association study for response phenotypes and inclusion of individual phenotype and genotype data from this study in meta-analyses hold promise for eventual identification of susceptibility and protective variants.

Endophenotype: a conceptual analysis.

Abstract: This paper provides a conceptual analysis of the endophenotype (EP) construct that is having an increasing role in genetic strategies for unraveling the etiology of psychiatric disorders (PDs). We make six major points illustrated through the method of path analysis. First, it is important to distinguish between mediational and liability-index (or ‘risk indicator’) models for EP, as only the former requires genetic risk for PD to pass through EP. Second, the relative reliability of EP and PD can have a critical role in the interpretation of results. Ignoring them can lead to substantial errors of inference. Third, we need to consider bidirectional relationships between an EP and a PD, and the possibility that genetic effects on PD are only partially mediated by EP. Fourth, EP models typically assume that all genetic effects that have an impact on EP also alter risk for PD. However, among the genetic influences on EP and PD, it is also plausible that some will influence only EP, some only PD and some both. Fifth, we should also consider models incorporating multiple EPs and PDs, which can be well captured by multivariate genetic methods. Sixth, EPs may also reflect the impact of the environment on risk for PDs. The EP concept has important potential lessons for etiological research in PDs that can be optimized by considering it as a special case of a broader set of multivariate genetic models, which can be fitted using currently available methodology.