Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders

作者:Bin Cho Seung; Aliev Fazil; Clark Shaunna L; Adkins Amy E; Edenberg Howard J; Bucholz Kathleen K; Porjesz Bernice; Dick Danielle M
来源:Behavior Genetics, 2017, 47(4): 405-415.
DOI:10.1007/s10519-017-9844-4

摘要

Twin studies indicate that latent genetic factors overlap across comorbid psychiatric disorders. In this study, we used a novel approach to elucidate shared genetic factors across psychiatric outcomes by clustering single nucleotide polymorphisms based on their genome-wide association patterns. We applied latent profile analysis (LPA) to p-values resulting from genome-wide association studies across three phenotypes: symptom counts of alcohol dependence (AD), antisocial personality disorder (ASP), and major depression (MD), using the European-American case-control genome-wide association study subsample of the collaborative study on the genetics of alcoholism (N = 1399). In the 3-class model, classes were characterized by overall low associations (85.6% of SNPs), relatively stronger association only with MD (6.8%), and stronger associations with AD and ASP but not with MD (7.6%), respectively. These results parallel the genetic factor structure identified in twin studies. The findings suggest that applying LPA to association results across multiple disorders may be a promising approach to identify the specific genetic etiologies underlying shared genetic variance.

  • 出版日期2017-7