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Item Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders(Springer, 2017-07) Cho, Seung Bin; Aliev, Fazil; Clark, Shaunna L.; Adkins, Amy E.; Edenberg, Howard J.; Bucholz, Kathleen K.; Porjesz, Bernice; Dick, Danielle M.; Biochemistry and Molecular Biology, School of MedicineTwin 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.