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Öğe RISK PREDICTION WITH POLYGENIC RISK SCORES IN MULTI-ETHNIC SAMPLES(Elsevier, 2019) Aliev, Fazil; Salvatore, Jessica; Su, Jinni; Kuo, Sally I-Chun; Barr, Peter; Agrawal, Arpana; Cho, Seung Bin[No abstract available]Öğe STUDIES OF ALCOHOL RELATED PHENOTYPES ACROSS HUMAN, MOUSE AND INVERTEBRATE MODELS(Elsevier, 2017) Aliev, Fazil; Cho, Seung Bin; Grotewiel, Mike; Bettinger, Jill; Mathies, Laura; Riley, Brien; Alexander, Jeffry[No abstract available]Öğe Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders(Springer, 2017) Cho, Seung Bin; Aliev, Fazil; Clark, Shaunna L.; Adkins, Amy E.; Edenberg, Howard J.; Bucholz, Kathleen K.; Porjesz, BerniceTwin 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.
