Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders. Academic Article uri icon

abstract

  • 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.

published proceedings

  • Behav Genet

altmetric score

  • 2.25

author list (cited authors)

  • Cho, S. B., Aliev, F., Clark, S. L., Adkins, A. E., Edenberg, H. J., Bucholz, K. K., Porjesz, B., & Dick, D. M.

citation count

  • 3

complete list of authors

  • Cho, Seung Bin||Aliev, Fazil||Clark, Shaunna L||Adkins, Amy E||Edenberg, Howard J||Bucholz, Kathleen K||Porjesz, Bernice||Dick, Danielle M

publication date

  • July 2017