In this study, we performed admixture mapping using AA individuals from the Collaborative study on the Genetics of Alcoholism (COGA) (Reich et al., 1998), Study of Addiction: Genetics and Environment (SAGE) (Bierut et al., 2010), Alcohol Dependence GWAS in European and African Americans (Yale-Penn) (Gelernter et al., 2014), and an African American cohort from the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Duplicate individuals among those studies were removed. We focused on four phenotypes: DSM-IV (American Psychiatric Association, 1994) alcohol dependence diagnosis; DSM-IV alcohol dependence criterion count as a measure of alcohol dependence severity (Lai, Wetherill, Bertelsen, et al., 2019), and two scores from the Self-Rating of Effects of Ethanol (SRE) questionnaire (Schuckit, Smith, & Tipp, 1997) as measures of response to alcohol. In genome-wide significant (GWS) regions, we conducted fine mapping using genotyped and imputed data to identify potentially causal variants. Lastly, we performed conditional analyses to test whether the variants identified during fine mapping could explain the admixture mapping association signal.
