In the present study, we evaluate the independent and overlapping genetic contributions to AUDIT-C and AUD in a single large multi-ancestry sample from the Million Veteran Program (MVP)22. Large-scale biobanks such as the MVP offer the potential to link genes to health-related traits documented in the electronic health record (EHR) with greater statistical power than can ordinarily be achieved in prospective studies23. Such discoveries improve our understanding of the etiology and pathophysiology of complex diseases and their prevention and treatment. To that end, we use a common data source—longitudinal repeated measures of alcohol-related traits from the national Veterans Health Administration (VHA) EHR—to obtain the mean, age-adjusted AUDIT-C score and International Classification of Diseases (ICD) alcohol-related diagnosis codes over more than 11 years of care24. We then conduct a GWAS of each trait followed by downstream analysis of the findings in which we construct Polygenic Risk Scores (PRS) for both traits and show that they are associated with alcohol-related disorders in two independent samples. The availability of data on alcohol consumption from the AUDIT-C and a formal diagnosis of AUD from
