Current evidence indicates that AUDs have a complex, highly polygenic architecture driven by the aggregation of hundreds or thousands of common genetic variants of very small individual effect (Sullivan et al., 2012). Heritability estimates using measured genotypes of common variants (23-33%: Yang et al., 2014; Mbarek et al., 2015), while somewhat lower than those from twin studies, confirm that current genotyping platforms harbor genetic variants of importance to AUDs, but few of these have been identified despite considerable research efforts. Candidate gene studies and the more stringent, atheoretical genome-wide association studies (GWAS) have found only a few replicable genetic variants underlying alcohol use and alcohol problems, and even the most robust of these account for a minimal proportion of the heritability (Hart and Kranzler, 2015). Polygenic risk score methods that sum genetic liability across many variants at nominal thresholds of association (i.e. The International Schizophrenia Consortium, 2009) have had some success in predicting individual risk for AUDs (Hart and Kranzler, 2015), but as of yet the variance accounted for by such scores is generally less than 3%, well below clinical prediction utility.
