In recent years, polygenic approaches have emerged as one method to characterize aggregate measured genetic risk (Wray et al., 2014). These efforts were motivated by the growing recognition that many genes and genetic variants, each of small individual effects, contribute to complex disorders; as well as the practical, clinical goal of being able to accurately predict disease and disorder from genetic information. Most commonly, polygenic scores are created by summing the number of “risk” alleles an individual carries across a selected set of single nucleotide polymorphisms (SNPs), weighted by empirical information from genetic association results obtained from an independent discovery sample. In effect, polygenic scores capture the composite additive effect of these multiple variants. This approach was initially used in the study of schizophrenia (The International Schizophrenia Consortium, 2009) and has since been applied to numerous complex traits (Dudbridge, 2013). As reviewed by Hart & Kranzler (2015), several recent studies have successfully used polygenic score approaches to predict alcohol-related outcomes (Yan et al., 2014, Vrieze et al., 2013, Frank et al., 2012, Kos et al., 2013, Levey et al., 2014).
