The past decade of genomic research has provided a wealth of information about the genetic variants that are being aggregated in these polygenic scores, including information about which variants are more or less likely a priori to have functional consequences on human traits and behaviors (ENCODE Project Consortium, 2012). In the same way that functional genomic information is important for understanding the biological coherence underlying GWAS results, it may also inform better ways to characterize individuals’ aggregate genetic risk for alcohol outcomes. Recent large-scale efforts have established that genetic variants associated with a variety of complex diseases and traits are not randomly distributed throughout the genome, but rather are stratified based on their genomic context (Schork et al., 2013, Finucane et al., 2015). Across many complex diseases and traits, there is modest evidence for an overrepresentation of SNPs with significant GWAS signals in or near protein-coding regions, and even stronger evidence for overrepresentation of SNPs in certain noncoding regions (Hindorff et al., 2009). Once considered “junk DNA”, it is now known that many regions outside of the exons that code
