Beyond genetic correlations from LDSC, polygenic risk scores (PRS) offer an alternative approach for demonstrating genetic overlap between two traits (e.g. alcohol consumption and AUD). PRS represent the additive effects of independent single nucleotide polymorphisms (SNPs) that are weighted by their effect sizes from a “discovery” GWAS (International Schizophrenia Consortium, 2009). With this approach, every individual in the independent “target” sample is assigned a score that indexes their estimated genetic propensity to the behavior studied in the discovery GWAS. The phenotype of interest in the target sample is then regressed on the polygenic score, and the strength of this association is assessed using R2 or other measures of predictor efficacy (e.g., Area Under the Curve (AUC)). Although the PRS incorporates additional SNPs beyond those meeting the stringent genome-wide significance threshold, PRS typically explain a very small percentage (usually <10%) of the variance in the target sample phenotype (Dudbridge, 2013; Wray et al., 2014). How much variance PRS explain is dependent upon the SNP heritability of the phenotype, the size of both the discovery GWAS and the target sample, the selection
