In the absence of success in identifying individual genes that account for a substantial proportion of the variance in alcohol outcomes, and lack of expectation that such genes will be found in the near future, polygenic approaches have emerged as one paradigm for examining aggregate measured genetic effects that can have predictive power when individual genes cannot [19]. This approach typically uses results from a genome-wide association study in a discovery sample. Using a p-value threshold much more liberal than what would be required for genome-wide significance, a polygenic risk score for each individual in an independent target sample is calculated by summing up the number of alleles for each single nucleotide polymorphism (SNP) weighted by the effect size drawn from a GWAS. The score then represents the composite additive effect of these multiple variants, which likely includes a mixture of true genetic signals and noise.
