Table 2 displays the results of the linear models assessing how well the polygenic risk scores predict alcohol problems in each validation sample. Each “block” of the table represents a discovery-validation set, with the discovery GWAS sample in the row and the validation sample in the column. Within the population-based samples of ALSPAC and FT12 (upper blocks of Table 2), polygenic scores estimated based on weights from the ALSPAC GWAS were highly significant, accounting for 1.03% of the variance in AUD symptoms in FT12. In the reciprocal analyses, scores based on GWAS weights from the smaller FT12 sample were positively but not significantly associated (p =.006) with alcohol problems in the ALSPAC validation sample. Within the clinically ascertained samples of COGA and IASPSAD (lower blocks of Table 2), polygenic scores weighted in one sample did not significantly predict AUDs in the other, although there was a nominal trend (p = .03 to p = .07) in the expected direction.
