We sought to compare the performance of the latent factor-based PRSs (Consumption and Problems PRSs) against the performance of their sum score counterparts (AUDIT-C and AUDIT-P PRSs) in predicting different alcohol phenotypes. To this end, we applied two approaches to our PRS analyses: (i) cross-dimension PRS models (i.e., Consumption + Problems PRSs included as simultaneous predictors), and (ii) cross-method PRS models (i.e., Consumption + AUDIT-C PRSs included as simultaneous predictors in a model, and Problems + AUDIT-P PRSs included as simultaneous predictors in a model). We corrected for the total number of outcome phenotypes across the validation samples using a conservative Bonferroni p value = 8.33E-3, since the same PRSs were used as predictors across models (and were correlated with each other).
