Lack of cross-study harmonization is evident across several aspects of the methods, but is not systematic across one group of samples or another, so we would expect this to make our results more conservative rather than to induce spuriousness. This may have reduced our ability to detect true associations of the polygenic risk scores, especially given the small effect sizes that were found. However, we were well powered to detect effects accounting for >2% of the variance in AUDs, which would not be expected of a single gene but is reasonable for an aggregate genome-wide score. A combination of methods to improve gene identification (e.g. larger and less heterogeneous discovery samples, more precise phenotyping, integration of bioinformatics information) could be helpful in creating more accurate polygenic risk scores in the future, in addition to potentially identifying individually important genetic variants.
