The omission of developmental considerations from GWAS has downstream consequences for statistical analyses that leverage GWAS summary statistics for genetic prediction of phenotypes with polygenic scores (PGS), reducing the effectiveness of PGS in younger target samples. For example, PGS derived from developmentally-agnostic GWAS (Liu et al. 2019) predict 0.58% and 0.61% of the variance in alcohol consumption in adolescence and early adulthood, respectively (Kandaswamy et al. 2021), but predict 2.4% of the variance in alcohol consumption in an older target sample (age 24-32; Liu et al. 2019). A recent study that examined age-specific effects of an alcohol consumption PGS from an adult discovery sample (Kranzler et al. 2019) found that the PGS were associated with alcohol use in adulthood, but not adolescence (Elam et al. 2021). Similar patterns may be expected for PGS that are derived from adolescent samples and applied to adult samples. Despite previous findings that the nature and magnitude of genetic effects vary throughout development (Aliev et al. 2015; Dick et al. 2006; Edwards & Kendler, 2013; Kendler et al. 2011; Meyers et al. 2014; Sakai et al. 2010), PGS have not been constructed to model this variability.
