Differences in environmental exposure, gene-gene interactions, gene-environment interactions, historical population size dynamics, statistical noise, some potential causal effect differences, and/or other factors will further limit generalizability for genetic risk scores in an unpredictable, trait-specific fashion46–49. Complex traits do not behave in a genetically deterministic manner, with some environmental factors dwarfing individual genetic effects, creating outsized issues of comparability across globally diverse populations. Among psychiatric disorders for example, whereas schizophrenia has a nearly identical genetic basis across East Asians and Europeans (rg=0.98)40, substantially different rates of alcohol use disorder across populations are partially explained by differences in availability and genetic differences impacting alcohol metabolism50. While non-linear genetic factors explain little variation in complex traits beyond a purely additive model51, some unrecognized nonlinearities and gene-gene interactions can also induce genetic risk prediction challenges, as pairwise interactions are likely to vary more across populations than individual SNPs. Mathematically, we can simplistically think of this in terms of a two-SNP model, in which the sum of two SNP effects is likely to explain more phenotypic variance than the product of the same SNPs. Some
