Despite their widespread application, unique strengths, and the formative insight generated by their application, PRS have numerous limitations that require careful consideration. First, PRS are constrained to the sample size and phenotyping of the discovery GWAS. Such phenotyping may have a completely or partially distinct genetic architecture of comorbidity, related pathophysiology, response to current treatment, or interplay with the environment. Thus, GWAS across a variety of phenotypes and attempts to harmonize results is becoming increasing important. Second, traditional PRS are uninformed by system-level knowledge or functional annotation and provide no insight into molecular mechanisms. Alternative approaches, such as biologically informed multilocus profiles (BIMPS) that additively combine candidate variants based on their functionality, or methods that combine SNPs into meaningful pathways or networks by liaising with mRNA expression data, and even more sophisticated machine learning methods may overcome this limitation of PRS, but also have their own challenges (Bogdan et al., 2017). Along these lines, PRS are not currently amenable to direct translational work in nonhuman animals, though multiplex CRISPR/Cas9 approaches are beginning to be employed (Cong et al., 2013, Wang
