As GWAS continue to expand and include large-scale studies of treatment response, it is possible that PRS results may be clinically applicable and potentially even usefully guide personalized treatment recommendations in the distant future. Further, as multiplex gene editing in preclinical models advance, it is plausible that polygenic effects across systems can be modeled to identify potentially influential, covarying, or even novel pathways for future treatment development. In addition to using novel analytic tools such as LDPred and MTAG to enhance the predictive utility of PRS, it will be important to increase the size and diversity of GWAS samples alongside the use of refined and diverse phenotyping. For example, it is possible that genetic loci associated with disorder expression are entirely or partially distinct from those associated with mechanistic pathways and treatment response. Lastly, integrating polygenic GWAS statistics with functional data (Arloth et al., 2015) and pathway analyses may help guide the identification of potential treatment pathways.
