Polygenic risk scores in clinical psychology: Bridging genomic risk to individual differences

Abstract

Genomewide association studies (GWAS) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (OR<1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWAS can be used to generate polygenic risk scores (PRS) in independent, target datasets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition). The intuitive appeal and generalizability of PRS have led to their widespread use and new insight into mechanisms of polygenic liability. However, presently, when applied across traits they account for small effects (less than 3% of variance) and are relatively uninformative for clinical treatment and, in isolation, provide no insight into molecular mechanisms. Larger GWAS are needed to increase their precision and novel approaches integrating various data sources (e.g., multi-trait analysis of GWAS) may improve the utility of current PRS.