Positioning personal polygenic risk score against the population background

Polygenic risk scores, or PRS, have been widely used across many traits to estimate polygenic risk, pleiotropy, and disease prediction. While PRS has the potential to be simple and informative they are not generally interpretable and not directly comparable between studies. They depend on the specific approach used, the chosen parameters, the number of genetic variants included and the underlying population structure. One way to improve comparability is to place an individual’s score in the context of the PRS distribution of the ancestry-matched population. In this work, we present a method to estimate the parameters of PRS distributions in any population, using only publicly available summary data. It can be applied to quickly assess individual’s polygenic disease risk for any complex genetic disorder assuming that risk loci are shared across populations. We demonstrate the accuracy of this method through simulations and present population-specific PRS examples derived from genome-side association studies (GWAS) of two neurodegenerative diseases, Alzheimer’s disease (AD) and amyotrophic lateral sclerosis (ALS) using data from the 1000 Genomes Project.