Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleotide polymorphisms (SNPs) that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating and analyzing African population data for clinical evaluation of PRSs of interest and predicting rare diseases.
