Polygenic Risk Score in African populations: progress and challenges

Abstract

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.

Genetic association and transferability for urinary albumin-creatinine ratio as a marker of kidney disease in four Sub-Saharan African populations and non-continental individuals of African ancestry

“…However, PGS often translate poorly across different ancestries ( Martin et al, 2017 ; Kamiza et al, 2022 ; Kachuri et al, 2023 ). Since most published GWAS for kidney disease and kidney function markers are based on European ancestry populations, the predictive accuracy of models developed from these studies is expected to be significantly diminished for African populations ( Adam et al, 2022 ; Choudhury et al, 2022 ; Kamiza et al, 2023 ; Majara et al, 2023 ).…”

PRS-ing Forward to Identify Genetic Risk in Idiopathic Pulmonary Fibrosis

“…To date, PRS methodology has not had a substantial impact on clinical practice, and pitfalls of PRSs in predicting risk of age-related traits have been documented ( 12 ). Other issues related to maximizing the power and utility of PRS include limitations in the size of GWAS datasets available for relatively rare diseases, difficulties in extrapolation to ethnicities underrepresented in GWAS datasets, and underlying assumptions of lack of specific gene-by-environment interactions ( 13 , 14 ), all of which may have implications for application in IPF. Also, PRS methodology does not account for rare genetic variants, which can have a major impact on disease risk in the ∼8.5% of individuals with sporadic IPF who harbor loss-of-function rare variants in telomere maintenance genes ( 15 ).…”