Single- versus Multi-Ancestry Polygenic Risk Scores for CKD in Black Americans.

BACKGROUND: Chronic kidney disease (CKD) is a risk factor for cardiovascular disease and early death. Recently, polygenic risk scores (PRS) have been developed to quantify risk for CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PRS development overall. Moreover, European-ancestry derived PRS demonstrate diminished predictive performance in African ancestry populations.

METHODS: This study aimed to develop a PRS for CKD in Black Americans. We obtained score weights from a meta-analysis of genome-wide association studies (GWAS) for estimated glomerular filtration rate (eGFR) in the Million Veteran Program (MVP) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study to develop an eGFR PRS. We optimized the PRS risk model in a cohort of Participants from the Hypertension Genetic Epidemiology Network (HyperGEN). Validation was performed in subsets of Black participants of the Trans-Omics in Precision Medicine (TOPMed) Consortium and Genetics of Hypertension Associated Treatment (GenHAT) Study.

RESULTS: The prevalence of CKD-defined as stage 3 or higher-was associated with the PRS as a continuous predictor (OR[95% CI]:1.35[1.08,1.68]) and in a threshold-dependent manner. Further, including APOL1 risk status-a putative variant for CKD with higher prevalence among those of sub-Saharan African descent-improved the score's accuracy. PRS associations were robust to sensitivity analyses accounting for traditional CKD risk factors, as well as CKD classification based on prior eGFR equations. Compared with previously published PRS, the predictive performance of our PRS was comparable to a European-ancestry derived PRS for kidney traits. However, both single-ancestry PRS were less predictive than multi-ancestry derived PRS.

CONCLUSIONS: In this study, we developed a PRS that was significantly associated with CKD with improved predictive accuracy when including APOL1 risk status. However, PRS generated from multi-ancestry populations outperformed single-ancestry PRS in our study.