Nature Medicine · 2022 · 117 citations · 17 references
Life SciencesBiostatisticsGeneticsEpidemiologyGenetic EpidemiologyStatistical GeneticsGenetic RiskGenetic Risk AssessmentGenetic Risk FactorsGenetic Risk PredictionGenomic PredictionPolygenic Risk AssessmentAncestry-informed Risk PredictionCross-ancestry TransferabilityEnvironmental FactorsGenetic Risk StratificationPolygenic Risk Score TransferabilityPredictionRisk Prediction ScoresSummary Statistics
Abstract The poor transferability of genetic risk scores (GRSs) derived from European ancestry data in diverse populations is a cause of concern. We set out to evaluate whether GRSs derived from data of African American individuals and multiancestry data perform better in sub-Saharan Africa (SSA) compared to European ancestry-derived scores. Using summary statistics from the Million Veteran Program (MVP), we showed that GRSs derived from data of African American individuals enhance polygenic prediction of lipid traits in SSA compared to European and multiancestry scores. However, our GRS prediction varied greatly within SSA between the South African Zulu (low-density lipoprotein cholesterol (LDL-C), R 2 = 8.14%) and Ugandan cohorts (LDL-C, R 2 = 0.026%). We postulate that differences in the genetic and environmental factors between these population groups might lead to the poor transferability of GRSs within SSA. More effort is required to optimize polygenic prediction in Africa.
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