Ancestry-aligned polygenic scores combined with conventional risk factors improve prediction of cardiometabolic outcomes in African populations.

ABSTRACT:

Background

Cardiovascular diseases (CVD) are a major health concern in Africa. Improved identification and treatment of high-risk individuals can reduce adverse health outcomes. Current CVD risk calculators are largely unvalidated in African populations and overlook genetic factors. Polygenic scores (PGS) can enhance risk prediction by measuring genetic susceptibility to CVD, but their effectiveness in genetically diverse populations is limited by a European-ancestry bias. To address this, we developed models integrating genetic data and conventional risk factors to assess the risk of developing cardiometabolic outcomes in African populations.

Methods

We used summary statistics from a genome-wide association meta-analysis (n = 14,126) in African populations to derive novel g

SUBMITTER: Kamp M 

PROVIDER: S-EPMC11346299 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature