Common DNA sequence variation influences epigenetic aging in African populations.

Abstract

Aging is associated with genome-wide changes in DNA methylation in humans, facilitating the development of epigenetic age prediction models. However, these models have been trained primarily on European-ancestry individuals and none account for the impact of methylation quantitative trait loci (meQTL). To address these gaps, we analyze the relationships between age, genotype, and CpG methylation in 3 understudied populations: central African Baka (n = 35), southern African ‡Khomani San (n = 52), and southern African Himba (n = 51). We show that published prediction methods yield higher mean errors in these cohorts compared to European-ancestry individuals and find that unaccounted-for DNA sequence variation may be a significant factor underlying this loss of accuracy. We leverage information about the associations between DNA genotype and CpG methylation to develop an age predictor that is minimally influenced by meQTL and show that this model remains accurate across a broad range of genetic backgrounds. Intriguingly, we also find that the older individuals and those with lower epigenetic age acceleration carry more genetic variants linked to reduced epigenetic age. These findings support the hypothesis that multiple heritable factors collectively influence healthspan and longevity in human populations.