Common DNA sequence variation influences epigenetic aging in African populations.

Area of Science:

• Genetics
• Genomics
• Aging Research

Background:

• Aging is linked to genome-wide DNA methylation changes, enabling epigenetic age prediction.
• Existing epigenetic age predictors are primarily trained on European-ancestry individuals and do not account for methylation quantitative trait loci (meQTL).

Purpose of the Study:

• To assess epigenetic age prediction accuracy in understudied African populations.
• To develop a novel epigenetic age predictor robust to genetic variation and meQTL effects.
• To explore the relationship between genetics, epigenetic aging, and longevity.

Main Methods:

• Analysis of age, genotype, and CpG methylation in Baka, ‡Khomani San, and Himba populations.
• Evaluation of existing epigenetic age prediction methods in these cohorts.
• Development of a new age predictor incorporating meQTL information.
• Investigation of genetic variants associated with epigenetic age acceleration and longevity.

Main Results:

• Published epigenetic age predictors exhibited higher mean errors in the studied African cohorts compared to European-ancestry individuals.
• Unaccounted DNA sequence variation was identified as a key factor in reduced prediction accuracy.
• The newly developed meQTL-informed age predictor demonstrated consistent accuracy across diverse genetic backgrounds.
• Older individuals and those with lower epigenetic age acceleration carried more epigenetic age-reducing genetic variants.

Conclusions:

• Epigenetic age prediction requires models that account for population-specific genetic variation and meQTLs.
• A novel, genetically robust epigenetic age predictor was developed.
• Heritable genetic factors may influence longevity through modulation of epigenetic aging.