Common DNA sequence variation influences epigenetic aging in African populations

Area of Science:

• Genetics
• Epigenetics
• Population Health

Background:

• Aging causes genome-wide DNA methylation changes, enabling epigenetic age prediction.
• Current epigenetic age models are biased towards 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 more accurate epigenetic age predictor by accounting for meQTL effects across diverse genetic backgrounds.
• To investigate the relationship between genetic variants, epigenetic age, and longevity.

Main Methods:

• Analysis of DNA methylation and genotype data in Baka, ‡Khomani San, and Himba populations.
• Comparison of existing epigenetic age predictors' performance in these cohorts versus European-ancestry individuals.
• Development of a novel age predictor model incorporating meQTL information.

Main Results:

• Published epigenetic age predictors exhibited higher mean errors in the studied African populations compared to European-ancestry individuals.
• Unaccounted DNA sequence variation significantly impacts predictor accuracy.
• The novel meQTL-aware model demonstrated consistent accuracy across diverse genetic backgrounds.
• Older individuals and those with lower epigenetic age acceleration possessed more genetic variants associated with reduced epigenetic age.

Conclusions:

• Epigenetic age prediction requires models robust to diverse genetic backgrounds.
• Heritable genetic factors collectively influence human healthspan and longevity.
• Accounting for meQTL is crucial for accurate and equitable epigenetic age prediction across populations.