DNA methylation clocks for estimating biological age in Chinese cohorts

Abstract

Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation at specific CpG sites. However, available DNA methylation (DNAm) age predictors are based on datasets with limited ethnic representation. Moreover, a systematic comparison between DNAm data and other omics datasets has not yet been performed. To address these knowledge gaps, we generated and analyzed DNA methylation datasets from two independent Chinese cohorts, revealing age-related DNAm changes. Additionally, a DNA methylation (DNAm) aging clock (iCAS-DNAmAge) and a group of DNAm-based multi-modal clocks for Chinese individuals were developed, with most of them demonstrating strong predictive capabilities for chronological age. The clocks were further employed to predict factors influencing aging rates. The DNAm aging clock, derived from multi-modal aging features (compositeAge-DNAmAge), exhibited a close association with multi-omics changes, lifestyles, and disease status, underscoring its robust potential for precise biological age assessment. Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace, providing basis for evaluating aging intervention strategies.