Epigenetic drift score captures directional methylation variability and links aging to transcriptional, metabolic, and genetic alterations.

Epigenetic drift refers to the gradual and stochastic accumulation of epigenetic changes, such as DNA methylation variability, with advancing age. Although increasingly recognized for its potential role in aging biology, its extent, biological significance, and population specificity remain insufficiently characterized. Here, we present the first comprehensive epigenome-wide drift study (EWDS) in a large Chinese cohort (n = 3538), with replication in two independent Chinese (total n = 1467) and two European cohorts (total n = 956), to investigate the scale and relevance of epigenetic drift across populations. Through simulation, we identify White's test as the most powerful method among four alternatives for detecting age-associated methylation variability. Our EWDS reveals that 10.8% (50,385 CpGs) of sites on the 850 K EPIC array exhibit epigenome-wide significant drift, with 99% showing increased interindividual variability (positive drift) and 1% showing decreased variability (negative drift). Integration with single-cell RNA-seq data demonstrates that positive drift-CpGs are associated with increased transcriptional variability and upregulation in specific cell types, whereas negative drift-CpGs exhibit the opposite effect. We develop epigenetic drift scores (EDSs) to quantify individual drift burden; these scores are strongly age-associated and correlate with lipidomic profiles and clinical aging indicators. Longitudinal data confirm within-individual accumulation of drift over time. Finally, a GWAS of EDS identifies genetic determinants of drift magnitude, including heritable loci (e.g.,