DNA Methylation Algorithms of Aging and Incident Cardiovascular Disease: A Prospective Cohort Study

While DNA methylation (DNAm)-based algorithms of aging show promise for predicting age-related diseases, their comparative utility for incident cardiovascular disease (CVD) remains underexplored. We aimed to systematically compare 13 DNAm algorithms in relation to CVD risk in older adults.

This prospective cohort study included 2112 participants from the US HRS (Health and Retirement Study) with baseline DNAm data (2016) and 6-year follow-up. DNAm profiling was performed using the Infinium MethylationEPIC BeadChip kit (EPIC, Illumina, San Diego, CA). Thirteen widely used DNAm algorithms of aging were evaluated. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs per 1-SD increase in risk scores for incident CVD, including any CVD, congestive heart failure, and stroke.

During a median of 37 months' follow-up, a total of 288 CVD cases (congestive heart failure, 38; stroke, 152) were observed. Zhang_DNAmAge, methylation Pace of Aging, and DNAmGrimAgeAcc showed positive associations with any CVD risk, with HRs per SD increase of 1.25 (95% CI, 1.07-1.45), 1.16 (95% CI, 1.02-1.33), and 1.24 (95% CI, 1.05-1.47), respectively. For specific CVD subtypes, DNAmGrimAge was associated with congestive heart failure risk (HR, 1.47 [95% CI, 1.11-1.95]), while both mPoA (HR, 1.24 [95% CI, 1.03-1.49]) and HorvathAcc (HR, 1.28 [95% CI, 1.07-1.55]) predicted incident stroke. Significant dose-response relationships (P-trend <0.05) were observed for Zhang_DNAmAge and DNAmGrimAgeAcc across all CVD outcomes.

Zhang_DNAmAge, methylation Pace of Aging, and DNAmGrimAgeAcc function as independent predictors of incident CVD. These epigenetic biomarkers may improve early CVD detection and risk stratification in aging populations.