An unbiased comparison of 14 epigenetic clocks in relation to 174 incident disease outcomes.
Level 3 - non-randomized controlled study
Prospective longitudinal cohort study assessing biomarker prediction of incident disease outcomes.
PubMed 41402269 · doi:10.1038/s41467-025-66106-y
What was done
Researchers evaluated 14 widely used epigenetic clocks across 18,859 individuals to predict all-cause mortality and 174 incident disease outcomes over a 10-year follow-up period. Associations were assessed using fully adjusted Cox proportional hazards regression models controlling for lifestyle and socioeconomic factors, alongside classification models comparing clocks against traditional risk factor baselines.
What was found
Second- and third-generation epigenetic clocks significantly outperformed first-generation clocks. There were 176 Bonferroni-significant associations (P < 0.05/174); in 27 diseases (including primary lung cancer and diabetes), the hazard ratio for the clock exceeded its association with all-cause mortality. Adding clock metrics to traditional risk factors significantly increased classification accuracy by >1% for 32 of the 176 associations. Interactions between clocks and sex or smoking status were minimal. Clocks performed best for respiratory and liver-related conditions.
Why it matters
This large-scale benchmark demonstrates that newer epigenetic clocks capture specific disease risks beyond general biological aging and traditional risk factors, while confirming that first-generation clocks have limited utility in clinical disease prediction.
Limits
The abstract does not report population demographics, geographic origin, or ethnic diversity of the cohort. Exact hazard ratios and confidence intervals are not provided in the abstract, and the incremental improvement in classification accuracy was modest (>1% in only 32 of 176 significant associations).
Cited by
- supports Large cohort studies, including the Generation Scotland study of 18,000 individuals and a Harvard study of 30,000 individuals, found that GrimAge is the best epigenetic clock for predicting mortality risk.
- supports The Horvath pan-tissue epigenetic clock tracks stem cell biology, hematopoietic stem cells, and leukemia precursors, but is not good for predicting mortality risk.