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<p>Epigenetic clocks derived from DNA methylation robustly predict biological aging, health, and mortality, yet differ substantially in their predictive profiles. The biological processes underlying these differences remain poorly understood. Using data from 3227 participants in the U.S. Health and Retirement Study, with contemporaneous DNA methylation and RNA-sequencing, we examined the five most widely used epigenetic clocks (Horvath, Hannum, PhenoAge, GrimAge, and DunedinPACE). We conducted differential gene expression analyses to identify clock-specific gene expression levels and enriched biological pathways, to reveal substantial heterogeneity in the molecular processes captured by each clock. We further derived transcriptomic aging gene scores (TAGS) from differentially expressed genes associated with each age acceleration clock, and evaluated their associations with aging-related phenotypes. TAGS complemented DNAm clocks, and in several cases, showed stronger associations with age-related morbidities and mortality. Findings unveiled more unique than common biological processes underlying clocks, illuminating their internal mechanisms, and advancing their interpretability for aging research and clinical applications.</p>

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How epigenetic clocks tick: unpacking the black box by deciphering biological pathways and transcriptomic signatures of accelerated aging

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月20日

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  • Thalida Em Arpawong,
  • Steve Cole,
  • Harshanna Badhesha,
  • Jung Ki Kim,
  • Christopher R. Beam,
  • Eric T. Klopack,
  • Kimberly Siegmund,
  • Bharat Thyagarajan,
  • Eileen M. Crimmins

摘要

Epigenetic clocks derived from DNA methylation robustly predict biological aging, health, and mortality, yet differ substantially in their predictive profiles. The biological processes underlying these differences remain poorly understood. Using data from 3227 participants in the U.S. Health and Retirement Study, with contemporaneous DNA methylation and RNA-sequencing, we examined the five most widely used epigenetic clocks (Horvath, Hannum, PhenoAge, GrimAge, and DunedinPACE). We conducted differential gene expression analyses to identify clock-specific gene expression levels and enriched biological pathways, to reveal substantial heterogeneity in the molecular processes captured by each clock. We further derived transcriptomic aging gene scores (TAGS) from differentially expressed genes associated with each age acceleration clock, and evaluated their associations with aging-related phenotypes. TAGS complemented DNAm clocks, and in several cases, showed stronger associations with age-related morbidities and mortality. Findings unveiled more unique than common biological processes underlying clocks, illuminating their internal mechanisms, and advancing their interpretability for aging research and clinical applications.