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

TL;DR

This study explores how different epigenetic clocks predict aging by analyzing gene expression and biological pathways, revealing unique mechanisms behind each clock.

Contribution

The study introduces transcriptomic aging gene scores (TAGS) that enhance the understanding and utility of epigenetic clocks.

Findings

Each epigenetic clock captures distinct biological processes and transcriptional signatures.

TAGS showed stronger associations with age-related diseases and mortality than some DNA methylation clocks.

The findings highlight more unique than shared mechanisms among the clocks.

Abstract

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 3,227 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). Differential gene expression analyses identified clock-specific transcriptional signatures and enriched biological pathways, revealing substantial heterogeneity in the molecular processes captured by each clock. We further derived transcriptomic aging gene scores (TAGS), from differentially expressed genes of 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 revealed more unique than common biological processes underlying clocks, illuminate their internal mechanisms, and advance their interpretability for aging research and clinical applications.

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