Telomere Length, Epigenetic Age Acceleration, and Mortality Risk in US Adult Populations: An Additive Bayesian Network Analysis.

Abstract

Telomere length and DNA methylation (DNAm) clocks serve as markers of biological aging and have been linked to mortality risk. This study applies additive Bayesian networks (ABNs) to examine associations between DNAm clocks, telomere length, and mortality, with a focus on racial and sex differences in aging. Data from three US cohorts-NHANES (n = 2522), HRS (n = 1029), and HANDLS (n = 92-470)-were analyzed using correlation matrices, Cox models, ABNs, and generalized structural equation models (GSEM) with mortality from the National Death Index. Epigenetic clocks, particularly GrimAgeEAA, HannumAgeEAA, and DunedinPoAM (or DunedinPACE), were stronger mortality predictors than telomere length. ABNs highlighted key relationships, consistently linking age and GrimAgeEAA to mortality in NHANES and HRS. GSEM models derived from ABNs indicated an inverse association between female sex and GrimAgeEAA in NHANES (β = -0.500) and HRS (β = -0.563), suggesting slower biological aging in women, although GrimAge clock incorporates sex in its definition. GrimAgeEAA strongly predicted mortality (LnHR, β ± SE of +0.476 ± 0.0393 in NHANES and +0.511 ± 0.0775 in HRS). Non-Hispanic Black adults exhibited accelerated aging via DunedinPoAM, partially mediating their higher mortality risk. Hispanic adults in NHANES had unique associations with PhenoAgeEAA (β = +0.197), a mortality predictor. DNAm clocks, particularly GrimAgeEAA, outperform telomere length in predicting mortality. Second-generation epigenetic aging markers offer insights into demographic disparities in aging and mortality, with ABNs revealing complex interrelations among aging biomarkers, sex, race, and mortality risk.