Comparing fourteen consensus biomarkers of aging: epigenetic pace of aging as the strongest predictor of mortality in BASE-II

Mar 6, 2026Biomarker research

Fourteen common aging markers compared: epigenetic aging speed best predicts death risk in BASE-II study

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Longevity & Aging on OpenScience ↗PubMed ↗DOI ↗OA ↗

Abstract

Among fourteen biomarkers of aging, DunedinPACE emerged as the strongest predictor of mortality.

Hand grip strength, interleukin-6, standing balance, cognitive health, and the epigenetic clock significantly predicted all-cause mortality in adjusted models.
C-reactive protein, gait speed, insulin-like growth factor 1, blood pressure, muscle mass, growth-differentiating factor-15, frailty phenotype, and Timed-Up-and-Go were not linked to mortality.
A minimal biomarker set including muscle mass, standing balance, and DunedinPACE predicted mortality with a C-index of 0.63, comparable to the full model's C-index of 0.65.
Results were consistent across subgroup analyses based on causes of death.

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BACKGROUND: In many countries, lifespan has been increasing faster than healthspan, leading to more years spent with late-life disease and highlighting the need for reliable biomarkers to measure biological aging.

METHODS: We used data from the Berlin Aging Study II (BASE-II, 60-80 years of age at baseline, average follow-up 7.4 ± 1.5 years, range 3.9-10.4, n = 1,083) to compare 14 biomarkers of aging recently consented by an expert panel for the use as outcome measures in intervention studies: physiological (insulin-like growth factor 1 (IGF-1), growth-differentiating factor-15 (DNA methylation derived, DNAmGDF15)), inflammatory (high sensitivity C-reactive protein (CRP), interleukin-6 (IL-6)), functional (muscle mass, muscle strength, hand grip strength (HGS), Timed-Up-and-Go (TUG), gait speed, standing balance test, frailty phenotype (FP), cognitive health, blood pressure), and epigenetic (epigenetic clock, DunedinPACE). Cox proportional hazard regression analyses were performed to investigate their role in prediction of all-cause as well as cause-specific mortality. Results were adjusted for age, sex, lifestyle factors, and genetic ancestry.

RESULTS: In adjusted models of all-cause mortality, HGS, IL-6, standing balance, cognitive health, and the epigenetic clock (DunedinPACE) statistically significantly predicted mortality, with the epigenetic clock (DunedinPACE) emerging as the strongest predictor. CRP, gait speed, IGF-1, blood pressure, muscle mass, DNAmGDF15, FP and TUG were not associated with mortality in this study. These results were corroborated in subgroup analyses stratified by cause of death. Feature selection identified a minimal biomarker set consisting of muscle mass, standing balance, and epigenetic clock (DunedinPACE) that predicted mortality with nearly the same discriminative accuracy (C-index = 0.63) as the full model including all biomarkers (C-index = 0.65).

CONCLUSION: Among the fourteen investigated biomarkers of aging, DunedinPACE emerged with the strongest and most consistent association with mortality.