It isn’t surprising to find that epigenetic clocks predict mortality more effectively than simple clinical measures such as individual biomarkers of age-related chronic inflammation. Epigenetic clocks are derived from many more data points, and at least some clocks, such as the Dunedin Pace of Aging clock, were constructed with the intent of predicting mortality. Nonetheless, one has to run the numbers. Here, researchers look at the ability of various measures and combinations of measures to predict mortality in a large database of human epidemiological data, and find that the epigenetic clock outperforms other options, but is still better augmented with a few clinical measures.
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.
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).
In conclusion, among the fourteen investigated biomarkers of aging, DunedinPACE emerged with the strongest and most consistent association with mortality.
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