Aging measures and cancer in the Health and Retirement Study (HRS).
Level 3 - non-randomized controlled study
Prospective cohort study analyzing biological age metrics and mortality outcomes in a population sample.
PubMed 40593734 · doi:10.1038/s41467-025-60913-z
What was done
Authors examined associations of biological age (BA) acceleration with cancer prevalence and mortality using Health and Retirement Study (HRS) data. BA was evaluated via physiological and subjective metrics—Klemera and Doubal method (KDM-BA), phenotypic age (PhenoAge), and subjective age (SA)—in 946 cancer survivors and 4,555 controls. Epigenetic clocks (Horvath, Hannum, Levine, GrimAge, Zhang Score [ZS], and methylation-based pace of aging [mPOA]) were assessed in 582 cancer survivors and 2,805 controls. Age acceleration was calculated by regressing BA measures on chronological age. Prevalence associations were tested with logistic regression, and mortality was evaluated using Cox regression.
What was found
Cancer prevalence was significantly associated with Hannum, GrimAge, SA, and ZS metrics in multivariable models (specific odds ratios not reported in the abstract). In cancer survivors, mortality was significantly associated with PhenoAge, Hannum, Levine, GrimAge, and ZS, with GrimAge demonstrating the strongest association (hazard ratio per 1 standard deviation = 1.80, p < 0.001). In controls, mortality was significantly associated with KDM-BA, PhenoAge, and ZS.
Why it matters
This study shows that specific epigenetic clocks and phenotypic age metrics reflect accelerated aging in cancer survivors and may serve as useful prognostic markers for survival.
Limits
The abstract omits exact effect estimates, confidence intervals, and p-values for most evaluated clocks and prevalence associations. Observational design cannot determine causality, and the abstract does not report specific cancer types, stages, or treatment regimens.
Cited by
- contradicts Subjective age is a better predictor of longevity than biological or chronological age.