Epigenetic clocks have been widely applied to assess biological ageing, with Age Acceleration (AA) serving as a key metric linked to adverse health outcomes, including mortality. However, the comparative predictive value of AAs derived from different epigenetic clocks for mortality risk has not been systematically evaluated. In this retrospective cohort study based on 1,942 NHANES participants (median age 65 years; 944 women), we examined the associations between AAs from multiple epigenetic clocks and the risks of all-cause, cancer-specific, and cardiac mortality. Restricted cubic spline models were used to assess the shape of these associations, and Cox proportional hazards regression was employed to quantify risk estimates. Model performance was compared using the Akaike Information Criterion (AIC) and concordance index (C-index). Our findings revealed that only GrimAge AA and GrimAge2 AA demonstrated approximately linear and positive associations with all three mortality outcomes. Both were significantly associated with increased risks of death, and these associations were consistent across most subgroups. GrimAge and GrimAge2 AAs showed very similar performance in predicting all-cause, cancer and cardiac mortality, with only small differences in AIC values and C-index scores. These findings suggest that both GrimAge and GrimAge2 are effective epigenetic biomarkers for mortality risk prediction and may be valuable tools in future ageing-related research.

Epigenetic clocks have been widely applied to assess biological ageing, with Age Acceleration (AA) serving as a key metric linked to adverse health outcomes, including mortality. However, the comparative predictive value of AAs derived from different epigenetic clocks for mortality risk has not been systematically evaluated. In this retrospective cohort study based on 1,942 NHANES participants (median age 65 years; 944 women), we examined the associations between AAs from multiple epigenetic clocks and the risks of all-cause, cancer-specific, and cardiac mortality. Restricted cubic spline models were used to assess the shape of these associations, and Cox proportional hazards regression was employed to quantify risk estimates. Model performance was compared using the Akaike Information Criterion (AIC) and concordance index (C-index). Our findings revealed that only GrimAge AA and GrimAge2 AA demonstrated approximately linear and positive associations with all three mortality outcomes. Both were significantly associated with increased risks of death, and these associations were consistent across most subgroups. GrimAge and GrimAge2 AAs showed very similar performance in predicting all-cause, cancer and cardiac mortality, with only small differences in AIC values and C-index scores. These findings suggest that both GrimAge and GrimAge2 are effective epigenetic biomarkers for mortality risk prediction and may be valuable tools in future ageing-related research.