Both of these predictors show stronger associations with lifespan and mortality than Horvath’s age predictor. DNAPhenoAge and DNAmGrimAge predictors were developed to predict a composite phenotype (composed of chronological age and clinical markers). For example, a mitotic clock has been built for tracking the proliferation of cancer. However, a better way of predicting these health-related traits is developing a predictor with the target trait as a reference. Individuals with positive AAR are considered to be biologically older than their chronological age, and vice versa.Ī number of studies have identified associations between AAR and mortality, obesity and other health-related traits. These clocks utilize age acceleration residuals (AAR, defined as the residuals from regressing predicted age on chronological age) as a biomarker of ageing. Subsequently, a number of other DNA methylation-based ‘clocks’ have been developed. and Horvath built chronological age predictors (termed ‘epigenetic clock’) based on DNA methylation. Therefore, researchers have attempted to search for biomarkers of ageing that can predict functional capability at a later age. However, it is not necessarily a good predictor of biological ageing since individuals with the same chronological age can vary in health, especially in later life. Chronological age has been widely used as a marker of ageing due to ease and accuracy of measurement. This study indicates that the epigenetic clock can be improved by increasing the training sample size and that its association with mortality attenuates with increased prediction of chronological age.Īgeing is a major risk for diseases and mortality. We observed comparable performance of our predictor in non-blood tissues with a multi-tissue-based predictor. Predictors based on small sample size are prone to confounding by cellular compositions relative to those from large sample size. AAR from our best predictor (based on Elastic Net, ) exhibits no association with mortality in both LBC1921 (hazard ratio = 1.08, 95% CI 0.91–1.27) and LBC1936 (hazard ratio = 1.00, 95% CI 0.79–1.28). The association between AAR and mortality attenuates as prediction accuracy increases.
We found that in principle, a near-perfect age predictor could be developed when the training sample size is sufficiently large. In addition, we investigated the performance of our predictor in non-blood tissues. We use the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936) to examine whether the association between AAR (from these predictors) and death is affected by (1) improving prediction accuracy of an age predictor as its training sample size increases (from 335 to 12,710) and (2) additionally correcting for confounders (i.e., cellular compositions). In this study, we build multiple predictors based on training DNA methylation samples selected from 13,661 samples (13,402 from blood and 259 from saliva). However, it is currently unclear how a better prediction of chronological age affects such association. The deviation of predicted age from the actual age (‘age acceleration residual’, AAR) has been reported to be associated with death. Chronological age predictors built from DNA methylation are termed ‘epigenetic clocks’.
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