GrimAge Outperforms Other Epigenetic Clocks in the Prediction of Age-Related Clinical Phenotypes and All-Cause Mortality

The aging process is characterized by the presence of high interindividual variation between individuals of the same chronical age prompting a search for biomarkers that capture this heterogeneity. Epigenetic clocks measure changes in DNA methylation levels at specific CpG sites that are highly correlated with calendar age. The discrepancy resulting from the regression of DNA methylation age on calendar age is hypothesized to represent a measure of biological aging with a positive/negative residual signifying age acceleration (AA)/deceleration, respectively. The present study examines the associations of 4 epigenetic clocks-Horvath, Hannum, PhenoAge, GrimAge-with a wide range of clinical phenotypes (walking speed, grip strength, Fried frailty, polypharmacy, Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), Sustained Attention Reaction Time, 2-choice reaction time), and with all-cause mortality at up to 10-year follow-up, in a sample of 490 participants in the Irish Longitudinal Study on Ageing (TILDA). HorvathAA and HannumAA were not predictive of health; PhenoAgeAA was associated with 4/9 outcomes (walking speed, frailty MOCA, MMSE) in minimally adjusted models, but not when adjusted for other social and lifestyle factors. GrimAgeAA by contrast was associated with 8/9 outcomes (all except grip strength) in minimally adjusted models, and remained a significant predictor of walking speed, .polypharmacy, frailty, and mortality in fully adjusted models. Results indicate that the GrimAge clock represents a step-improvement in the predictive utility of the epigenetic clocks for identifying age-related decline in an array of clinical phenotypes promising to advance precision medicine.

Automated summary

The study indicates that the GrimAge clock is a significant improvement in predicting age-related decline in various clinical phenotypes compared to other epigenetic clocks, showing better predictive utility and promising to advance precision medicine.