Traditional Disease Risk Factors Outperform Epigenetic Clocks as Predictors of Non-Communicable Disease Morbidity in a Middle-Aged Cohort.

Abstract

DNA methylation-based epigenetic clocks have been highlighted as promising biomarkers of ageing, and they have been shown to robustly predict morbidity and mortality. However, current literature is lacking a formal analysis of the increased prediction accuracy, or the added value, of the epigenetic clocks over traditional risk factors, such as body composition, smoking, or alcohol consumption, in predicting common chronic diseases. Here, we have compared the most commonly used epigenetic clocks and traditional risk factors as predictors of incidence of ageing-associated non-communicable chronic disease in a 7-to-9-year follow-up in a middle-aged population cohort (n = 1108, aged 34 to 49 years at baseline). In our cohort, a statistical model consisting of a combination of traditional risk factors (age, sex, smoking, alcohol consumption, WHR, BMI) outperforms any model including an epigenetic clock. The added value of epigenetic clock measurements over simple and affordable traditional risk factors should be clearly established if epigenetic clocks are to be used in clinical settings or as tools of personal health monitoring.