Genetic Correlates of Biological Aging and the Influence on Prediction of Mortality

Abstract

Abstract Longevity and disease-free survival are influenced by a combination of genetics and lifestyle. Biological age (BioAge), a measure of aging based on composite biomarkers, may outperform chronological age in predicting health and longevity. This study investigated the relationship between genetic risks, lifestyle factors, and delta age (Δage), estimated as the difference between biological and chronological age. BioAge and Δage were calculated for 52 418 participants from the population-based Lifelines cohort. We computed 2 independent polygenic risk scores (PRS) for health span and DNA methylation-based aging clock to characterize genetic risks. The capacity of BioAge to predict all-cause mortality when adjusted for chronological age and genetic risks for aging, was assessed. Obesity, lifestyle, socioeconomic status, sex, and genetic variations in a population contributed to the differences in the rates of accelerated aging. The overall risk of death for a 1-year increase in BioAge for a given chronological age and sex among the genotyped participants was 11% (HR = 1.11; 95% CI: 1.09, 1.13). After adjusting for genetic factors, BioAge maintained its sensitivity for predicting mortality. Findings from this study ascertain that BioAge can be a useful tool for risk stratification in research and aging interventions.