A Comparison of 5 Measures of Accelerated Biological Aging and Their Association With Incident Cardiovascular Disease: The CARDIA Study.

ABSTRACT

BACKGROUND: Accelerated biological aging is an increasingly popular way to track the acceleration of biology over time that may not be captured by calendar time. Biological aging has been linked to external and internal chronic stressors and has the potential to be used clinically to understand a person's personalized functioning and predict future disease. We compared the association of different measures of biological aging and incident cardiovascular disease (CVD) overall and by race. METHODS AND RESULTS: We used multiple informants models to compare the strength of clinical marker-derived age acceleration, 5 measures of epigenetic age acceleration (intrinsic and extrinsic epigenetic age acceleration, GrimAge acceleration, and PhenoAge acceleration), and 1 established clinical predictor of future CVD, Framingham 10-year risk score, with incident CVD over an 11-year period (2007-2018). Participants were 913 self-identified Black or White (41% and 59%, respectively) female or male (51% and 49%, respectively) individuals enrolled in the US-based CARDIA (Coronary Artery Risk Development in Young Adults) cohort study. The analytic baseline for this study was the 20-year follow-up examination (2005-2006; median age 45 years). We also included race-specific analysis. We found that all measures were modestly correlated with one another. However, clinical marker-derived age acceleration and Framingham 10-year risk score were more strongly associated with incident CVD than all the epigenetic measures. Clinical marker-derived age acceleration and Framingham 10-year risk score were not significantly different than one another in their association with incident CVD. CONCLUSIONS: The type of accelerated aging measure should be taken into consideration when comparing their association with clinical outcomes. A multisystem clinical composite shows associations with incident CVD equally to a well-known clinical predictor.