Measures of Biologic Age in a Community Sample Predict Mortality and Age-Related Disease: The Framingham Offspring Study

Background: We tested the association of biologic age (BA) measures constructed from different types of biomarkers with mortality and disease in a community-based sample. Methods: In Framingham Offspring participants at Exams 7 (1998-2001, mean age 62 ± 10) and 8 (2005-2008, mean age 67 ± 9), we used the Klemera-Doubal method to estimate clinical BA and inflammatory BA and computed the difference (∆age) between BA and CA. Clinical ∆age was computed at Exam 2 (1979-1983, mean age 45 ± 10). At Exam 8, we computed measures of intrinsic and extrinsic epigenetic age. Participants were followed through 2014 for outcomes. Cox proportional hazards models tested the association of each BA estimate with each outcome adjusting for covariates. Results: Sample sizes ranged from 2532 to 3417 participants. In multivariable models, each 1-year increase in clinical ∆age at Exam 2 (hazard ratio [HR] = 1.04-1.06, p < 2 × 10-16) and clinical ∆age and inflammatory ∆age at Exam 7 significantly increased the hazards of mortality and incident cardiovascular disease (HR = 1.01-1.05, p < 2 × 10-7), whereas inflammatory ∆age increased the hazards of cancer (HR = 1.01, p < .05). At Exam 8, increased clinical ∆age, inflammatory ∆age, and extrinsic epigenetic age all significantly increased the hazard of mortality (HR = 1.03-1.05, all p < .05); clinical ∆age and inflammatory ∆age increased cardiovascular disease risk (HR = 1.04-1.05, all p < .01); and clinical ∆age increased cancer risk (HR = 1.03, p < .01) when all three BA measures were included in the model. Intrinsic epigenetic age was not significantly associated with any outcome. Conclusions: Our findings suggest BA measures may be complementary in predicting risk for mortality and age-related disease.