DNA methylation age is associated with mortality in a longitudinal Danish twin study

L Christiansen, A Lenart, Q Tan, JW Vaupel, A Aviv… - Aging cell, 2016 - Wiley Online Library
L Christiansen, A Lenart, Q Tan, JW Vaupel, A Aviv, M McGue, K Christensen
Aging cell, 2016Wiley Online Library
An epigenetic profile defining the DNA methylation age (DNA m age) of an individual has
been suggested to be a biomarker of aging, and thus possibly providing a tool for
assessment of health and mortality. In this study, we estimated the DNA m age of 378
Danish twins, age 30–82 years, and furthermore included a 10‐year longitudinal study of the
86 oldest‐old twins (mean age of 86.1 at follow‐up), which subsequently were followed for
mortality for 8 years. We found that the DNA m age is highly correlated with chronological …
Summary
An epigenetic profile defining the DNA methylation age (DNAm age) of an individual has been suggested to be a biomarker of aging, and thus possibly providing a tool for assessment of health and mortality. In this study, we estimated the DNAm age of 378 Danish twins, age 30–82 years, and furthermore included a 10‐year longitudinal study of the 86 oldest‐old twins (mean age of 86.1 at follow‐up), which subsequently were followed for mortality for 8 years. We found that the DNAm age is highly correlated with chronological age across all age groups (r = 0.97), but that the rate of change of DNAm age decreases with age. The results may in part be explained by selective mortality of those with a high DNAm age. This hypothesis was supported by a classical survival analysis showing a 35% (4–77%) increased mortality risk for each 5‐year increase in the DNAm age vs. chronological age. Furthermore, the intrapair twin analysis revealed a more‐than‐double mortality risk for the DNAm oldest twin compared to the co‐twin and a ‘dose–response pattern’ with the odds of dying first increasing 3.2 (1.05–10.1) times per 5‐year DNAm age difference within twin pairs, thus showing a stronger association of DNAm age with mortality in the oldest‐old when controlling for familial factors. In conclusion, our results support that DNAm age qualifies as a biomarker of aging.
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