4.6 Article

DNA methylation-based measures of biological age: meta-analysis predicting time to death

期刊

AGING-US
卷 8, 期 9, 页码 1844-1865

出版社

IMPACT JOURNALS LLC
DOI: 10.18632/aging.101020

关键词

all-cause mortality; lifespan; epigenetics; epigenetic clock; DNA methylation; mortality

资金

  1. NIH/NIA [1U34AG051425-01]
  2. Cooperative Studies Program/ERIC
  3. ESRC [ES/N000404/1] Funding Source: UKRI
  4. MRC [MR/M013111/1] Funding Source: UKRI
  5. Economic and Social Research Council [ES/N000404/1] Funding Source: researchfish
  6. Medical Research Council [MR/M013111/1, MR/K026992/1] Funding Source: researchfish
  7. National Institute for Health Research [NF-SI-0514-10027, NF-SI-0507-10228] Funding Source: researchfish

向作者/读者索取更多资源

Estimates of biological age based on DNA methylation patterns, often referred to as epigenetic age, DNAm age, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p <= 8.2x10(-9)), independent of chronological age, even after adjusting for additional risk factors (p<5.4x10(-4)), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10(-43)). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

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