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Associations of DNA Methylation Algorithms of Aging With Cardiovascular Disease and Mortality Risk Among US Older

Xian Cui1, Shiqun Sun2, Hui Zhang3

  • 1Diagnostic Imaging Center, Shanghai Children's Medical Center School of Medicine, Shanghai Jiao Tong University Shanghai 200127 China.

Journal of the American Heart Association
|May 2, 2025
PubMed

Insights

DNA methylation (DNAm) algorithms like GrimAgeMortacc and GrimAge2Mortacc show promise for predicting cardiovascular disease (CVD) risk and mortality. These epigenetic clocks offer valuable insights for assessing adverse health outcomes in older adults.

Area of Science:

  • Epigenetics
  • Gerontology
  • Cardiovascular Medicine

Background:

  • DNA methylation (DNAm) algorithms are emerging predictors of aging and adverse health outcomes.
  • Existing DNAm algorithms show variable performance in cardiovascular disease (CVD) risk stratification.
  • A systematic investigation is needed to assess the predictive utility of various DNAm algorithms for CVD and mortality risk.

Purpose of the Study:

  • To systematically evaluate the associations of 12 DNAm algorithms with CVD risk.
  • To assess the predictive performance of these algorithms for CVD mortality.
  • To determine the consistency of these associations across demographic subgroups.

Main Methods:

  • Utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999-2002.
  • Assessed 12 DNAm algorithms (e.g., HannumAgeacc, PhenoAgeacc, GrimAgeMortacc, GrimAge2Mortacc) in relation to CVD and mortality risk.
  • Employed multivariable regression models to calculate odds ratios (ORs) and hazard ratios (HRs) per standard deviation increase in DNAm algorithms.

Main Results:

  • GrimAgeMortacc and GrimAge2Mortacc were significantly associated with coronary heart disease and heart attack (ORs 2.15-2.76 per SD).
  • Several algorithms showed significant associations with CVD mortality, including HannumAgeacc, PhenoAgeacc, ZhangAgeacc, GrimAgeMortacc, and GrimAge2Mortacc (HRs 1.13-1.90 per SD).
  • Associations remained consistent across biological sex, age groups, and race/ethnicity.

Conclusions:

  • DNA methylation algorithms, especially GrimAgeMortacc and GrimAge2Mortacc, show potential as tools for CVD risk stratification.
  • These epigenetic markers are valuable for assessing mortality risk associated with cardiovascular conditions.
  • The findings support the use of specific DNAm algorithms in clinical settings for improved risk assessment.
Abstract

Keywords:
CVD mortality riskCVD riskDNA methylationage accelerationepigenetic clock

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