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Associations of Twelve DNA Methylation Signatures of Aging with Mortality
17 Pages Posted: 9 Oct 2024
More...Abstract
Background: Multiple DNA methylation (DNAm) based signatures of aging have been derived and shown to predict mortality. However, the predictive capacity of these signatures differs and requires further validation and comparison across diverse populations.
Methods: A total of 2532 participants aged older than 50 years were included from the U.S. National Health and Nutrition Examination Survey 1999-2002. Dates and causes of death were linked to the National Death Index records through December 31, 2019. Twelve DNAm-based aging signatures were derived from distinct algorithms, including HorvathAge, HannumAge, SkinBloodAge, LevinePhenoAge, ZhangAge, LinAge, WeidnerAge, VidalBraloAge, GrimAge, GrimAge2, HorvathTelo, and DunedinPoAm.
Findings: During a median follow-up period of 17.17 years, 1361 deaths were observed. In the pooled dataset, significant associations with all-cause mortality were observed for HorvathAge, HannumAge, LevinePhenoAge, GrimAge, GrimAge2, and DunedinPoAm, with multivariable-adjusted hazard ratios per standard deviation increase ranging from 1.19 (HannumAge) to 2.12 (GrimAge2) after applying Bonferroni correction (P-value < 0.004). Notably, several algorithms demonstrated robust predictive capabilities for all-cause mortality, with Harrell’s C-statistic for GrimAge2 at 0.760 (95% confidence interval [CI]: 0.747-0.772), surpassing that of chronological age (C-statistic = 0.735, 95% CI: 0.725-0.745) and other algorithms (C-statistic ranged from 0.587 to 0.720).
Interpretation: These findings suggest that GrimAge2 may serve as a robust predictor of mortality, outperforming both chronological age and other DNAm signatures.
Funding: This work was supported by grants from the National Natural Science Foundation of China (NO. 82301768) and International Joint Laboratory on Tropical Diseases Control in Greater Mekong Subregion (NO. 21410750200).
Declaration of Interest: The authors declare that they have no relevant financial interests.
Keywords: DNAm algorithms, US older adults, Mortality, Cohort study
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