Evidence map›Paper›PMID 40301953›Full record

ArticleClinical epigenetics2025

Associations between five indicators of epigenetic age acceleration and all-cause and cause-specific mortality among US adults aged 50 years and older.

Yun Zou, Jing Huang, Xiaoli Tang, Jixiong Xu

Abstract read
In one paragraph

Article in Clinical epigenetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yun Zou *Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanchang University, No 17 Yongwaizheng St., Nanchang, 330006, Jiangxi Province, People's Republic of China.
Jing Huang *School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Nanchang University, Nanchang, People's Republic of China.
Xiaoli TangSchool of Basic Medical Sciences, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, People's Republic of China. xltangmail@163.com.
Jixiong XuDepartment of Endocrinology and Metabolism, First Affiliated Hospital of Nanchang University, No 17 Yongwaizheng St., Nanchang, 330006, Jiangxi Province, People's Republic of China. Jixiong.xu@ncu.edu.cn.

Funding

Science and Technology Innovation Base Construction Plan of Jiangxi Province, China 20221ZDG02011Science and Technology Innovation Base Plan of Jiangxi Province, China 2020BCG74001
6 · The paper itself

Abstract

backgroundAlthough DNA methylation age estimators (DNAmAges) are reliable tools for predicting aging, their effectiveness in predicting mortality risk has not been fully validated. This study compared the predictive utility of five different DNAmAges (HorvathAge, HannumAge, PhenoAgeAge, GrimAge and GrimAge2) for all-cause and cause-specific mortality among adults aged ≥ 50 years.

methodsWe screened 1966 participants adults aged ≥ 50 from the National Health and Nutrition Examination Survey (1999-2002) and linked them to the National Death Index to obtain cause and status of death. We used weighted Cox proportional hazards models to examine the associations between epigenetic age acceleration (EAA) measured by different DNAmAges and all-cause and cause-specific mortality in the general population, adjusting for various covariates including age, smoking status and chronic diseases. We used restricted cubic splines to explore nonlinear associations. Finally, stratified analyses were performed to assess the relationship between DNA age estimators and stratification variables.

resultsThe multivariable adjustment model showed that EAA measured by HorvathAge (AAHorvathAge), HannumAge (AAHannumAge), PhenoAge (AAPhenoAge), GrimAge (AAGrimAge) and GrimAge2 (AAGrimAge) were significantly associated with the risk of death, among which AAGrimAge and AAGrimAge2 had stronger statistical correlation and the correlation pattern was positively correlated. Specifically, each 5-year increase in AAGrimAge was associated with a 44% increased risk of all-cause death, a 33% increased risk of cardiovascular death and a 54% increased risk of non-cardiovascular death. And each 5-year increase in AAGrimAge2 was associated with a 40% increased risk of all-cause death, a 33% increased risk of cardiovascular death and a 47% increased risk of non-cardiovascular death. In contrast, AAHorvathAge, AAHannumAge and AAPhenoAge showed a J-shaped correlation with the risk of all-cause mortality and non-cardiovascular mortality, with the inflection points of all-cause mortality and non-cardiovascular mortality occurring at AAHorvathAge of 2.29 and 2.8, AAHannumAge of 3.07 and 2.97, and AAPhenoAge of - 7.65 and 7.04, respectively. No interaction was found between DNAmAges and stratification variables.

conclusionsAAGrimAge and AAGrimAge2 outperformed AAHorvathAge, AAHannumAge and AAPhenoAge in predicting mortality risk, and the association pattern was positive.

Indexed as

AgingDNA MethylationEpigenesis, GeneticMortalityAgedAged, 80 and overCause of DeathFemaleHumansMaleMiddle AgedNutrition SurveysProportional Hazards ModelsRisk FactorsUnited StatesAll-cause mortalityBiological ageCause-specific mortalityDNA methylation age estimatorEpigenetic age acceleration

Identifiers

PMID40301953
PMCPMC12038942

What Socratic holds

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.