Evidence map›Paper›PMID 41992304›Full record

ArticleClinical epigenetics2026

Tracking DNA methylation-based biological age over 8 years and its association with mortality in community-dwelling older adults.

Qiming Yin, Ben Schöttker, Bernd Holleczek, Ziwen Fan, Joshua Stevenson-Hoare, Hermann Brenner

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Article in Clinical epigenetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Qiming YinDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Ben SchöttkerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Bernd HolleczekSaarland Cancer Registry, Neugeländstraße 9, 66119, Saarbrücken, Germany.
Ziwen FanDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Joshua Stevenson-HoareDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Hermann BrennerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany. h.brenner@dkfz.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation aging presents major health, social, economic, and political challenges. Aging is characterized by functional decline and increased disease risk. Recent advances in DNA methylation (DNAm) analysis have enabled more accurate estimates of biological age (BA), with accelerated epigenetic aging linked to unhealthy aging and higher mortality risk.

methodsWe estimated DNAm-based BA using two-wave longitudinal data from 894 participants aged 50–75 years at baseline in the German ESTHER cohort, with a mean follow-up duration of 8.1 years. Cross-sectional correlations between chronological age (CA) and BA estimates based on five established epigenetic clocks were assessed. Average BA trajectories were modeled using linear regression. Multivariable linear regression was applied to identify potential baseline determinants of BA, and Cox proportional hazards models and restricted cubic splines (RCS) analyses were used to evaluate associations between BA dynamics and all-cause mortality.

resultsBAs were correlated with baseline characteristics, including CA and sex. Longitudinally, BA increased at a slower rate than CA, and changes in BA were only weakly correlated with baseline CA. Smoking, physical activity, and alcohol consumption were identified as major determinants of individual BA trajectories. Furthermore, the rate of change in BA was significantly associated with all-cause mortality, with up to a 28% increased risk per standard deviation increase in BA slope.

conclusionsOur findings demonstrate strong correlations between BA and CA and highlight the influence of lifestyle factors on BA trajectories and mortality risk in older adults. We also emphasize the presence of sex-specific patterns in BA trajectories, underscoring the need for stratified approaches in aging research.

Indexed as

AgingDNA MethylationMortalityAgedAging in PlaceCross-Sectional StudiesEpigenesis, GeneticFemaleGermanyHumansIndependent LivingLongitudinal StudiesMaleMiddle AgedProportional Hazards ModelsAgingBiological ageEpigenetic clockLife-course perspectiveLongitudinal study

Identifiers

PMID41992304
PMCPMC13085702

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