Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort
Open accessAbstract
BACKGROUND: Previous studies have developed models predicting methylation age from DNA methylation in blood and other tissues (epigenetic clock) and suggested the difference between DNA methylation and chronological ages as a marker of healthy aging. The goal of this study was to confirm and expand such observations by investigating whether different concepts of the epigenetic clocks in a population-based cohort are associated with cancer, cardiovascular, and all-cause mortality. RESULTS: DNA methylation age was estimated in a cohort of 1863 older people, and the difference between age predicted by DNA methylation and chronological age (Δage) was calculated. A case-cohort design and weighted proportional Cox hazard models were used to estimate associations of Δage with cancer, cardiovascular, and all-cause mortality. Hazard ratios for Δage (per 5 years) calculated using the epigenetic clock developed by Horvath were 1.23 (95 % CI 1.10-1.38) for all-cause mortality, 1.22 (95 % CI 1.03-1.45) for cancer mortality, and 1.19 (95 % CI 0.98-1.43) for cardiovascular mortality after adjustment for batch effects, age, sex, educational level, history of chronic diseases, hypertension, smoking status, body mass index, and leucocyte distribution. Associations were similar but weaker for Δage calculated using the epigenetic clock developed by Hannum. CONCLUSIONS: These results show that age acceleration in terms of the difference between age predicted by DNA methylation and chronological age is an independent predictor of all-cause and cause-specific mortality and may be useful as a general marker of healthy aging.
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The Horvath clock measures epigenetic dysregulation that is shared between ageing and many cancers.
“Moreover, across many cancers and in multiple cohorts, cancer tissues showed marked age acceleration on the Horvath clock44,57, suggesting it measures epigenetic dysregulation that is shared between ageing and many cancers.”
From Measuring biological age using omics data (2022) · cites this paper as [57]
Across many cancers and in multiple cohorts, cancer tissues showed marked age acceleration on the Horvath clock.
“Moreover, across many cancers and in multiple cohorts, cancer tissues showed marked age acceleration on the Horvath clock44,57, suggesting it measures epigenetic dysregulation that is shared between ageing and many cancers.”
From Measuring biological age using omics data (2022) · cites this paper as [57]
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- Authors
- Perna, L., Zhang, Y., Mons, U., Holleczek, B., Saum, K.-U., & Brenner, H.
- Affiliations
- German Cancer Research Center (DE)
- Krebsregister Saarland (DE)
- Corresponding author
- Perna, Laura
- Venue
- Clinical Epigenetics
- Published
- 2016-06-03
- Volume
- 8
- Issue
- 1
- Pages
- 64-64
- ISSN
- 1868-7075 (ISSN-L)
- 1868-7083
- PMC
- PMC4891876
- OpenAlex
- W2416801689
- Cited by
- 572
- References
- 22
- Citations by year
- 2026: 28 · 2025: 42 · 2024: 65 · 2023: 54 · 2022: 74 · 2021: 88 · 2020: 56 · 2019: 49 · 2018: 60 · 2017: 50 · 2016: 6
- FWCI
- 28.59
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Clinical Epigenetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Keywords
- epigenetic age acceleration, DNA methylation age, epigenetic clocks, Horvath clock, Hannum clock, all-cause mortality, cancer mortality, cardiovascular mortality, healthy aging, older adults, blood DNA methylation
- MeSH terms
- Aged, Aging, Blood, Cardiovascular Diseases, Cause of Death, Female, Humans, Leukocyte Count, Male, Middle Aged, Mortality, Neoplasms, Risk Factors, Cohort Studies, Proportional Hazards Models, Epigenesis, Genetic
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