DNA methylation signatures in peripheral blood strongly predict all-cause mortality
Open accessAbstract
DNA methylation (DNAm) has been revealed to play a role in various diseases. Here we performed epigenome-wide screening and validation to identify mortality-related DNAm signatures in a general population-based cohort with up to 14 years follow-up. In the discovery panel in a case-cohort approach, 11,063 CpGs reach genome-wide significance (FDR<0.05). 58 CpGs, mapping to 38 well-known disease-related genes and 14 intergenic regions, are confirmed in a validation panel. A mortality risk score based on ten selected CpGs exhibits strong association with all-cause mortality, showing hazard ratios (95% CI) of 2.16 (1.10–4.24), 3.42 (1.81–6.46) and 7.36 (3.69–14.68), respectively, for participants with scores of 1, 2–5 and 5+ compared with a score of 0. These associations are confirmed in an independent cohort and are independent from the ‘epigenetic clock’. In conclusion, DNAm of multiple disease-related genes are strongly linked to mortality outcomes. The DNAm-based risk score might be informative for risk assessment and stratification.
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Individuals with positive age gaps, termed age acceleration, are at greater risk of mortality and some diseases of ageing such as heart disease, metabolic syndrome and certain cancers.
“These hypotheses have been supported by observations that individuals with positive age gaps, termed age acceleration, are at greater risk of mortality and some diseases of ageing such as heart disease, metabolic syndrome and certain cancers46–50.”
From Measuring biological age using omics data (2022) · cites this paper as [50]
The DNAm GrimAge clock shows consistently stronger associations with various measures of age-related dysfunction, including heart disease, frailty, and cognitive and physical decline, compared to other clocks.
“The DNAm GrimAge clock shows consistently stronger associations with various measures of age-related dysfunction, including heart disease, frailty, and cognitive and physical decline, compared to other clocks47,48,50,64–72.”
From Measuring biological age using omics data (2022) · cites this paper as [50]
By design, second-generation clocks specifically designed to associate with mortality risk have robust associations with mortality risk, and some show associations with heart disease risk, physical functioning and several blood chemistry markers of health.
“By design, all these clocks have robust associations with mortality risk, and some show associations with heart disease risk, physical functioning (balance, grip strength, walking speed) and several blood chemistry markers of health.”
From Measuring biological age using omics data (2022) · cites this paper as [50]
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- Authors
- Zhang, Y., Wilson, R., Heiss, J., Breitling, L. P., Saum, K.-U., Schöttker, B., Holleczek, B., Waldenberger, M., Peters, A., & Brenner, H.
- Affiliations
- German Cancer Research Center (DE)
- Helmholtz Munich (DE)
- Krebsregister Saarland (DE)
- Corresponding author
- Zhang, Yan
- ORCID
- Venue
- Nature Communications
- Published
- 2017-03-17
- Volume
- 8
- Issue
- 1
- Pages
- 14617-14617
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC5357865
- OpenAlex
- W2596440417
- Cited by
- 382
- References
- 65
- Citations by year
- 2026: 34 · 2025: 43 · 2024: 57 · 2023: 29 · 2022: 61 · 2021: 40 · 2020: 50 · 2019: 24 · 2018: 30 · 2017: 13
- FWCI
- 13.07
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Site cant be reached (submittedVersion, cc-by)
- Funders
- European Commission (2007–2013, FP7 2007-2013, FP7/2007, 603288)
- Bundesministerium für Bildung und Forschung (603288)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Birth, Development, and Health
- Keywords
- DNA methylation, all-cause mortality, mortality risk score, peripheral blood, epigenome-wide association study, CpG sites, disease-related genes, intergenic regions, mortality prediction, risk stratification, epigenetic clocks
- MeSH terms
- Aged, Cardiovascular Diseases, Cause of Death, Diabetes Mellitus, Female, Follow-Up Studies, Humans, Hypertension, Male, Middle Aged, Mortality, Neoplasms, Obesity, Smoking, Thinness, Cohort Studies, Proportional Hazards Models, CpG Islands, DNA Methylation, Epigenesis, Genetic, Overweight
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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