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An epigenetic predictor of death captures multi-modal measures of brain health
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Abstract
Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed ‘DNAm GrimAge’ has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 ( n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10 −16 ). Higher DNAm GrimAge was associated with lower age 11 IQ ( β = −0.11), lower age 73 general cognitive ability ( β = −0.18), decreased brain volume ( β = −0.25) and increased brain white matter hyperintensities ( β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health- and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.
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“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 [70]
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Metadata
- Authors
- Hillary, R. F., Stevenson, A. J., Cox, S. R., McCartney, D. L., Harris, S. E., Seeboth, A., Higham, J., Sproul, D., Taylor, A. M., Redmond, P., Corley, J., Pattie, A., Hernández, M. D. C. V., Muñoz-Maniega, S., Bastin, M. E., Wardlaw, J. M., Horvath, S., Ritchie, C. W., Spires-Jones, T. L., McIntosh, A. M., Evans, K. L., Deary, I. J., & Marioni, R. E.
- Affiliations
- University of Edinburgh (GB)
- Edinburgh Cancer Research (GB)
- UK Dementia Research Institute (GB)
- University of California, Los Angeles (US)
- Institute of Genetics and Cancer (GB)
- Corresponding author
- Marioni, Riccardo E.
- ORCID
- Venue
- Molecular Psychiatry
- Published
- 2019-12-03
- Volume
- 26
- Issue
- 8
- Pages
- 3806-3816
- ISSN
- 1359-4184 (ISSN-L)
- 1476-5578
- PMC
- PMC8550950
- OpenAlex
- W2993770134
- Cited by
- 139
- References
- 70
- Citations by year
- 2026: 16 · 2025: 26 · 2024: 14 · 2023: 26 · 2022: 22 · 2021: 21 · 2020: 14
- FWCI
- 4.72
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Molecular Psychiatry (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- Alzheimer's Research UK (ARUK-PG2017B-10.)
- Wellcome Trust (108890/Z/15/Z)
- Fondation Leducq
- U.S. Department of Health & Human Services | National Institutes of Health (R01AG054628)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Keywords
- DNA methylation, epigenetic clocks, biological aging, mortality prediction, all-cause mortality, cognitive ability, child intelligence, brain volume, white matter hyperintensities, cognitive decline, Lothian Birth Cohort 1936, brain health
- MeSH terms
- Birth Cohort, Aged, Aging, Brain, Child, Humans, DNA Methylation, Epigenesis, Genetic, Epigenomics
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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