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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
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