Projects per year
Abstract
Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.
Original language | English |
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Pages (from-to) | 1385-1392 |
Number of pages | 8 |
Journal | Molecular Psychiatry |
Volume | 23 |
Early online date | 25 Apr 2017 |
DOIs | |
Publication status | Published - 31 May 2018 |
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Dive into the research topics of 'Brain age predicts mortality'. Together they form a unique fingerprint.Projects
- 8 Finished
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Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III
Wardlaw, J., Bastin, M. & Deary, I.
1/05/15 → 30/04/19
Project: Research
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RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.
Deary, I., Gale, C., Holmes, M., Logie, P., Maclullich, A., Porteous, D., Seckl, J., Starr, J., Wardlaw, J. & Okely, J.
1/09/13 → 31/08/19
Project: Research
Profiles
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Maria Valdes Hernandez
- Deanery of Clinical Sciences - Lecturer in Medical Image Analysis
- Centre for Clinical Brain Sciences
- Edinburgh Neuroscience
- Edinburgh Imaging
- Small Vessel Disease Research
Person: Academic: Research Active , Academic: Research Active (Research Assistant)