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Updated: Jul 3, 2026

Abbiategrasso Brain Bank Protocol for Collecting, Processing and Characterizing Aging Brains
Published on: June 3, 2020
Multimorbidity burden and patterns associated with DeepBrainNet-derived brain-age gap in dementia-free older adults:
Xinyu Liu1, Ming Mao2,3, Cuicui Liu2
1Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China.
Chronic diseases and multimorbidity are linked to an accelerated brain-age gap in older adults. Specific patterns, including cardiometabolic conditions, significantly contribute to advanced brain aging.
Area of Science:
- Neuroscience
- Gerontology
- Public Health
Background:
- Chronic diseases are increasingly linked to structural brain changes.
- The association between multimorbidity patterns and brain-age gap remains under-explored.
Purpose of the Study:
- To investigate the relationship between multimorbidity patterns and brain-age gap in older adults.
- To identify specific multimorbidity patterns associated with accelerated brain aging.
Main Methods:
- Community-based study of 1151 dementia-free older adults (MIND-China).
- Hierarchical cluster analysis identified five multimorbidity patterns.
- Brain age predicted using DeepBrainNet; linear regression analyzed associations.
Main Results:
- Higher chronic disease count, multimorbidity, and cardiometabolic multimorbidity correlated with larger brain-age gap (p < 0.05).
- Multimorbidity clusters involving cerebrovascular/metabolic diseases, dorsopathies, anemia, and hearing issues showed significant brain-age gap increases (p < 0.05).
Conclusions:
- The overall burden of chronic diseases and specific cardiometabolic multimorbidity patterns are associated with advanced brain aging.
- Findings highlight the impact of multimorbidity on brain health in aging populations.
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