Multimorbidity burden and patterns associated with DeepBrainNet-derived brain-age gap in dementia-free older adults: A community-based study.

INTRODUCTION

Emerging evidence has linked chronic diseases with structural brain measures; however, the relationship between multimorbidity patterns and brain-age gap is unclear.

METHODS

This community-based study involved 1151 dementia-free older adults in Multimodal Interventions to Delay Dementia and Disability in Rural China (MIND-China). Multimorbidity was defined as coexistence of two or more chronic diseases. Hierarchical cluster analysis was used to identify five patterns of multimorbidity. We additionally defined cardiometabolic multimorbidity as coexistence of two or more cardiometabolic diseases. The predicted brain age was estimated using DeepBrainNet. Data were analyzed using linear regression models.

RESULTS

The number of chronic diseases, multimorbidity, and cardiometabolic multimorbidity were significantly associated with larger brain-age gap (p < 0.05). The multimorbidity clusters comprising cerebrovascular disease and metabolic disorders or biliary tract diseases, dorsopathies, anemia, and hearing problems were significantly correlated with larger brain-age gap (p < 0.05).

DISCUSSION: The overall burden and cardiometabolic pattern of multimorbidity are associated with advanced brain aging in dementia-free older adults.