Abstract
Neuroimaging-based brain age gap (BAG) is presumably a mediator linking modifiable risk factors to cognitive changes, but this has not been verified yet. To address this hypothesis, modality-specific brain age models were constructed and applied to a population-based cohort (N = 326) to estimate their BAG. Structural equation modeling was employed to investigate the mediation effect of BAG between modifiable risk factors (assessed by 2 cardiovascular risk scores) and cognitive functioning (examined by 4 cognitive assessments). The association between higher burden of modifiable risk factors and poorer cognitive functioning can be significantly mediated by a larger BAG (multimodal: p = 0.014, 40.8% mediation proportion; white matter-based: p = 0.023, 15.7% mediation proportion), which indicated an older brain. Subgroup analysis further revealed a steeper slope (p = 0.019) of association between cognitive functioning and multimodal BAG in the group of higher modifiable risks. The results confirm that BAG can serve as a mediating indicator linking risk loadings to cognitive functioning, implicating its potential in the management of cognitive aging and dementia.
| Original language | English |
|---|---|
| Pages (from-to) | 61-72 |
| Number of pages | 12 |
| Journal | Neurobiology of Aging |
| Volume | 114 |
| DOIs | |
| Publication status | Published - Jun 2022 |
Keywords
- Brain age gap
- Cognitive aging
- Machine learning
- Mediation
- Modifiable risk factor
- Neuroimaging
ASJC Scopus subject areas
- General Neuroscience
- Ageing
- Clinical Neurology
- Developmental Biology
- Geriatrics and Gerontology
Fingerprint
Dive into the research topics of 'Validation of neuroimaging-based brain age gap as a mediator between modifiable risk factors and cognition'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS