journal articles
SPATIAL AMYLOID–INFORMED MULTIMODAL BRAIN AGE AS AN EARLY MARKER OF ALZHEIMER’S-RELATED VULNERABILITY AND RISK STRATIFICATION
Liang Cui, Qing-Min Wang, Zhen Zhang, Min Wang, You-Yi Tu, Jie-Hui Jiang, Yi-Hui Guan, Yue-Hua Li, Fang Xie, Qi-Hao Guo
BACKGROUND: Brain age gap (BAG)—the difference between predicted and chronological age—captures neurobiological aging, but MRI-only models insufficiently reflect Alzheimer’s disease (AD) pathology. Whether incorporating regional amyloid-β (Aβ) positron emission tomography (PET) improves sensitivity to early AD processes remains unknown.
OBJECTIVES: To develop an amyloid-informed multimodal BAG model and examine its associations with cognition, plasma biomarkers, and functional connectivity across the AD continuum.
DESIGN: Cross-sectional analysis using integrated machine-learning models.
SETTING: Chinese Preclinical Alzheimer’s Disease Study (CPAS), a cohort recruited from community settings and memory clinics.
PARTICIPANTS: Nine hundred ninety community-dwelling adults spanning normal cognition, subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia.
MEASUREMENTS: Regional Aβ-PET and structural MRI informed BAG estimation. Cognitive tests, plasma biomarkers (p-tau217, p-tau181, neurofilament light [NfL], glial fibrillary acidic protein [GFAP], Aβ42/40), and hippocampus–default mode network (DMN) connectivity from resting-state fMRI were assessed.
RESULTS: Higher BAG was associated with greater odds of SCD, MCI, or dementia across the cohort, with stronger effects in Aβ-positive individuals. BAG explained more cognitive variance than global Aβ burden and was linked to multidomain cognitive deficits. Elevated BAG corresponded to higher p-tau217, p-tau181, NfL, and GFAP and lower Aβ42/40, indicating early biomarker alterations. BAG was also associated with reduced hippocampus–DMN connectivity.
CONCLUSIONS: An amyloid-informed multimodal BAG model captures convergent AD-related pathology, biomarker alterations, and cognitive vulnerability beyond amyloid burden alone, supporting its value for individualized risk s2tratification and prevention-focused assessment.
CITATION:
Liang Cui ; Qing-Min Wang ; Zhen Zhang ; Min Wang ; You-Yi Tu ; Jie-Hui Jiang ; Yi-Hui Guan ; Yue-Hua Li ; Fang Xie ; Qi-Hao Guo (2025): Spatial amyloid–informed multimodal brain age as an early marker of Alzheimer’s-related vulnerability and risk stratification. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2026.100501