Spatial amyloid–informed multimodal brain age as an early marker of Alzheimer’s-related vulnerability and risk stratification - 06/02/26
, Fang Xie c, ⁎ , Qi-Hao Guo a, ⁎
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Highlights |
• | A amyloid-informed multimodal brain age model detects early brain vulnerability. |
• | BAG was associated with cognitive decline risk across preclinical and prodromal stages. |
• | Higher BAG related to plasma p-tau, NfL, GFAP, and hippocampal–DMN connectivity alterations. |
• | BAG offers a noninvasive marker for early risk stratification in the Alzheimer’s continuum. |
Abstract |
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.
Le texte complet de cet article est disponible en PDF.Keywords : Alzheimer’s disease, Brain age gap, Amyloid-beta, Cognitive decline, Plasma biomarkers, Functional connectivity
Plan
Vol 13 - N° 4
Article 100501- avril 2026 Retour au numéro
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