A Quantitative Analysis of Multimodal Biomarkers in Alzheimer's Disease

• URL: http://arxiv.org/abs/2606.17867v1
• Date: Tue, 16 Jun 2026 12:40:15 GMT
• Title: A Quantitative Analysis of Multimodal Biomarkers in Alzheimer's Disease
• Abstract summary: We present a quantitative analysis of multimodal AD biomarkers by integrating tau-PET, structural MRI, cognitive scores, and APOE4 data.<n>This study provides a systematic characterization of cross-modal relationships, improving the interpretability and selection of biomarkers in Alzheimer's Disease.
• Score: 0.0468771281852187
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Despite increasing adoption of multimodal approaches in Alzheimer's Disease (AD) research -- aimed at integrating molecular, structural, clinical, and genetic biomarkers to enhance disease characterization -- the relationships among these modalities remain poorly understood. A systematic analysis of their dynamic interaction is essential for improving disease modeling, identifying redundant assessments, and reducing patient burden and acquisition costs. In this paper, we present a quantitative analysis of multimodal AD biomarkers by integrating tau-PET, structural MRI, cognitive scores (MMSE and CDR), and APOE4 data from 789 subjects drawn from the ADNI dataset. In our analyses, we (A) quantify cross-modal mutual information and explained variance to assess redundancy and predictive dependencies; (B) examine associations between tau topologies and structural atrophy across brain regions to select informative ROIs; (C) perform a statistical decomposition of the tau-cognition association into atrophy-related and atrophy-independent components; (D) and identify a dominant neurodegenerative trajectory that aligns with cognitive decline. This study provides a systematic characterization of cross-modal relationships, improving the interpretability and selection of biomarkers in AD. Code is publicly available at: https://github.com/antonioscardace/Multimodal-AD.

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