ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2026
Mapping cross-domain drivers of Alzheimer's disease risk through integrated network analysis.
Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Mapping cross-domain drivers of Alzheimer's disease risk through integrated network analysis.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
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11 authors.
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Abstract
introductionAlzheimer's disease (AD) is a complex neurodegenerative disorder with numerous known risk factors. Identification of which genetic factors are causal drivers is difficult due to the long disease prodrome in an inaccessible organ. The application of integrative, systems-level approaches are crucial for addressing this complexity.
methodsSixteen biological domain specific interaction networks were derived from the top AD risk-enriched proteins within each domain. Weighted key driver analysis (wKDA) identified influential hub nodes within each network.
resultsDistinct processes and drivers were identified within each domain's network. Domains including structural stabilization, endolysosome, and lipid metabolism were especially influential. Integrating key drivers across domains identified consistent drivers such as CTNNB1, ACSL1, and ALDH3A2, suggesting fundamental roles contributing to AD risk. DISCUSSION: This highly integrative network-based approach identified context-dependent drivers and enabled the inference of interactions between domains. The identified drivers suggest potential targets for future therapeutic development.
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