Integrative analysis of Alzheimer's disease molecular networks with circadian regulators for prioritization of drug repurposing candidates

BackgroundAlzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by complex molecular mechanisms. Growing evidence indicates that circadian rhythm disruption contributes to disease progression and interacts with pathogenic pathways. Although multi-omics resources, compound perturbation profiles, and pharmacological bioactivity data are increasingly available, their integrative use for drug repurposing prioritization in AD, particularly with explicit consideration of circadian rhythm, remains limited.ObjectiveThis study aimed to prioritize drug repurposing candidates for AD, by integrating heterogeneous biological and pharmacological data.MethodsWe applied an integrative, systems-level computational analysis to prioritize drug repurposing and repositioning candidates for AD by combining network-based gene prioritization, functional transcriptomic similarity analysis, and target-level bioactivity prediction. Disease-associated molecular modules were identified within the human protein-protein interaction network, with circadian rhythm regulators incorporated as an additional disease relevant biological context. These modules were represented using functional gene embeddings to rank compound perturbation signatures. Candidate compounds were subsequently refined through ligand-based bioactivity prediction across AD associated targets to support polypharmacological prioritization.ResultsThe analysis prioritized compounds supported by convergent network-level disease relevance, transcriptomic similarity, and predicted target engagement. Several drugs previously investigated in dementia-related clinical trials were recovered. Novel repositioning candidates, including PF-562271, MGCD-265, and BMS-777607, were identified, converging on focal adhesion kinase (FAK), PI3K-AKT, and receptor tyrosine kinase (RTK) signaling pathways enriched in AD-associated genes and implicated in circadian regulation and neuroinflammation.ConclusionsThis integrative analysis identifies mechanistically coherent repurposing candidates, associated with circadian and inflammatory pathways, supporting systems-based strategies for therapeutic prioritization in complex neurodegenerative diseases.

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Publication Details

Journal
Journal of Alzheimer s Disease
Published
2026-10-13
DOI
https://doi.org/10.1177/13872877261497407
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Integrative analysis of Alzheimer's disease molecular networks with circadian regulators for prioritization of drug repurposing candidates

Chiara Pallara, Elisa Uliassi, Xinzhong Li, Alexandros Zantis
Journal of Alzheimer s Disease
Computational Drug Discovery Methods
article

Integrative analysis of Alzheimer's disease molecular networks with circadian regulators for prioritization of drug repurposing candidates

Chiara Pallara, Elisa Uliassi, Xinzhong Li, Alexandros Zantis
article en

Abstract

BackgroundAlzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by complex molecular mechanisms. Growing evidence indicates that circadian rhythm disruption contributes to disease progression and interacts with pathogenic pathways. Although multi-omics resources, compound perturbation profiles, and pharmacological bioactivity data are increasingly available, their integrative use for drug repurposing prioritization in AD, particularly with explicit consideration of circadian rhythm, remains limited.ObjectiveThis study aimed to prioritize drug repurposing candidates for AD, by integrating heterogeneous biological and pharmacological data.MethodsWe applied an integrative, systems-level computational analysis to prioritize drug repurposing and repositioning candidates for AD by combining network-based gene prioritization, functional transcriptomic similarity analysis, and target-level bioactivity prediction. Disease-associated molecular modules were identified within the human protein-protein interaction network, with circadian rhythm regulators incorporated as an additional disease relevant biological context. These modules were represented using functional gene embeddings to rank compound perturbation signatures. Candidate compounds were subsequently refined through ligand-based bioactivity prediction across AD associated targets to support polypharmacological prioritization.ResultsThe analysis prioritized compounds supported by convergent network-level disease relevance, transcriptomic similarity, and predicted target engagement. Several drugs previously investigated in dementia-related clinical trials were recovered. Novel repositioning candidates, including PF-562271, MGCD-265, and BMS-777607, were identified, converging on focal adhesion kinase (FAK), PI3K-AKT, and receptor tyrosine kinase (RTK) signaling pathways enriched in AD-associated genes and implicated in circadian regulation and neuroinflammation.ConclusionsThis integrative analysis identifies mechanistically coherent repurposing candidates, associated with circadian and inflammatory pathways, supporting systems-based strategies for therapeutic prioritization in complex neurodegenerative diseases.

Journal of Alzheimer s Disease
University of Bologna (IT)
UK Research and Innovation
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
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