Repurposing Existing Drugs For Dual Treatment of Alzheimer'S Disease and Type 2 Diabetes Mellitus: A Network Pharmacology Approach

Background: Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) represent two of the most prevalent and burdensome chronic conditions of aging, sharing overlapping pathophysiological mechanisms including insulin resistance, neuroinflammation, oxidative stress, and dysregulated PI3K–Akt–GSK-3β signaling. Repurposing approved antidiabetic agents to simultaneously target both conditions offers a cost-effective and mechanistically justified therapeutic strategy. Objective: To apply a systematic network pharmacology framework to identify shared molecular targets between AD and T2DM, screen approved antidiabetic drugs against these targets, and evaluate the mechanistic basis and clinical evidence for lead candidate compounds. Methods: Disease target genes for AD and T2DM were retrieved from GeneCards, DisGeNET, and OMIM databases. Drug targets of approved antidiabetic agents were obtained from DrugBank and ChEMBL. Shared targets were identified via Venn diagram analysis. A protein-protein interaction (PPI) network was constructed using STRING v12.0 and visualized in Cytoscape v3.10. Hub genes were identified by CytoHubba. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler R package. Candidate drugs were ranked using a multi-criteria scoring system incorporating hub gene targeting, pathway coverage, blood-brain barrier (BBB) penetration, neuroprotective evidence, and safety profile. Results: A total of 312 shared target genes were identified between AD (1,055 targets) and T2DM (1,203 targets). PPI network analysis revealed ten hub genes: AKT1, TP53, TNF, IL-6, MAPK3, GSK-3β, INSR, EGFR, CASP3, and APP. KEGG enrichment analysis highlighted the PI3K–Akt, MAPK, insulin resistance, TNF, and AGE–RAGE signaling pathways as the most significantly enriched shared pathways (p-adjusted < 0.001). Multi-criteria scoring ranked metformin (score 9.10/10) as the top candidate, followed by liraglutide (8.37/10) and empagliflozin (7.31/10). These findings are convergent with emerging clinical evidence: network pharmacology analysis demonstrated that metformin exerts the strongest comparative impact on shared AD–T2DM pathways among 39 antidiabetic agents, while the ELAD Phase 2b trial reported an 18% reduction in cognitive decline and approximately 50% less brain volume loss with liraglutide versus placebo. Conclusion: This network pharmacology analysis provides a mechanistic rationale for repurposing metformin, liraglutide, and empagliflozin as dual-indication agents for AD and T2DM. The shared PI3K–Akt–GSK-3β, neuroinflammatory, and metabolic pathways represent actionable therapeutic nodes. Prospective randomized controlled trials with integrated metabolic and cognitive endpoints are warranted.

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