ArticleImmunity, inflammation and disease2025
Identification and Exploration of Immunity-Related Genes and Natural Products for Alzheimer's Disease Based on Bioinformatics, Molecular Docking, and Molecular Dynamics.
Article in Immunity, inflammation and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Exploring Mechanistic Targets ofInternational journal of molecular sciences · 2026Article
- Biomarkers and therapeutic strategies targeting microglia in neurodegenerative diseases: current status and future directions.Molecular neurodegeneration · 2025Review
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8 authors.
Funding
Abstract
backgroundRecent research highlights the immune system's role in AD pathogenesis and promising prospects of natural compounds in treatment. This study explores immunity-related biomarkers and potential natural products using bioinformatics, machine learning, molecular docking, and kinetic simulation.
methodsDifferentially expressed genes (DEGs) in AD were analyzed using GSE5281 and GSE132903 datasets. Important AD module genes were identified using a weighted co-expression algorithm (WGCNA), and immune-related genes (IRGs) were obtained from the ImmPortPortal database. Intersecting these genes yielded important IRGs. Then, the least absolute shrinkage and selection operator (LASSO) and other methods screened common immune-related AD markers. Biological pathways were explored through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). The accuracy of these markers was assessed by subject operator signature (ROC) curves and validated in the GSE122063 dataset. The datasets was then subjected to immunoinfiltration analysis. Multiple compound databases were used to analyze core Chinese medicines and components. Molecular docking and kinetic simulation verification were used for further verification.
resultsA total of 1360 differential genes and 5 biomarkers (PGF, GFAP, GPI, SST, NFKBIA) were identified, showing excellent diagnostic efficiency. GSEA revealed markers associated with Oxidative phosphorylation, Nicotine addiction, and Hippo signaling pathway. Immune infiltration analysis showed dysregulation in multiple immune cell types in AD brains, with significant interactions between markers and 5 immune cell types. A total of 27 possible herbs and 7 core compounds were eventually identified. The binding environment of GPI-luteolin and GPI-stigasterol was relatively stable and showed good affinity.
conclusionsPGF, GFAP, SST, GPI, and NFKBIA were identified for early AD diagnosis, associated with immune cells and pathways in AD brains. 7 promising natural compounds, including luteolin and stigmasterol, were screened for targeting these biomarkers.
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