Integrated bioinformatics and network pharmacology to identify and validate macrophage polarization related hub genes in the treatment of osteoarthritis with Astragalus membranaceus.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40442788", "kind": "science-record", "revision": 3, "content_hash": "sha256:346d88e259d6663c84b37f82762367a12fa8cc604c071108049a8597ea019df6", "created_at": "2026-11-01T20:30:34Z", "updated_at": "2026-11-01T22:14:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated bioinformatics and network pharmacology to identify and validate macrophage polarization related hub genes in the treatment of osteoarthritis with Astragalus membranaceus.", "doi": "10.1186/s13018-025-05799-9", "pmid": "40442788", "authors": ["Hui Zang", "Liuyan Wang", "Yang Wu", "Junfei Chang", "Wanjun Liu"], "journal": "Journal of orthopaedic surgery and research", "year": 2025, "abstract": "BACKGROUND: Macrophage polarization exacerbates the pathological processes of osteoarthritis (OA). Astragalus membranaceus (AM) can repair chondrocytes and serve as a protective agent for OA. Therefore, the study intended to identify macrophage polarization-related genes (MPRGs) in the treatment of OA with AM.\nMETHODS: We utilized data from GSE57218 as training set, while GSE117999 serves as a validation set, all obtained from Gene Expression Omnibus(GEO). The MPRGs were exported from the Molecular Signatures Database. Target genes of AM were obtained by network pharmacology. Differentially expressed genes (DEGs) were identified in OA vs. control groups. Then key module genes were acquired through weighted gene co-expression network analysis (WGCNA) and intersected with DEGs and target genes of AM to obtain candidate genes. Subsequently, the candidate genes were further screened for hub genes by machine learning, receiver operating characteristic (ROC) curve analysis, and expression validation. Further, reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) was applied to verify the mRNA expression levels of hub genes. In addition, the mechanism of these hub genes was investigated through enrichment analysis, immune microenvironment analysis, regulatory network construction, and molecular docking.\nRESULTS: Ultimately, 1,430 DEGs, 4,577 key module genes, and 486 target genes of AM were intersected to derive 28 candidate genes. After machine learning, ROC curve analysis and expression validation, CREBBP and PIM3 were identified. The mRNA expression of tissue CREBBP and PIM3 was significantly decreased in OA compared with the control group. Furthermore, the enrichment analysis indicated that eight pathways, including oxidative phosphorylation, were simultaneously enriched by two hub genes. Microenvironment analysis revealed negative correlations between both hub genes and 11 differential immune cells. We identified that CREBBP and PIM3 were regulated by 6 miRNAs (e.g., hsa-mir-942-5p) and 79 transcription factors (TFs) (e.g., IRF1). Molecular docking experiments indicated that isoflavone strongly bound to CREBBP, while (3R)-3-(2-hydroxy-3,4-dimethoxyphenyl) chroman-7-ol exhibited significant binding affinity for PIM3, suggesting that these two active ingredients were core components of AM in treating OA via hub genes.\nCONCLUSION: This study identified CREBBP and PIM3 as potential focal points for the treatment of OA with AM, providing valuable clues to help treat and predict OA.\nCLINICAL TRIAL NUMBER: Not applicable.", "claims": [{"id": "claim-method", "statement": "Differences in OA vs. control groups were analyzed using the Wilcoxon test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40442788", "locator": "sections[14] \"Statistical analysis\" paragraph 2", "quote": "Differences in OA vs. control groups were analyzed using the Wilcoxon test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "No datasets were generated or analysed during the current study.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40442788", "locator": "sections[29] \"Data availability\" paragraph 2", "quote": "No datasets were generated or analysed during the current study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Ultimately, 1,430 DEGs, 4,577 key module genes, and 486 target genes of AM were intersected to derive 28 candidate genes. After machine learning, ROC curve analysis and expression validation, CREBBP and PIM3 were identified.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40442788", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Ultimately, 1,430 DEGs, 4,577 key module genes, and 486 target genes of AM were intersected to derive 28 candidate genes. After machine learning, ROC curve analysis and expression validation, CREBBP and PIM3 were identified."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Ultimately, 1,430 DEGs, 4,577 key module genes, and 486 target genes of AM were intersected to derive 28 candidate genes. After machine learning, ROC curve analysis and expression validation, CREBBP and PIM3 were identified.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40442788"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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