Bioinformatics and Gene Expression Omnibus Analysis of Key Candidate Genes and Pathways Associated with Femoral Head Necrosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39830663", "kind": "science-record", "revision": 3, "content_hash": "sha256:0a0fe1b0711c368900371680a84216bf5aae12b9ab420a32ba8d9c19409f080e", "created_at": "2026-11-01T20:30:07Z", "updated_at": "2026-11-01T22:13:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics and Gene Expression Omnibus Analysis of Key Candidate Genes and Pathways Associated with Femoral Head Necrosis.", "doi": "10.5812/ijpr-145223", "pmid": "39830663", "authors": ["Yuanjing Ding", "Yuxia Ma", "Heng Yan", "Enshui Zhang"], "journal": "Iranian journal of pharmaceutical research : IJPR", "year": 2024, "abstract": "Background: Femoral head necrosis (FHN) is a debilitating bone disease affecting an estimated 8 million people worldwide. Although specific drugs for FHN have limitations, targeted therapies have shown promising results. The significance of this study is underscored by the high prevalence of FHN, the limitations of current treatments, and the potential of targeted drugs and natural compounds for effective therapeutic interventions.\nObjectives: This study aimed to explore the genetic landscape and associated pathways of FHN through bioinformatics analysis of Gene Expression Omnibus (GEO) data and molecular docking simulations targeting specific enzymes implicated in FHN.\nMethods: Differentially expressed genes (DEGs) in FHN samples were identified from GEO datasets, specifically accession number GSE123568 (Platform: GPL15207). Functional enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to identify enriched pathways and Gene Ontology (GO) terms. Additionally, a protein-protein interaction (PPI) network was constructed using the STITCH (search tool for interaction of chemicals) database, which helped identify top hub genes and proteins. Molecular docking was conducted against key proteins using compounds from the topical chinese herbal medicine (TCHM) database associated with FHN.\nResults: The study provided a comprehensive bioinformatics analysis of key candidate genes and pathways associated with FHN, which may serve as potential therapeutic targets. It was found that FHN is associated with mitogen-activated protein kinases (MAP4K4/ MAPK8/ MAPK9) and interleukins (IL1b/ IL19/ IL26). Molecular docking results showed strong interactions of traditional Chinese herbal compounds through hydrogen bonding and electrostatic interactions at the active sites of the top ten target proteins associated with FHN.\nConclusions: The study confirmed that FHN is linked with enzymes such as mitogen-activated protein kinases (MAPKs), interleukins, tumor necrosis factors (TNFs), and VEGFA (vascular endothelial growth factor A). Molecular docking simulations demonstrated that hesperidin, naringin, and curcumin exhibit potent inhibition against key proteins involved in FHN. Future research will focus on elucidating the specific roles of genes associated with FHN and exploring potential therapeutic targets using natural compounds.", "claims": [{"id": "claim-data-access", "statement": "The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39830663", "locator": "sections[25] \"Data Availability:\" paragraph 2", "quote": "The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In this study, a total of 795 elements from 40 human samples within GSE123568 (Platform: GPL15207) were analyzed. Out of these, 195 unique elements were identified as differentially expressed in association with FHN.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39830663", "locator": "sections[12] \"4.1. Identification of Microarray Data\" paragraph 2", "quote": "In this study, a total of 795 elements from 40 human samples within GSE123568 (Platform: GPL15207) were analyzed. Out of these, 195 unique elements were identified as differentially expressed in association with FHN."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In this study, a total of 795 elements from 40 human samples within GSE123568 (Platform: GPL15207) were analyzed. 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