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ORIGINAL RESEARCH article

Front. Bioinform.

Sec. Genomic Analysis

This article is part of the Research TopicDecoding Genomes: Bioinformatics Pipelines for Functional InsightsView all 4 articles

Identification and functional analysis of hub genes in knee osteoarthritis via bioinformatics and experimental validation

Provisionally accepted
Shanyong  JiangShanyong Jiang1Jingjing  CaoJingjing Cao1Jianshu  LuJianshu Lu1Jianxiao  LiangJianxiao Liang1Lianxin  LiLianxin Li2Yanqiang  SongYanqiang Song1Jincheng  GaoJincheng Gao1Baoen  JiangBaoen Jiang1*
  • 1Dongying District People's Hospital of Dongying City, Dongying, China
  • 2Shandong Provincial Hospital, Jinan, China

The final, formatted version of the article will be published soon.

Objective Knee osteoarthritis (KOA) is a prevalent chronic degenerative joint disease that causes chronic pain and mobility restrictions in the elderly, significantly impacting quality of life. Current treatments focus on symptom relief, lacking effective interventions targeting the underlying mechanisms. Understanding KOA's molecular mechanisms and identifying key pathogenic genes are essential for developing targeted therapies. Methods Gene expression data from KOA patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to reveal the associated biological processes and signaling pathways. Protein-protein interaction (PPI) network analysis and Gene Ontology-based semantic similarity calculations were used to identify hub genes. Gene Set Variation Analysis (GSVA) assessed enrichment in KOA-related pathways. Immune infiltration analysis (CIBERSORT) assessed the immune cell distribution in KOA tissues. Finally, hub gene expression changes were validated using the IL-1β-treated CHON-001 cell model and real-time quantitative PCR (RT-qPCR). Results A total of 3,290 upregulated and 2,536 downregulated DEGs were identified. GO and KEGG enrichment analyses revealed these genes were primarily involved in extracellular matrix remodeling, transmembrane transport, and inflammation-related pathways. Key hub genes, including HSPA5, FOXO1, and YWHAE, were identified. GSVA showed that these genes were significantly enriched in multiple KOA-associated signaling pathways. Immune infiltration analysis revealed significant differences in the levels of six immune cell types in KOA tissues, which were associated with the hub genes expression. In CHON-001 cell, the expression levels of GRB2, IKBKG, and HSPA12A were upregulated, whereas YWHAE, HSPB1, and DCAF8 were downregulated, consistent with the tissue samples. Conclusion This study identified key pathogenic genes and their regulatory pathways in KOA, highlighting their potential role in disease progression via inflammation and immune modulation. These findings provide insights for developing targeted therapeutic strategies for KOA.

Keywords: knee osteoarthritis, bioinformatics, Differentially expressed genes, Immuneinfiltration, GSVA

Received: 23 Jul 2025; Accepted: 24 Nov 2025.

Copyright: © 2025 Jiang, Cao, Lu, Liang, Li, Song, Gao and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Baoen Jiang, tfovbwzc@hotmail.com

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