ArticleClinical rheumatology2026
Gender inequality in osteoarthritis: a bioinformatics perspective.
Article in Clinical rheumatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesOsteoarthritis (OA) is more common and severe in females than in males. This study aimed to identify key genes and pathways underlying this gender disparity.
methodsThree microarray datasets (GSE12021, GSE55457, and GSE55584) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the R package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Protein-protein interaction (PPI) networks were constructed and analyzed in Cytoscape, and hub genes were identified using nine topological methods in CytoHubba. Selected hub genes were further validated by RT-qPCR.
resultsWe identified 90 and 375 DEGs in female and male OA patients compared to controls. Among them, 24 genes (9 downregulated and 15 upregulated) were identified in both genders. The PPI network analysis identified 9 hub genes in females and 5 hub genes in males. RT-qPCR validated the expression levels of CTGF, CX3CR1, TGBR2, and KDR in female OA patients and those of ISG15, STAT1, MYC, and IL6 in male OA patients. Additionally, the expression level of JUN was validated in both genders. A total of 90 DEGs were identified in female OA patients and 375 in male patients, compared to controls. Twenty-four genes (15 upregulated, 9 downregulated) were common to both genders. PPI analysis revealed nine hub genes in females and five in males. RT-qPCR confirmed the expression of CTGF, CX3CR1, TGBR2, and KDR in female OA patients, and ISG15, STAT1, MYC, and IL6 in male OA patients. JUN expression was validated in both genders.
conclusionThe identified genes and pathways may contribute to the higher incidence and severity of OA in females. These findings provide potential gender-specific diagnostic markers and therapeutic targets for OA. Key Points • This study identified gender-specific differentially expressed genes (DEGs) in osteoarthritis using integrated analysis of three GEO datasets. • Distinct hub genes were discovered in male and female OA patients through PPI network analysis and CytoHubba algorithms. • RT-qPCR validated key genes including CTGF, CX3CR1, and IL6, revealing gender-specific gene expression profiles in OA. • Findings provide insights into potential gender-specific diagnostic biomarkers and therapeutic targets for osteoarthritis.
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