Background/Aim: Worldwide, osteoarthritis causes pain in many patients, reducing their quality of life. Unfortunately, there are limited ways to alleviate the pain of osteoarthritis patients. Today, advances in genetic analysis have made it possible to analyze various causes of disease, including osteoarthritis. However, genetic analysis of osteoarthritis patients in the Korean population has rarely been performed. This study aims to find specific gene expression patterns in synovium tissues of Korean osteoarthritis patients through transcriptome analysis. Materials and Methods: Transcriptome analysis was performed on eight tissue samples obtained from osteoarthritis patients and seven tissue samples obtained from normal individuals. To functionally analyze the differentially expressed genes (DEGs) identified from the transcriptome analysis, Gene Ontology (GO) term enrichment analysis, network analysis, and Gene Set Enrichment Analysis (GSEA) analysis were conducted. Results: After performing GO analysis on the top 50 DEGs, 11 candidate genes were selected based on adjusted p-value <0.05 and |log2 fold change (FC)| ≥2. Gene network analysis of the 11 DEGs confirmed their association with immune responses. Furthermore, GSEA analysis of the 11 DEGs revealed that all of them showed positive correlations with the corresponding GO terms. Conclusion: We identified 11 candidate genes associated with immune responses that are abnormally overexpressed in the synovium tissues of Korean osteoarthritis patients. Establishment of the strategies for targeting these genes may help alleviate pain in Korean osteoarthritis patients.
Gene Profiling Analyses of Synovium Tissues in Korean Osteoarthritis Patients
Jung-Jae Roh,Jaewan Jeon,Sunmi Jo,Geumju Park,Jihoon Kang,Sang-Won Moon,Wanyeon Kim
Published 2025 in In Vivo
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- Publication year
2025
- Venue
In Vivo
- Publication date
2025-10-29
- Fields of study
Biology, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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