{"title":"类风湿关节炎的潜在CD8+ t细胞相关生物标志物IFIT3","authors":"Kangsong Tian, Jie Guo, Qian Yan, Ning Wang","doi":"10.1111/1756-185x.70385","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objective</h3>\n \n <p>The aim is to pinpoint crucial genes linked to CD8<sup>+</sup> T cells in rheumatoid arthritis (RA) for aiding in diagnosis, predicting disease progression, and ultimately discovering potential drug targets.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>This study utilized datasets from the Gene Expression Omnibus (GEO) database to analyze gene expression profiles in RA patients. Weighted Gene Coexpression Network Analysis (WGCNA) was conducted to identify gene modules associated with the diseases, followed by differential gene expression analysis. Functional enrichment and protein–protein interaction (PPI) network analysis were employed. Gene Set Enrichment Analysis (GSEA) and Disease Ontology (DO) analysis were applied to understand their potential pathways. Transcription factors (TFs) correlated with target gene expression were screened, and TF binding sites were predicted. The proportion of immune cell infiltration was calculated using CIBERSORT.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The study identified 58 candidate genes associated with CD8<sup>+</sup> T cells in RA. The top five genes, <i>RSAD2, IFIT3, OAS1, IFIT2</i>, and <i>SAMD9L</i>, were found to be upregulated in RA and other autoimmune diseases. <i>IFIT3</i> showed potential diagnostic value in RA, with significant expression differences in RA vs. OA samples. TF <i>BCL11B</i> bound to the <i>IFIT3</i> promoter. GSEA analysis indicated <i>IFIT3</i>'s influence on pathways like the cell cycle and TNF signaling. Immune landscape analysis showed <i>IFIT3</i>'s correlation with immune cell infiltration such as B cells and plasma cells. Drug prediction analysis suggested naringin's treatment potential for RA via targeting <i>IFIT3</i>.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>This study identifies key CD8<sup>+</sup> T-cell genes in RA, with <i>IFIT3</i> as a potential diagnostic and therapeutic target, revealing <i>BCL11B</i>'s regulatory role.</p>\n </section>\n </div>","PeriodicalId":14330,"journal":{"name":"International Journal of Rheumatic Diseases","volume":"28 8","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Potential CD8+ T-Cell-Related Biomarker IFIT3 for Rheumatoid Arthritis\",\"authors\":\"Kangsong Tian, Jie Guo, Qian Yan, Ning Wang\",\"doi\":\"10.1111/1756-185x.70385\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>The aim is to pinpoint crucial genes linked to CD8<sup>+</sup> T cells in rheumatoid arthritis (RA) for aiding in diagnosis, predicting disease progression, and ultimately discovering potential drug targets.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>This study utilized datasets from the Gene Expression Omnibus (GEO) database to analyze gene expression profiles in RA patients. Weighted Gene Coexpression Network Analysis (WGCNA) was conducted to identify gene modules associated with the diseases, followed by differential gene expression analysis. Functional enrichment and protein–protein interaction (PPI) network analysis were employed. Gene Set Enrichment Analysis (GSEA) and Disease Ontology (DO) analysis were applied to understand their potential pathways. Transcription factors (TFs) correlated with target gene expression were screened, and TF binding sites were predicted. The proportion of immune cell infiltration was calculated using CIBERSORT.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The study identified 58 candidate genes associated with CD8<sup>+</sup> T cells in RA. The top five genes, <i>RSAD2, IFIT3, OAS1, IFIT2</i>, and <i>SAMD9L</i>, were found to be upregulated in RA and other autoimmune diseases. <i>IFIT3</i> showed potential diagnostic value in RA, with significant expression differences in RA vs. OA samples. TF <i>BCL11B</i> bound to the <i>IFIT3</i> promoter. GSEA analysis indicated <i>IFIT3</i>'s influence on pathways like the cell cycle and TNF signaling. Immune landscape analysis showed <i>IFIT3</i>'s correlation with immune cell infiltration such as B cells and plasma cells. Drug prediction analysis suggested naringin's treatment potential for RA via targeting <i>IFIT3</i>.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>This study identifies key CD8<sup>+</sup> T-cell genes in RA, with <i>IFIT3</i> as a potential diagnostic and therapeutic target, revealing <i>BCL11B</i>'s regulatory role.</p>\\n </section>\\n </div>\",\"PeriodicalId\":14330,\"journal\":{\"name\":\"International Journal of Rheumatic Diseases\",\"volume\":\"28 8\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Rheumatic Diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1756-185x.70385\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RHEUMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Rheumatic Diseases","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1756-185x.70385","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RHEUMATOLOGY","Score":null,"Total":0}
A Potential CD8+ T-Cell-Related Biomarker IFIT3 for Rheumatoid Arthritis
Objective
The aim is to pinpoint crucial genes linked to CD8+ T cells in rheumatoid arthritis (RA) for aiding in diagnosis, predicting disease progression, and ultimately discovering potential drug targets.
Methods
This study utilized datasets from the Gene Expression Omnibus (GEO) database to analyze gene expression profiles in RA patients. Weighted Gene Coexpression Network Analysis (WGCNA) was conducted to identify gene modules associated with the diseases, followed by differential gene expression analysis. Functional enrichment and protein–protein interaction (PPI) network analysis were employed. Gene Set Enrichment Analysis (GSEA) and Disease Ontology (DO) analysis were applied to understand their potential pathways. Transcription factors (TFs) correlated with target gene expression were screened, and TF binding sites were predicted. The proportion of immune cell infiltration was calculated using CIBERSORT.
Results
The study identified 58 candidate genes associated with CD8+ T cells in RA. The top five genes, RSAD2, IFIT3, OAS1, IFIT2, and SAMD9L, were found to be upregulated in RA and other autoimmune diseases. IFIT3 showed potential diagnostic value in RA, with significant expression differences in RA vs. OA samples. TF BCL11B bound to the IFIT3 promoter. GSEA analysis indicated IFIT3's influence on pathways like the cell cycle and TNF signaling. Immune landscape analysis showed IFIT3's correlation with immune cell infiltration such as B cells and plasma cells. Drug prediction analysis suggested naringin's treatment potential for RA via targeting IFIT3.
Conclusion
This study identifies key CD8+ T-cell genes in RA, with IFIT3 as a potential diagnostic and therapeutic target, revealing BCL11B's regulatory role.
期刊介绍:
The International Journal of Rheumatic Diseases (formerly APLAR Journal of Rheumatology) is the official journal of the Asia Pacific League of Associations for Rheumatology. The Journal accepts original articles on clinical or experimental research pertinent to the rheumatic diseases, work on connective tissue diseases and other immune and allergic disorders. The acceptance criteria for all papers are the quality and originality of the research and its significance to our readership. Except where otherwise stated, manuscripts are peer reviewed by two anonymous reviewers and the Editor.