Department of Rheumatology and Immunology, The Affiliated Hospital of Jiaxing University (The First Hospital of Jiaxing), Jiaxing, Zhejiang, China.
Jiaxing Key Laboratory of Osteoporosis and Bone Metabolism, The Affiliated Hospital of Jiaxing University (The First Hospital of Jiaxing), Jiaxing, Zhejiang, China.
Autoimmunity. 2024 Dec;57(1):2358069. doi: 10.1080/08916934.2024.2358069. Epub 2024 Jun 13.
Rheumatoid arthritis (RA) is the predominant manifestation of inflammatory arthritis, distinguished by an increasing burden of morbidity and mortality. The intricate interplay of genes and signalling pathways involved in synovial inflammation in patients with RA remains inadequately comprehended. This study aimed to ascertain the role of necroptosis in RA, as along with their associations with immune cell infiltration. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify central genes for RA. In this study, identified total of 28 differentially expressed genes (DEGs) were identified in RA. Utilising WGCNA, two co-expression modules were generated, with one module demonstrating the strongest correlation with RA. Through the integration of differential gene expression analysis, a total of 5 intersecting genes were discovered. These 5 hub genes, namely fused in sarcoma (FUS), transformer 2 beta homolog (TRA2B), eukaryotic translation elongation factor 2 (EEF2), cleavage and polyadenylation specific factor 6 (CPSF6) and signal transducer and activator of transcription 3 (STAT3) were found to possess significant diagnostic value as determined by receiver operating characteristic (ROC) curve analysis. The close association between the concentrations of various immune cells is anticipated to contribute to the diagnosis and treatment of RA. Furthermore, the infiltration of immune cells mentioned earlier is likely to exert a substantial influence on the initiation of this disease.
类风湿关节炎(RA)是炎症性关节炎的主要表现,其发病率和死亡率不断增加。RA 患者滑膜炎症相关的基因和信号通路的复杂相互作用仍未被充分理解。本研究旨在确定坏死性凋亡在 RA 中的作用,以及它们与免疫细胞浸润的关联。差异表达分析和加权基因共表达网络分析(WGCNA)用于鉴定 RA 的核心基因。在这项研究中,共鉴定出 28 个 RA 差异表达基因(DEGs)。利用 WGCNA,生成了两个共表达模块,其中一个模块与 RA 相关性最强。通过差异基因表达分析的整合,共发现了 5 个交集基因。这 5 个枢纽基因,即肉瘤融合(FUS)、转化 2β 同源物(TRA2B)、真核翻译延伸因子 2(EEF2)、切割和多聚腺苷酸化特异性因子 6(CPSF6)和信号转导和转录激活因子 3(STAT3),通过接收者操作特征(ROC)曲线分析发现它们具有显著的诊断价值。各种免疫细胞浓度之间的密切关联有望有助于 RA 的诊断和治疗。此外,前面提到的免疫细胞浸润可能对这种疾病的发生有很大的影响。