Ding Shuangfeng, Zhang Yunyun, Tang Yunzhe, Zhang Ying, Liu Mingyuan
Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Department of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, Shanghai, China.
Front Neurol. 2024 Nov 27;15:1437778. doi: 10.3389/fneur.2024.1437778. eCollection 2024.
Multiple Sclerosis (MS) is an autoimmune disorder characterized by demyelination occurring within the white matter of the central nervous system. While its pathogenesis is intricately linked with the body's immune response, the precise underlying mechanisms remain elusive. This study aims to explore potential immune-related genes associated with MS and assess the causal relationship between these genes and the risk of developing MS.
We retrieved expression datasets of peripheral blood mononuclear cells from MS patients from the Gene Expression Omnibus (GEO) database. Immune-related differentially expressed genes (IM-DEGs) were identified using the ImmPort database. GO and KEGG analyses were subsequently performed to elucidate the functions and pathways associated with the IM-DEGs. To visualize protein-protein interactions (PPIs), we used STRING, Cytoscape, and Cytohubba to construct networks of PPIs and hub genes. The diagnostic efficacy of hub genes was assessed using the nomogram model and ROC curve. The correlation of these hub genes was further validated in the mouse EAE model using quantitative PCR (qPCR). Finally, Mendelian randomization (MR) was performed to ascertain the causal impact of hub genes on MS.
Twenty-eight IM-DEGs were selected from the intersection of DEGs and immune genes. These genes are involved mainly in antigen receptor-mediated signaling pathways, B cell differentiation, B cell proliferation, and B cell receptor signaling pathways. Using Cytoscape software for analysis, the top 10 genes with the highest scores were identified as PTPRC, CD19, CXCL8, CD79A, IL7, CR2, CD22, BLNK, LCN2, and LTF. Five hub genes (PTPRC, CD19, CXCL8, CD79A, and IL7) are considered to have strong diagnostic potential. In the qPCR validation, the relative expression of these five genes showed significant differences between the control and EAE groups, indicating that these genes may play a potential role in the pathogenesis of MS. The MR results indicate that elevated levels of CD79A (OR = 1.106, 95% CI 1.002-1.222, = 0.046) are causally positively associated with the risk of developing MS.
This study integrated GEO data mining with MR to pinpoint pivotal immune genes linked to the onset of MS, thereby offering novel strategies for the treatment of MS.
多发性硬化症（MS）是一种自身免疫性疾病，其特征是中枢神经系统白质内发生脱髓鞘。虽然其发病机制与机体免疫反应密切相关，但确切的潜在机制仍不清楚。本研究旨在探索与MS相关的潜在免疫相关基因，并评估这些基因与MS发病风险之间的因果关系。
我们从基因表达综合数据库（GEO）中检索了MS患者外周血单个核细胞的表达数据集。使用ImmPort数据库鉴定免疫相关差异表达基因（IM-DEGs）。随后进行基因本体（GO）和京都基因与基因组百科全书（KEGG）分析，以阐明与IM-DEGs相关的功能和途径。为了可视化蛋白质-蛋白质相互作用（PPI），我们使用STRING、Cytoscape和Cytohubba构建PPI网络和枢纽基因网络。使用列线图模型和ROC曲线评估枢纽基因的诊断效能。使用定量PCR（qPCR）在小鼠实验性自身免疫性脑脊髓炎（EAE）模型中进一步验证这些枢纽基因之间的相关性。最后，进行孟德尔随机化（MR）分析以确定枢纽基因对MS的因果影响。
从差异表达基因（DEGs）与免疫基因的交集处选择了28个IM-DEGs。这些基因主要参与抗原受体介导的信号通路、B细胞分化、B细胞增殖和B细胞受体信号通路。使用Cytoscape软件进行分析，得分最高的前10个基因被确定为PTPRC、CD19、CXCL8、CD79A、IL7、CR2、CD22、BLNK、LCN2和LTF。五个枢纽基因（PTPRC、CD19、CXCL8、CD79A和IL7）被认为具有很强的诊断潜力。在qPCR验证中，这五个基因的相对表达在对照组和EAE组之间显示出显著差异，表明这些基因可能在MS发病机制中发挥潜在作用。MR结果表明，CD79A水平升高（比值比[OR]=1.106，95%置信区间[CI]1.002-1.222，P=0.046）与MS发病风险呈因果正相关。
本研究将GEO数据挖掘与MR相结合，以确定与MS发病相关的关键免疫基因，从而为MS的治疗提供新策略。
