Combining gene expression microarrays and Mendelian randomization: exploring key immune-related genes in multiple sclerosis.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.