Gene expression in multiple sclerosis during pregnancy based on integrated bioinformatics analysis

Background The modulation of the activity disease in patients with Multiple Sclerosis (MS) that occurs during pregnancy is a helpful model which could provide insight into central disease mechanisms and facilitate treatment. Therefore, the aim of the study was to identify differentially expressed genes in-silico to perform biological function pathway enrichment analysis and protein-protein interaction from pregnant women with MS. Methods Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. We selected the microarray dataset GSE17449. The gene expression dataset contains the data of mononuclear cells from four different groups sought, including seven healthy women (H), four healthy pregnant women (HP), eight women with multiple sclerosis (WMS), and nine women nine months pregnant with multiple sclerosis (PMS). The GSEA software was employed for enrichment analysis, and the REACTOME database was used for biological pathways. The protein-protein interaction (PPI) network was plotted with STRING. The databases used to identify the connection of DEGs with different signaling pathways were KEGG and WIKIPATHWAYS. Results We identified 42 differentially expressed genes in pregnant women with MS. The significant pathways included IL-10 signaling pathway, ErbB2 activates, the hemoglobin complex (HBD, HBB, HBA1, AHSP, and HBA2), IL-17 signaling pathway (LCN2 and MMP9), antigen processing and presentation, and Th17 cell differentiation (HLA-DQA1), Rap1 signaling pathway (ID1), NOD-Like receptor signaling pathway (CAMP and DEFA4), PD-L1 Signaling, Interferon gamma signaling (MMP9 and ARG1), Neutrophil degranulation (CAMP, DEFA4, ELANE, CEACAM8, S100P, CHI3L1, AZU1, OLFM4, CRISP3, LTF, ARG1, PGLYRP1, and TCN1). In the WIKIPATHWAYS set, significance was found Vitamin B12 metabolism (TCN1, HBB, and HBA2), and IL-18 signaling pathway (S100P). Conclusion This study can be used to understand several essential target genes and pathways identified in the present study, which may serve as feasible targets for MS therapies.