Abstract
Experimental autoimmune encephalomyelitis (EAE) is a mouse model that can be used to investigate aetiology, pathogenesis, and treatment approaches for multiple sclerosis (MS). A novel integrated bioinformatics approach was used to understand the involvement of differentially expressed genes (DEGs) in the spleen of EAE mice through data mining of existing microarray and RNA-seq datasets. We screened differentially expressed mRNAs using mRNA expression profile data of EAE spleens taken from Gene Expression Omnibus (GEO). Functional and pathway enrichment analyses of DEGs were performed by Database for Annotation, Visualization, and Integrated Discovery (DAVID). Subsequently, the DEGs-encoded protein-protein interaction (PPI) network was constructed. The 784 DEGs in GSE99300 A.SW PP-EAE mice spleen mRNA profiles, 859 DEGs in GSE151701 EAE mice spleen mRNA profiles, and 646 DEGs in GSE99300 SJL/J PP-EAE mice spleen mRNA profiles were explored. Functional enrichment of 55 common DEGs among 3 sub-datasets revealed several immune-related terms, such as neutrophil extravasation, leucocyte migration, antimicrobial humoral immune response mediated by an antimicrobial peptide, toll-like receptor 4 bindings, IL-17 signalling pathway, and TGF-beta signalling pathway. In the screening of 10 hub genes, including MPO, ELANE, CTSG, LTF, LCN2, SELP, CAMP, S100A9, ITGA2B, and PRTN3, and in choosing and validating the 5 DEGs, including ANK1, MBOAT2, SLC25A21, SLC43A1, and SOX6, the results showed that SLC43A1 and SOX6 were significantly decreased in EAE mice spleen. Thus this study offers a list of genes expressed in the spleen that might play a key role in the pathogenesis of EAE.