Effect of surgical damage to spinal nerve on dorsal-root ganglion gene expressions: Comprehensive analysis of differentially expressed genes

Abstract

BackgroundNeuropathic pain can cause significant physical and economic burden, and there are no effective long-term treatments. We conducted a bioinformatics analysis to identify mechanisms to determine strategies for more effective treatments of neuropathic pain. MethodGSE24982 and GSE63442 microarray datasets were extracted from the Gene Expression Omnibus database to analyze transcriptome differences of neuropathic pain in the dorsal root ganglions (DRGs). We filtered the differentially expressed genes (DEGs) in the two datasets and conducted Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the shared DEGs. The Protein–Protein Interaction network was used to determine the hub genes, which were verified in the GSE30691 dataset. miRDB and miRWalk Databases were used to predict potential miRNA of the selected DEGs. We made the spinal nerve ligation (SNL) rat model and qPCR was used to verify the differential expression of hub genes. ResultsA total of 182 overlapped DEGs were found between GSE24982 and GSE63442 datasets. The GO and KEGG analysis showed that the selected DEGs were enriched in infection, transmembrane transport of ion channels, and synaptic transmission. We identified seven hub genes (Atf3, Aif1, Ctss, Gfap, Scg2, Jun, and Vgf). qPCR verified the expression differences of the hub genes in the DRGs after SNL model. Predicted miRNA targeting each selected hub genes were identified. ConclusionsSeven hub genes related to the pathogenesis of neuropathic pain and potential targeting miRNA were identified, expanding understanding of the mechanism of neuropathic pain and facilitating treatment development.