PurposeNeuropathic pain is a complex chronic condition occurring post-nervous system damage. The transcriptional reprogramming of injured dorsal root ganglia (DRGs) drives neuropathic pain. However, few comparative analyses using high-throughput platforms have investigated uninjured DRG in neuropathic pain, and potential interactions among differentially expressed genes (DEGs) and pathways were not taken into consideration. The aim of this study was to identify changes in genes and pathways associated with neuropathic pain in uninjured L4 DRG after L5 spinal nerve ligation (SNL) by using bioinformatic analysis.Materials and methodsThe microarray profile GSE24982 was downloaded from the Gene Expression Omnibus database to identify DEGs between DRGs in SNL and sham rats. The prioritization for these DEGs was performed using the Toppgene database followed by gene ontology and pathway enrichment analyses. The relationships among DEGs from the protein interactive perspective were analyzed using protein–protein interaction (PPI) network and module analysis. Real-time polymerase chain reaction (PCR) and Western blotting were used to confirm the expression of DEGs in the rodent neuropathic pain model.ResultsA total of 206 DEGs that might play a role in neuropathic pain were identified in L4 DRG, of which 75 were upregulated and 131 were downregulated. The upregulated DEGs were enriched in biological processes related to transcription regulation and molecular functions such as DNA binding, cell cycle, and the FoxO signaling pathway. Ctnnb1 protein had the highest connectivity degrees in the PPI network. The in vivo studies also validated that mRNA and protein levels of Ctnnb1 were upregulated in both L4 and L5 DRGs.ConclusionThis study provides insight into the functional gene sets and pathways associated with neuropathic pain in L4 uninjured DRG after L5 SNL, which might promote our understanding of the molecular mechanisms underlying the development of neuropathic pain.
Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus (DM). The pathogenic mechanisms of DPN and the therapeutic interventions required may be distinct between type 1 (T1) and type 2 (T2) DM. However, the molecular mechanisms underlying the pathogenesis of DPN in both types of diabetes remain unclear. The aim of the current study was to identify the changes in genes and pathways associated with DPN in sciatic nerves of T1- and T2DM mice using bioinformatics analysis. The microarray profiles of sciatic nerves of T1DM (GSE11343) and T2DM (GSE27382) mouse models were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in each. DEGs in the two types of DM (with fold change ≥2 and P<0.05) were identified with BRB-ArrayTools. Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins and visualized using Cytoscape. Compared with control samples, 623 and 1,890 DEGs were identified in sciatic nerves of T1- and T2DM mice, respectively. Of these, 75 genes were coordinately dysregulated in the sciatic nerves of both models. Many DEGs unique to T1DM mice were localized to the nucleoplasm and were associated with regulation of transcription processes, while many unique to T2DM mice were localized at cell junctions and were associated with ion transport. In addition, certain DEGs may be associated with the different treatment strategies used for the two types of DM. This analysis provides insight into the functional gene sets and pathways operating in sciatic nerves in T1- and T2DM. The results should improve understanding of the molecular mechanisms underlying the pathophysiology of DPN, and provide information for the development of therapeutic strategies for DPN specific to each type of DM.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.