Identification of key genes and pathways associated with neuropathic pain in uninjured dorsal root ganglion by using bioinformatic analysis

Abstract

Purpose

Neuropathic 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 methods

The 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.

Results

A 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.

Conclusion

This 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.

Keywords:

• spinal nerve ligation
• neuropathic pain
• uninjured afferent
• bioinformatic analysis
• microarray

Acknowledgments

This Project was supported by the National Natural Science Foundation of China (number 81701104) and the Natural Science Foundation of Guangdong Province, China (number 2016A030310157).

Disclosure

The authors report no conflicts of interest in this work.