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已发表论文
通过生物信息学分析确定与非伤害背根神经节神经性疼痛相关的关键基因及其通路
Authors Chen CJ, Liu DZ, Yao WF, Gu Y, Huang F, Hei ZQ, Li X
Received 8 June 2017
Accepted for publication 11 October 2017
Published 14 November 2017 Volume 2017:10 Pages 2665—2674
DOI https://doi.org/10.2147/JPR.S143431
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Lucy Goodman
Peer reviewer comments 2
Editor who approved publication: Dr E. Alfonso Romero-Sandoval
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
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
