Literature DB >> 31535407

Identification of key candidate genes in neuropathic pain by integrated bioinformatic analysis.

Simin Tang1,2, Huan Jing1,3, Zhenxing Huang1, Teng Huang1, Sen Lin1, Meijuan Liao1, Jun Zhou4.   

Abstract

This study aimed to disclose differentially expressed genes (DEGs) in dorsal root ganglia (DRGs) of neuropathic pain (NP) from spared nerve injury (SNI) model, thereby identifying specific and meaningful genetic targets for the diagnosis and treatment of NP. The GSE89224 was downloaded from the GEO database. DEGs were screened using the GEO2R online tool. Functional enrichment analysis of DEGs was then performed using the DAVID and constructed using the R ggplot2 package. Protein-protein interaction (PPI) network was constructed from the STRING database and visualized in Cytoscape software. MicroRNA targeting these DEGs was obtained from the TarBase and miRTarBase database, while transcription factor (TF)-targeting DEGs were predicted from the ENCODE database, both of which utilized the visual analytics platform NetworkAnayst. Finally, a merged microRNA-TF network was constructed based on the above two networks and was then analyzed with Cytoscape. Eighty DEGs were screened, only Vstm2b and Htr3a were downregulated and 78 genes were upregulated. The real-time polymerase chain reaction was applied to validate the gene expression of the top five DEGs (Npy, Atf3, Gpr151, Sprr1a, and Cckbr) in the DRG tissue 5 days after SNI surgery. It was found that Npy, Atf3, and Sprr1a have a significant increase after SNI stimulation, while Gpr151 and Cckbr showed a slight upward trend. Functional analysis was performed on all DEGs, of which 58 biological processes were enriched by gene ontology analysis, and 11 signaling pathways were enriched by KEGG analysis. In the PPI network, Atf3, Jun, Timp, and Npy had a higher degree. Thus, combined with various bioinformatic analyses, Npy and Atf3 may serve as the prognostic and therapeutic targets of NP. Key microRNA (mmu-mir-16-5p) and TF (MEF2A) were predicted to be associated with the pathogenetic process of NP with microRNA-TF regulatory network analysis, which were also identified as key regulators in the progression of NP.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  bioinformatic analysis; dorsal root ganlion; neuropathic pain

Mesh:

Substances:

Year:  2019        PMID: 31535407     DOI: 10.1002/jcb.29398

Source DB:  PubMed          Journal:  J Cell Biochem        ISSN: 0730-2312            Impact factor:   4.429


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