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

ATF3 小桶 基因 计算生物学 生物 生物信息学 基因表达 基因本体论 遗传学 发起人
作者
Simin Tang,Huan Jing,Zhenxing Huang,Teng Huang,Lin Shi,Mengyang Liao,Jun Zhou
出处
期刊:Journal of Cellular Biochemistry [Wiley]
卷期号:121 (2): 1635-1648 被引量:52
标识
DOI:10.1002/jcb.29398
摘要

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.
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