Identification of key candidate genes in neuropathic pain by integrated bioinformatic analysis
Identification of key candidate genes in neuropathic pain by integrated bioinformatic analysis
复制标题
通过综合生物信息分析鉴定神经病理性疼痛的关键候选基因
DOI：
10.1002/jcb.29398
复制
发表时间：
2019-09-18
影响因子：
4
通讯作者：
Zhou, Jun
中科院分区：
文献类型：
--
作者：
Tang, Simin;Jing, Huan;Zhou, Jun
本研究旨在揭示保留神经损伤（spared nerve injury，SNI）模型中神经病理性疼痛（neuropathic pain，NP）背根神经节（dorsal root ganglia，DRGs）的差异表达基因（differentially expressed gene，DEGs），从而为NP的诊断和治疗寻找特异性和有意义的基因靶点。GSE 89224从GEO数据库下载。使用GEO 2 R在线工具筛选DEG。然后使用大卫进行DEG的功能富集分析，并使用R ggplot 2软件包构建。蛋白质相互作用（PPI）网络构建从STRING数据库和Cytoscape软件可视化。从TarBase和miRTarBase数据库获得靶向这些DEG的microRNA，而从ENCODE数据库预测靶向转录因子（TF）的DEG，两者都利用可视化分析平台NetworkAnayst。最后，基于上述两个网络构建了一个合并的microRNA-TF网络，并使用Cytoscape进行分析。共筛选出80个DEG基因，只有Vstm 2b和Htr 3a基因表达下调，78个基因表达上调。应用实时聚合酶链反应验证SNI手术后5天DRG组织中前5个DEG（Npy、Atf 3、Gpr 151、Sprr 1a和Cckbr）的基因表达。结果发现，Npy，Atf 3和Sprr 1a在SNI刺激后有显著增加，而Gpr 151和Cckbr呈轻微上升趋势。对所有DEG进行了功能分析，其中58个生物过程通过基因本体分析富集，11个信号通路通过KEGG分析富集。在PPI网络中，Atf 3、Jun、Timp和Npy具有较高的度。因此，结合各种生物信息学分析，Npy和Atf 3可能作为NP的预后和治疗靶点。通过microRNA-TF调控网络分析，预测关键microRNA（mmu-mir-16- 5 p）和TF（MEF 2A）与NP的发病过程相关，也被认为是NP发病过程中的关键调控因子。
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.