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基于表达谱全基因组关联研究鉴定神经病理性疼痛的潜在机制和枢纽基因。

Identification of potential mechanism and hub genes for neuropathic pain by expression-based genome-wide association study.

机构信息

Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

出版信息

J Cell Biochem. 2019 Apr;120(4):4912-4923. doi: 10.1002/jcb.27766. Epub 2018 Sep 30.

Abstract

Neuropathic pain (NP) is a common pathological pain state with limited effective treatments. This study was designed to identify potential mechanisms and candidate genes using gene expression-based genome-wide association study (eGWAS). All NP-related microarray experiments were obtained from Gene Expression Omnibus and ArrayExpress. Significantly dysregulated genes were identified between experimental and untreated groups, and the number of microarray experiments in which each gene was dysregulated was calculated. Significantly dysregulated genes were ranked according to P values of the chi-square test. Using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes database, we performed functional and pathway enrichment analysis. Protein-protein interaction (PPI) network and module analysis was performed using Cytoscape software. A total of 115 candidate genes were identified from 19 independent microarray experiments by eGWAS based on the Bonferroni threshold ( P < 2.97 × 10 ). Immune and inflammatory responses, and complement and coagulation cascades, were respectively the most enriched biological process and pathways for candidate genes. The hub genes with highest connectivity in PPI network and two modules Ccl2 and Jun, and Ctss application of the eGWAS methodology can identify mechanisms and candidate genes associated with NP. Our results support the validity and prevalence of inflammatory and immune mechanisms across different NP models, and Ccl2, Jun, and Ctss may be the hub genes for NP.

摘要

神经病理性疼痛(NP)是一种常见的病理性疼痛状态,其有效治疗方法有限。本研究旨在通过基于基因表达的全基因组关联研究(eGWAS)来鉴定潜在的机制和候选基因。所有与 NP 相关的微阵列实验均从基因表达综合数据库和 ArrayExpress 中获得。在实验组和未治疗组之间鉴定出显著失调的基因,并计算每个基因失调的微阵列实验数量。根据卡方检验的 P 值对显著失调的基因进行排序。使用基因本体论和京都基因与基因组百科全书数据库,我们进行了功能和途径富集分析。使用 Cytoscape 软件进行蛋白质-蛋白质相互作用(PPI)网络和模块分析。通过 eGWAS 基于 Bonferroni 阈值(P < 2.97 × 10)从 19 个独立的微阵列实验中鉴定出 115 个候选基因。候选基因最富集的生物学过程和途径分别为免疫和炎症反应以及补体和凝血级联。PPI 网络中具有最高连通性的枢纽基因和两个模块 Ccl2 和 Jun,以及 Ctss 应用 eGWAS 方法可以鉴定与 NP 相关的机制和候选基因。我们的结果支持炎症和免疫机制在不同 NP 模型中的有效性和普遍性,并且 Ccl2、Jun 和 Ctss 可能是 NP 的枢纽基因。

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