Identification of potential mechanism and hub genes for neuropathic pain by expression-based genome-wide association study
Identification of potential mechanism and hub genes for neuropathic pain by expression-based genome-wide association study
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通过基于表达的全基因组关联研究鉴定神经性疼痛的潜在机制和中枢基因
DOI：
10.1002/jcb.27766
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发表时间：
2019-04-01
影响因子：
4
通讯作者：
Li, Xiang
中科院分区：
文献类型：
--
作者：
Gu, Yu;Qiu, Zhuolin;Li, Xiang
神经病理性疼痛（neuropathic pain，NP）是一种常见的病理性疼痛状态，治疗效果有限。本研究旨在通过基于基因表达的全基因组关联研究（eGWAS）来确定潜在的机制和候选基因。所有NP相关的微阵列实验均来自Gene ExpressionOmnibus和ArrayExpress。在实验组和未处理组之间鉴定出明显失调的基因，并计算每个基因失调的微阵列实验的数量。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和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。基于Bonferroni阈值（P < 2.97 x 10（-6）），通过eGWAS从19个独立的微阵列实验中总共鉴定出115个候选基因。免疫和炎症反应以及补体和凝血级联反应分别是候选基因最丰富的生物学过程和途径。PPI网络中具有最高连接性的枢纽基因和两个模块Ccl 2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。我们的研究结果支持不同NP模型中炎症和免疫机制的有效性和普遍性，并且Ccl 2，Jun和Ctss可能是NP的枢纽基因。
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 x 10(-6)). 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.