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与支气管肺发育不良相关的关键生物标志物的加权基因共表达网络分析

Weighted Gene Co-expression Network Analysis of Key Biomarkers Associated With Bronchopulmonary Dysplasia.

作者信息

Cai Yao, Ma Fei, Qu LiuHong, Liu Binqing, Xiong Hui, Ma Yanmei, Li Sitao, Hao Hu

机构信息

Department of Neonatology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

Department of Neonatology, The Maternal and Child Health Care Hospital of Huadu, Guangzhou, China.

出版信息

Front Genet. 2020 Sep 9;11:539292. doi: 10.3389/fgene.2020.539292. eCollection 2020.

Abstract

Bronchopulmonary dysplasia (BPD) is a complex disorder resulting from interactions between genes and the environment. The accurate molecular etiology of BPD remains largely unclear. This study aimed to identify key BPD-associated genes and pathways functionally enriched using weighted gene co-expression network analysis (WGCNA). We analyzed microarray data of 62 pre-term patients with BPD and 38 pre-term patients without BPD from Gene Expression Omnibus (GEO). WGCNA was used to construct a gene expression network, and genes were classified into definite modules. In addition, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of BPD-related hub genes were performed. Firstly, we constructed a weighted gene co-expression network, and genes were divided into 10 modules. Among the modules, the yellow module was related to BPD progression and severity and included the following hub genes: , , , , , and ; and the red module included some co-expression molecules that displayed a continuous decline in expression with BPD progression and included the following hub genes: , , , , , , , and . GO and KEGG analyses showed that high expression of inflammatory response-related genes and low expression of T cell receptor activation-related genes are significantly correlated with BPD progression. The present WGCNA-based study thus provides an overall perspective of BPD and lays the foundation for identifying potential pathways and hub genes that contribute to the development of BPD.

摘要

支气管肺发育不良(BPD)是一种由基因与环境相互作用导致的复杂疾病。BPD准确的分子病因在很大程度上仍不清楚。本研究旨在使用加权基因共表达网络分析(WGCNA)来鉴定功能富集的关键BPD相关基因和通路。我们分析了来自基因表达综合数据库(GEO)的62例患有BPD的早产儿和38例未患BPD的早产儿的微阵列数据。使用WGCNA构建基因表达网络,并将基因分类到特定模块中。此外,还对BPD相关的枢纽基因进行了基因本体(GO)和京都基因与基因组百科全书(KEGG)分析。首先,我们构建了一个加权基因共表达网络,基因被分为10个模块。在这些模块中,黄色模块与BPD的进展和严重程度相关,包含以下枢纽基因:[此处原文缺失具体基因名称];红色模块包含一些随着BPD进展表达持续下降的共表达分子,包含以下枢纽基因:[此处原文缺失具体基因名称]。GO和KEGG分析表明,炎症反应相关基因的高表达和T细胞受体激活相关基因的低表达与BPD进展显著相关。因此,本基于WGCNA的研究提供了BPD的整体视角,并为鉴定有助于BPD发展的潜在通路和枢纽基因奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6da/7509191/43446f11d321/fgene-11-539292-g001.jpg

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