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利用共表达网络分析挖掘呼吸机相关性肺损伤的关键基因。

Mining the key genes for ventilator-induced lung injury using co-expression network analysis.

机构信息

Department of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai, P.R. China.

Department of Endocrinology, Affiliated Nanhua Hospital, University of South China, Hengyang, P.R. China.

出版信息

Biosci Rep. 2021 Mar 26;41(3). doi: 10.1042/BSR20203235.

DOI:10.1042/BSR20203235
PMID:33687057
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7969703/
Abstract

Mechanical ventilation is extensively adopted in general anesthesia and respiratory failure management, but it can also induce ventilator-induced lung injury (VILI). Therefore, it is of great urgency to explore the mechanisms involved in the VILI pathogenesis, which might contribute to its future prevention and treatment. Four microarray datasets from the GEO database were selected in our investigation, and were subjected to the Weighted Gene Co-Expression Network Analysis (WGCNA) to identify the VILI-correlated gene modules. The limma package in R software was used to identify the differentially expressed genes (DEGs) between the VILI and control groups. WGCNA was constructed by merging the GSE9314, GSE9368, GSE11434 and GSE11662 datasets. A total of 49 co-expression network modules were determined as associated with VILI. The intersected genes between hub genes screened from DEGs for VILI and those identified using WGCNA were as follows: Tlr2, Hmox1, Serpine1, Mmp9, Il6, Il1b, Ptgs2, Fos and Atf3, which were determined to be key genes for VILI. Those key genes were validated by GSE86229 and quantitative PCR (qPCR) experiment to have significantly statistical difference in their expression between the VILI and control groups. In a nutshell, nine key genes with expression differences in VILI were screened by WGCNA by integrating multiple datasets.

摘要

机械通气在全身麻醉和呼吸衰竭管理中广泛应用,但也会引起呼吸机相关性肺损伤(VILI)。因此,探索 VILI 发病机制中涉及的机制具有重要的紧迫性,这可能有助于其未来的预防和治疗。我们的研究中选择了 GEO 数据库中的四个微阵列数据集,并对其进行加权基因共表达网络分析(WGCNA),以鉴定与 VILI 相关的基因模块。R 软件中的 limma 包用于鉴定 VILI 组和对照组之间的差异表达基因(DEGs)。通过合并 GSE9314、GSE9368、GSE11434 和 GSE11662 数据集构建了 WGCNA。共确定了 49 个与 VILI 相关的共表达网络模块。从 VILI 的 DEGs 中筛选出的枢纽基因与 WGCNA 中鉴定出的基因之间的交集基因如下:Tlr2、Hmox1、Serpine1、Mmp9、Il6、Il1b、Ptgs2、Fos 和 Atf3,这些基因被确定为 VILI 的关键基因。这些关键基因通过 GSE86229 和定量 PCR(qPCR)实验验证,在 VILI 组和对照组之间的表达差异具有统计学意义。总之,通过整合多个数据集,WGCNA 筛选出了 9 个 VILI 中表达差异的关键基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d45/7969703/24d45e6aaa00/bsr-41-bsr20203235-g7.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d45/7969703/24d45e6aaa00/bsr-41-bsr20203235-g7.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d45/7969703/4a9b232d2692/bsr-41-bsr20203235-g2.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d45/7969703/acdb68e7921d/bsr-41-bsr20203235-g5.jpg
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