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基于免疫相关基因和加权共表达网络分析鉴定缺血性脑卒中的分子亚型。

Identification of molecular subtypes of ischaemic stroke based on immune-related genes and weighted co-expression network analysis.

机构信息

Department of Pharmacy, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.

Department of Neurology, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.

出版信息

IET Syst Biol. 2023 Apr;17(2):58-69. doi: 10.1049/syb2.12059. Epub 2023 Feb 18.

DOI:10.1049/syb2.12059
PMID:36802116
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10116020/
Abstract

Immune system has been reported to play a key role in the development of ischaemic stroke (IS). Nevertheless, its exact immune-related mechanism has not yet been fully revealed. Gene expression data of IS and healthy control samples was downloaded from Gene Expression Omnibus database and differentially expressed genes (DEGs) was obtained. Immune-related genes (IRGs) data was downloaded from the ImmPort database. The molecular subtypes of IS were identified based on IRGs and weighted co-expression network analysis (WGCNA). 827 DEGs and 1142 IRGs were obtained in IS. Based on 1142 IRGs, 128 IS samples were clustered into two molecular subtypes: clusterA and clusterB. Based on the WGCNA, the authors found that the blue module had the highest correlation with IS. In the blue module, 90 genes were screened as candidate genes. The top 55 genes were selected as the central nodes according to gene degree in protein-protein interactions network of all genes in blue module. Through taking overlap, nine real hub genes were obtained that might distinguish between clusterA subtype and clusterB subtype of IS. The real hub genes (IL7R, ITK, SOD1, CD3D, LEF1, FBL, MAF, DNMT1, and SLAMF1) may be associated with molecular subtypes and immune regulation of IS.

摘要

免疫系统被报道在缺血性中风(IS)的发展中起着关键作用。然而,其确切的免疫相关机制尚未完全揭示。从基因表达综合数据库中下载 IS 和健康对照样本的基因表达数据,获得差异表达基因(DEGs)。从 ImmPort 数据库下载免疫相关基因(IRGs)数据。基于 IRGs 和加权共表达网络分析(WGCNA)确定 IS 的分子亚型。在 IS 中获得了 827 个 DEGs 和 1142 个 IRGs。基于 1142 个 IRGs,将 128 个 IS 样本聚类为两个分子亚型:clusterA 和 clusterB。基于 WGCNA,作者发现蓝色模块与 IS 相关性最高。在蓝色模块中,筛选出 90 个候选基因作为候选基因。根据蓝色模块中所有基因的蛋白质-蛋白质相互作用网络中的基因度,选择前 55 个基因作为中心节点。通过取重叠,得到了 9 个真实的 hub 基因,它们可能区分 IS 的 clusterA 亚型和 clusterB 亚型。这些真实的 hub 基因(IL7R、ITK、SOD1、CD3D、LEF1、FBL、MAF、DNMT1 和 SLAMF1)可能与 IS 的分子亚型和免疫调节有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1d/10116020/aa8b8ebe4e25/SYB2-17-58-g006.jpg
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