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缺血性心肌病中基因和通路的生物信息学分析与鉴定

Bioinformatics Analysis and Identification of Genes and Pathways in Ischemic Cardiomyopathy.

作者信息

Cao Jing, Liu Zhaoya, Liu Jie, Li Chan, Zhang Guogang, Shi Ruizheng

机构信息

Department of Cardiovascular Medicine, Third Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.

Department of Geriatrics, Third Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.

出版信息

Int J Gen Med. 2021 Sep 21;14:5927-5937. doi: 10.2147/IJGM.S329980. eCollection 2021.

Abstract

PURPOSE

Ischemic cardiomyopathy (ICM) is considered to be the most common cause of heart failure, with high prevalence and mortality. This study aimed to investigate the different expressed genes (DEGs) and pathways in the pathogenesis of ICM using bioinformatics analysis.

METHODS

The control and ICM datasets GSE116250, GSE46224 and GSE5406 were collected from the gene expression omnibus (GEO) database. DEGs were identified using limma package of R software, and co-expressed genes were identified using Venn diagrams. Then, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to explore the biological functions and signaling pathways. Protein-protein interaction (PPI) networks were assembled with Cytoscape software to identify hub genes related to the pathogenesis of ICM. RT-PCR of Heart tissues (n=2 for non-failing controls and n=4 for ischemic cardiomyopathy patients) was used to validate the bioinformatic results.

RESULTS

A total of 844 DEGs were screened from GSE116250, of which 447 were up-regulated genes and 397 were down-regulated genes, respectively. A total of 99 DEGs were singled out from GSE46224, of which 58 were up-regulated genes and 41 were down-regulated genes, respectively. Thirty DEGs were screened from GSE5406, including 10 genes with up-regulated expression and 20 genes with down-regulated expression. Five up-regulated and 3 down-regulated co-expressed DEGs were intersected in three datasets. GO and KEGG pathway analyses revealed that DEGs are mainly enriched in collagen fibril organization, protein digestion and absorption, AGE-RAGE signaling pathway and other related pathways. Collagen alpha-1(III) chain (COL3A1), collagen alpha-2(I) chain (COL1A2) and lumican (LUM) are the three hub genes in all three datasets through PPI network analysis. The expression of 5 DEGs (SERPINA3, FCN3, COL3A1, HBB, MXRA5) in heart tissues by qRT-PCR results was consistent with our GEO analysis, while expression of 3 DEGs (ASPN, LUM, COL1A2) was opposite with GEO analysis.

CONCLUSION

These findings from this bioinformatics network analysis investigated key hub genes, which contributed to better understanding the mechanism and new therapeutic targets of ICM.

摘要

目的

缺血性心肌病(ICM)被认为是心力衰竭最常见的病因,具有高患病率和死亡率。本研究旨在通过生物信息学分析探讨ICM发病机制中的差异表达基因(DEGs)和信号通路。

方法

从基因表达综合数据库(GEO)收集对照和ICM数据集GSE116250、GSE46224和GSE5406。使用R软件的limma包鉴定DEGs,并使用维恩图鉴定共表达基因。然后,进行基因本体(GO)和京都基因与基因组百科全书(KEGG)通路富集分析,以探索生物学功能和信号通路。使用Cytoscape软件构建蛋白质-蛋白质相互作用(PPI)网络,以鉴定与ICM发病机制相关的枢纽基因。对心脏组织(非衰竭对照组n = 2,缺血性心肌病患者n = 4)进行RT-PCR以验证生物信息学结果。

结果

从GSE116250中筛选出总共844个DEGs,其中分别有447个上调基因和397个下调基因。从GSE46224中选出总共99个DEGs,其中分别有58个上调基因和41个下调基因。从GSE5406中筛选出30个DEGs,包括10个表达上调的基因和20个表达下调的基因。在三个数据集中交集出5个上调和3个下调的共表达DEGs。GO和KEGG通路分析显示,DEGs主要富集在胶原纤维组织、蛋白质消化和吸收、AGE-RAGE信号通路及其他相关通路。通过PPI网络分析,胶原α-1(III)链(COL3A1)、胶原α-2(I)链(COL1A2)和纤连蛋白(LUM)是所有三个数据集中的三个枢纽基因。qRT-PCR结果显示心脏组织中5个DEGs(SERPINA3, FCN3, COL3A1, HBB, MXRA5)的表达与我们的GEO分析一致,而3个DEGs(ASPN, LUM, COL1A2)的表达与GEO分析相反。

结论

该生物信息学网络分析的这些发现研究了关键枢纽基因,有助于更好地理解ICM的机制和新的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9a7/8464396/5b67d513843d/IJGM-14-5927-g0001.jpg

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