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通过生物信息学方法分析扩张型心肌病中的基因表达谱。

Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods.

作者信息

Wang Liming, Zhu L, Luan R, Wang L, Fu J, Wang X, Sui L

机构信息

Emergency Department, The Second Affiliated Hospital of Xi'an, Jiaotong University, Xi'an, China.

Department of Emergency Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, China.

出版信息

Braz J Med Biol Res. 2016 Oct 10;49(10):e4897. doi: 10.1590/1414-431X20164897.

Abstract

Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.

摘要

扩张型心肌病(DCM)的特征是心室扩张,它是心力衰竭和心脏移植的常见原因。本研究旨在利用生物信息学方法探索潜在的DCM相关基因及其潜在调控机制。从基因表达综合数据库下载GSE3586的基因表达谱,包括15个正常样本和13个DCM样本。使用R语言中的Limma软件包鉴定正常样本和DCM样本之间的差异表达基因(DEG)。然后对DEG进行通路富集分析。同时,根据其结合序列预测这些DEG的潜在转录因子(TF)和微小RNA(miRNA)。此外,将DEG映射到cMap数据库以寻找潜在的小分子药物。通过比较DCM样本和对照样本之间的基因表达谱,共鉴定出4777个基因作为DEG。DEG在26条通路中显著富集,如淋巴细胞TarBase通路和雄激素受体信号通路。此外,鉴定出潜在的TF(SP1、LEF1和NFAT)以及潜在的miRNA(miR-9、miR-200家族和miR-30家族)。此外,发现异氟泼尼龙和苯海索等小分子是DCM的潜在治疗药物。鉴定出的DEG(PRSS12和FOXG1)、潜在的TF以及潜在的miRNA可能与DCM有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42de/5064772/03d558a5b3a2/1414-431X-bjmbr-1414-431X20164897-gf001.jpg

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