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Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods

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 profi...

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Autores principales: Wang, Liming, Zhu, L., Luan, R., Wang, L., Fu, J., Wang, X., Sui, L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Associação Brasileira de Divulgação Científica 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5064772/
https://www.ncbi.nlm.nih.gov/pubmed/27737314
http://dx.doi.org/10.1590/1414-431X20164897
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author Wang, Liming
Zhu, L.
Luan, R.
Wang, L.
Fu, J.
Wang, X.
Sui, L.
author_facet Wang, Liming
Zhu, L.
Luan, R.
Wang, L.
Fu, J.
Wang, X.
Sui, L.
author_sort Wang, Liming
collection PubMed
description 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.
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spelling pubmed-50647722016-10-19 Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods Wang, Liming Zhu, L. Luan, R. Wang, L. Fu, J. Wang, X. Sui, L. Braz J Med Biol Res Clinical Investigation 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. Associação Brasileira de Divulgação Científica 2016-10-10 /pmc/articles/PMC5064772/ /pubmed/27737314 http://dx.doi.org/10.1590/1414-431X20164897 Text en http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License
spellingShingle Clinical Investigation
Wang, Liming
Zhu, L.
Luan, R.
Wang, L.
Fu, J.
Wang, X.
Sui, L.
Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
title Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
title_full Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
title_fullStr Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
title_full_unstemmed Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
title_short Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
title_sort analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods
topic Clinical Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5064772/
https://www.ncbi.nlm.nih.gov/pubmed/27737314
http://dx.doi.org/10.1590/1414-431X20164897
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