Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling

Abstract Background Identify genes probably associated with chronic heart failure and predict potential target genes for dilated cardiomyopathy using bioinformatics analyses. Methods Gene expression profiles (series number GSE3585 and GSE42955) of cardiomyopathy patients and healthy controls were do...

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Main Authors: Jianquan Zhao, Tiewei Lv, Junjun Quan, Weian Zhao, Jing Song, Zhuolin Li, Han Lei, Wei Huang, Longke Ran
Format: Article
Language:English
Published: BMC 2018-08-01
Series:Journal of Biomedical Science
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12929-018-0459-8
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spelling doaj-35d52c34c70649b4aabf23ea0a39700c2020-11-24T21:55:31ZengBMCJournal of Biomedical Science1423-01272018-08-0125111010.1186/s12929-018-0459-8Identification of target genes in cardiomyopathy with fibrosis and cardiac remodelingJianquan Zhao0Tiewei Lv1Junjun Quan2Weian Zhao3Jing Song4Zhuolin Li5Han Lei6Wei Huang7Longke Ran8Department of Cardiology, Bayannaoer City HospitalDepartment of Cardiology, Children’s hospital, Chongqing Medical UniversityDepartment of Cardiology, Children’s hospital, Chongqing Medical UniversityDepartment of Cardiology, Children’s hospital, Chongqing Medical UniversityDepartment of Bioinformatics, Chongqing Medical UniversityDepartment of Vascular Cardiology, the First Affiliated Hospital of Chongqing, Medical UniversityDepartment of Vascular Cardiology, the First Affiliated Hospital of Chongqing, Medical UniversityDepartment of Vascular Cardiology, the First Affiliated Hospital of Chongqing, Medical UniversityDepartment of Bioinformatics, Chongqing Medical UniversityAbstract Background Identify genes probably associated with chronic heart failure and predict potential target genes for dilated cardiomyopathy using bioinformatics analyses. Methods Gene expression profiles (series number GSE3585 and GSE42955) of cardiomyopathy patients and healthy controls were downloaded from the Expression Omnibus Gene (GEO) database. Differential expression of genes (DEGS) between the two groups of total 14 cardiomyopathy patients and 10 healthy controls were subsequently identified by limma package of R. Database for Annotation, Visualization, and Integrated Discovery (DAVID Tool), which is an analysis of enriched biological processes. Search Tool for the Retrieval Interacting Genes (STRING) was used as well for the analysis of protein-protein interaction network (PPI). Prediction of the potential drugs was suggested based on the preliminarily identified genes using Connectivity Map (CMap). Results Eighty-nine DEGs were identified (57 up-regulated and 32 down-regulated). The most enrichment Gene Ontology (GO) terms (P < 0.05) contain genes involved in extracellular matrix (ECM) and biological adhesion signal pathways (P < 0.05, ES > 1.5) such as ECM-receptors, focal adhesion and transforming growth factor beta (TGF-β), etc. Fifty-one differentially expressed genes were found to encode interacting proteins. Eleven key genes along with related transcription factors were identified including CTGF, POSTN, CORIN, FIGF, etc. Conclusion Bioinformatics-based analyses reveal the targeted genes probably associated with cardiomyopathy, which provide clues for pharmacological therapies aiming at the targets.http://link.springer.com/article/10.1186/s12929-018-0459-8Dilated cardiomyopathyBioinformaticsMicroarrayHeart failure
collection DOAJ
language English
format Article
sources DOAJ
author Jianquan Zhao
Tiewei Lv
Junjun Quan
Weian Zhao
Jing Song
Zhuolin Li
Han Lei
Wei Huang
Longke Ran
spellingShingle Jianquan Zhao
Tiewei Lv
Junjun Quan
Weian Zhao
Jing Song
Zhuolin Li
Han Lei
Wei Huang
Longke Ran
Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
Journal of Biomedical Science
Dilated cardiomyopathy
Bioinformatics
Microarray
Heart failure
author_facet Jianquan Zhao
Tiewei Lv
Junjun Quan
Weian Zhao
Jing Song
Zhuolin Li
Han Lei
Wei Huang
Longke Ran
author_sort Jianquan Zhao
title Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
title_short Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
title_full Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
title_fullStr Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
title_full_unstemmed Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
title_sort identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
publisher BMC
series Journal of Biomedical Science
issn 1423-0127
publishDate 2018-08-01
description Abstract Background Identify genes probably associated with chronic heart failure and predict potential target genes for dilated cardiomyopathy using bioinformatics analyses. Methods Gene expression profiles (series number GSE3585 and GSE42955) of cardiomyopathy patients and healthy controls were downloaded from the Expression Omnibus Gene (GEO) database. Differential expression of genes (DEGS) between the two groups of total 14 cardiomyopathy patients and 10 healthy controls were subsequently identified by limma package of R. Database for Annotation, Visualization, and Integrated Discovery (DAVID Tool), which is an analysis of enriched biological processes. Search Tool for the Retrieval Interacting Genes (STRING) was used as well for the analysis of protein-protein interaction network (PPI). Prediction of the potential drugs was suggested based on the preliminarily identified genes using Connectivity Map (CMap). Results Eighty-nine DEGs were identified (57 up-regulated and 32 down-regulated). The most enrichment Gene Ontology (GO) terms (P < 0.05) contain genes involved in extracellular matrix (ECM) and biological adhesion signal pathways (P < 0.05, ES > 1.5) such as ECM-receptors, focal adhesion and transforming growth factor beta (TGF-β), etc. Fifty-one differentially expressed genes were found to encode interacting proteins. Eleven key genes along with related transcription factors were identified including CTGF, POSTN, CORIN, FIGF, etc. Conclusion Bioinformatics-based analyses reveal the targeted genes probably associated with cardiomyopathy, which provide clues for pharmacological therapies aiming at the targets.
topic Dilated cardiomyopathy
Bioinformatics
Microarray
Heart failure
url http://link.springer.com/article/10.1186/s12929-018-0459-8
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