Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis

Background: Dilated cardiomyopathy (DCM) is one of the main causes of systolic heart failure and frequently has a genetic component. The molecular mechanisms underlying the onset and progression of DCM remain unclear. This study aimed to identify novel diagnostic biomarkers to aid in the treatment a...

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Main Authors: Qixin Guo, Qiang Qu, Luyang Wang, Shengen Liao, Xu Zhu, Anning Du, Qingqing Zhu, Iokfai Cheang, Rongrong Gao, Xinli Li
Format: Article
Language:English
Published: IMR Press 2022-08-01
Series:Frontiers in Bioscience-Landmark
Subjects:
Online Access:https://www.imrpress.com/journal/FBL/27/8/10.31083/j.fbl2708246
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author Qixin Guo
Qiang Qu
Luyang Wang
Shengen Liao
Xu Zhu
Anning Du
Qingqing Zhu
Iokfai Cheang
Rongrong Gao
Xinli Li
author_facet Qixin Guo
Qiang Qu
Luyang Wang
Shengen Liao
Xu Zhu
Anning Du
Qingqing Zhu
Iokfai Cheang
Rongrong Gao
Xinli Li
author_sort Qixin Guo
collection DOAJ
description Background: Dilated cardiomyopathy (DCM) is one of the main causes of systolic heart failure and frequently has a genetic component. The molecular mechanisms underlying the onset and progression of DCM remain unclear. This study aimed to identify novel diagnostic biomarkers to aid in the treatment and diagnosis of DCM. Method: The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, GSE120895 and GSE17800, which were subsequently merged into a single cohort. Differentially expressed genes were analyzed in the DCM and control groups, followed by weighted gene coexpression network analysis to determine the core modules. Core nodes were identified by gene significance (GS) and module membership (MM) values, and four hub genes were predicted by the Lasso regression model. The expression levels and diagnostic values of the four hub genes were further validated in the datasets GSE19303. Finally, potential therapeutic drugs and upstream molecules regulating genes were identified. Results: The turquoise module is the core module of DCM. Four hub genes were identified: GYPC (glycophorin C), MLF2 (myeloid leukemia factor 2), COPS7A (COP9 signalosome subunit 7A) and ARL2 (ADP ribosylation factor like GTPase 2). Subsequently, Hub genes showed significant differences in expression in both the dataset and the validation model by real-time quantitative PCR (qPCR). Four potential modulators and seven chemicals were also identified. Finally, molecular docking simulations of the gene-encoded proteins with small-molecule drugs were successfully performed. Conclusions: The results suggested that ARL2, MLF2, GYPC and COPS7A could be potential gene biomarkers for DCM.
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spelling doaj.art-53fb85e80c6e47f397228a05c3eda04a2022-12-22T02:25:37ZengIMR PressFrontiers in Bioscience-Landmark2768-67012022-08-0127824610.31083/j.fbl2708246S2768-6701(22)00596-2Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network AnalysisQixin Guo0Qiang Qu1Luyang Wang2Shengen Liao3Xu Zhu4Anning Du5Qingqing Zhu6Iokfai Cheang7Rongrong Gao8Xinli Li9Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaBackground: Dilated cardiomyopathy (DCM) is one of the main causes of systolic heart failure and frequently has a genetic component. The molecular mechanisms underlying the onset and progression of DCM remain unclear. This study aimed to identify novel diagnostic biomarkers to aid in the treatment and diagnosis of DCM. Method: The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, GSE120895 and GSE17800, which were subsequently merged into a single cohort. Differentially expressed genes were analyzed in the DCM and control groups, followed by weighted gene coexpression network analysis to determine the core modules. Core nodes were identified by gene significance (GS) and module membership (MM) values, and four hub genes were predicted by the Lasso regression model. The expression levels and diagnostic values of the four hub genes were further validated in the datasets GSE19303. Finally, potential therapeutic drugs and upstream molecules regulating genes were identified. Results: The turquoise module is the core module of DCM. Four hub genes were identified: GYPC (glycophorin C), MLF2 (myeloid leukemia factor 2), COPS7A (COP9 signalosome subunit 7A) and ARL2 (ADP ribosylation factor like GTPase 2). Subsequently, Hub genes showed significant differences in expression in both the dataset and the validation model by real-time quantitative PCR (qPCR). Four potential modulators and seven chemicals were also identified. Finally, molecular docking simulations of the gene-encoded proteins with small-molecule drugs were successfully performed. Conclusions: The results suggested that ARL2, MLF2, GYPC and COPS7A could be potential gene biomarkers for DCM.https://www.imrpress.com/journal/FBL/27/8/10.31083/j.fbl2708246weighted gene coexpression network analysisdilated cardiomyopathy
spellingShingle Qixin Guo
Qiang Qu
Luyang Wang
Shengen Liao
Xu Zhu
Anning Du
Qingqing Zhu
Iokfai Cheang
Rongrong Gao
Xinli Li
Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis
Frontiers in Bioscience-Landmark
weighted gene coexpression network analysis
dilated cardiomyopathy
title Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis
title_full Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis
title_fullStr Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis
title_full_unstemmed Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis
title_short Identification of Potential Biomarkers Associated with Dilated Cardiomyopathy by Weighted Gene Coexpression Network Analysis
title_sort identification of potential biomarkers associated with dilated cardiomyopathy by weighted gene coexpression network analysis
topic weighted gene coexpression network analysis
dilated cardiomyopathy
url https://www.imrpress.com/journal/FBL/27/8/10.31083/j.fbl2708246
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