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Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy
Diabetic cardiomyopathy (DCM) is a pathophysiological condition induced by diabetes mellitus that often causes heart failure (HF). However, their mechanistic relationships remain unclear. This study aimed to identify immune gene signatures and molecular mechanisms of DCM. Microarray data from the Ge...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421304/ https://www.ncbi.nlm.nih.gov/pubmed/36046789 http://dx.doi.org/10.3389/fendo.2022.933635 |
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author | Guo, Qixin Zhu, Qingqing Zhang, Ting Qu, Qiang Cheang, Iokfai Liao, Shengen Chen, Mengli Zhu, Xu Shi, Mengsha Li, Xinli |
author_facet | Guo, Qixin Zhu, Qingqing Zhang, Ting Qu, Qiang Cheang, Iokfai Liao, Shengen Chen, Mengli Zhu, Xu Shi, Mengsha Li, Xinli |
author_sort | Guo, Qixin |
collection | PubMed |
description | Diabetic cardiomyopathy (DCM) is a pathophysiological condition induced by diabetes mellitus that often causes heart failure (HF). However, their mechanistic relationships remain unclear. This study aimed to identify immune gene signatures and molecular mechanisms of DCM. Microarray data from the Gene Expression Omnibus (GEO) database from patients with DCM were subjected to weighted gene co-expression network analysis (WGCNA) identify co-expression modules. Core expression modules were intersected with the immune gene database. We analyzed and mapped protein-protein interaction (PPI) networks using the STRING database and MCODE and filtering out 17 hub genes using cytoHubba software. Finally, potential transcriptional regulatory factors and therapeutic drugs were identified and molecular docking between gene targets and small molecules was performed. We identified five potential immune biomarkers: proteosome subunit beta type-8 (PSMB8), nuclear factor kappa B1 (NFKB1), albumin (ALB), endothelin 1 (EDN1), and estrogen receptor 1 (ESR1). Their expression levels in animal models were consistent with the changes observed in the datasets. EDN1 showed significant differences in expression in both the dataset and the validation model by real-time quantitative PCR (qPCR) and Western blotting(WB). Subsequently, we confirmed that the potential transcription factors upstream of EDN1 were PRDM5 and KLF4, as its expression was positively correlated with the expression of the two transcription factors. To repurpose known therapeutic drugs, a connectivity map (CMap) database was retrieved, and nine candidate compounds were identified. Finally, molecular docking simulations of the proteins encoded by the five genes with small-molecule drugs were performed. Our data suggest that EDN1 may play a key role in the development of DCM and is a potential DCM biomarker. |
format | Online Article Text |
id | pubmed-9421304 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94213042022-08-30 Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy Guo, Qixin Zhu, Qingqing Zhang, Ting Qu, Qiang Cheang, Iokfai Liao, Shengen Chen, Mengli Zhu, Xu Shi, Mengsha Li, Xinli Front Endocrinol (Lausanne) Endocrinology Diabetic cardiomyopathy (DCM) is a pathophysiological condition induced by diabetes mellitus that often causes heart failure (HF). However, their mechanistic relationships remain unclear. This study aimed to identify immune gene signatures and molecular mechanisms of DCM. Microarray data from the Gene Expression Omnibus (GEO) database from patients with DCM were subjected to weighted gene co-expression network analysis (WGCNA) identify co-expression modules. Core expression modules were intersected with the immune gene database. We analyzed and mapped protein-protein interaction (PPI) networks using the STRING database and MCODE and filtering out 17 hub genes using cytoHubba software. Finally, potential transcriptional regulatory factors and therapeutic drugs were identified and molecular docking between gene targets and small molecules was performed. We identified five potential immune biomarkers: proteosome subunit beta type-8 (PSMB8), nuclear factor kappa B1 (NFKB1), albumin (ALB), endothelin 1 (EDN1), and estrogen receptor 1 (ESR1). Their expression levels in animal models were consistent with the changes observed in the datasets. EDN1 showed significant differences in expression in both the dataset and the validation model by real-time quantitative PCR (qPCR) and Western blotting(WB). Subsequently, we confirmed that the potential transcription factors upstream of EDN1 were PRDM5 and KLF4, as its expression was positively correlated with the expression of the two transcription factors. To repurpose known therapeutic drugs, a connectivity map (CMap) database was retrieved, and nine candidate compounds were identified. Finally, molecular docking simulations of the proteins encoded by the five genes with small-molecule drugs were performed. Our data suggest that EDN1 may play a key role in the development of DCM and is a potential DCM biomarker. Frontiers Media S.A. 2022-08-15 /pmc/articles/PMC9421304/ /pubmed/36046789 http://dx.doi.org/10.3389/fendo.2022.933635 Text en Copyright © 2022 Guo, Zhu, Zhang, Qu, Cheang, Liao, Chen, Zhu, Shi and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Guo, Qixin Zhu, Qingqing Zhang, Ting Qu, Qiang Cheang, Iokfai Liao, Shengen Chen, Mengli Zhu, Xu Shi, Mengsha Li, Xinli Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy |
title | Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy |
title_full | Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy |
title_fullStr | Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy |
title_full_unstemmed | Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy |
title_short | Integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy |
title_sort | integrated bioinformatic analysis reveals immune molecular markers and potential drugs for diabetic cardiomyopathy |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421304/ https://www.ncbi.nlm.nih.gov/pubmed/36046789 http://dx.doi.org/10.3389/fendo.2022.933635 |
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