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Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis

Introduction: Coronavirus disease 2019 (COVID-19) has become a global pandemic and poses a serious threat to human health. Many studies have shown that pre-existing nonalcoholic steatohepatitis (NASH) can worsen the clinical symptoms in patients suffering from COVID-19. However, the potential molecu...

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Autores principales: Lu, Huishuang, Ma, Jiaxiu, Li, Yalan, Zhang, Jin, An, Yaxin, Du, Wei, Cai, Xuefei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315682/
https://www.ncbi.nlm.nih.gov/pubmed/37405258
http://dx.doi.org/10.3389/fmolb.2023.1164220
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author Lu, Huishuang
Ma, Jiaxiu
Li, Yalan
Zhang, Jin
An, Yaxin
Du, Wei
Cai, Xuefei
author_facet Lu, Huishuang
Ma, Jiaxiu
Li, Yalan
Zhang, Jin
An, Yaxin
Du, Wei
Cai, Xuefei
author_sort Lu, Huishuang
collection PubMed
description Introduction: Coronavirus disease 2019 (COVID-19) has become a global pandemic and poses a serious threat to human health. Many studies have shown that pre-existing nonalcoholic steatohepatitis (NASH) can worsen the clinical symptoms in patients suffering from COVID-19. However, the potential molecular mechanisms between NASH and COVID-19 remain unclear. To this end, key molecules and pathways between COVID-19 and NASH were herein explored by bioinformatic analysis. Methods: The common differentially expressed genes (DEGs) between NASH and COVID-19 were obtained by differential gene analysis. Enrichment analysis and protein-protein interaction (PPI) network analysis were carried out using the obtained common DEGs. The key modules and hub genes in PPI network were obtained by using the plug-in of Cytoscape software. Subsequently, the hub genes were verified using datasets of NASH (GSE180882) and COVID-19 (GSE150316), and further evaluated by principal component analysis (PCA) and receiver operating characteristic (ROC). Finally, the verified hub genes were analyzed by single-sample gene set enrichment analysis (ssGSEA) and NetworkAnalyst was used for the analysis of transcription factor (TF)-gene interactions, TF-microRNAs (miRNA) coregulatory network, and Protein-chemical Interactions. Results: A total of 120 DEGs between NASH and COVID-19 datasets were obtained, and the PPI network was constructed. Two key modules were obtained via the PPI network, and enrichment analysis of the key modules revealed the common association between NASH and COVID-19. In total, 16 hub genes were obtained by five algorithms, and six of them, namely, Kruppel-like factor 6 (KLF6), early growth response 1 (EGR1), growth arrest and DNA-damage-inducible 45 beta (GADD45B), JUNB, FOS, and FOS-like antigen 1 (FOSL1) were confirmed to be closely related to NASH and COVID-19. Finally, the relationship between hub genes and related pathways was analyzed, and the interaction network of six hub genes was constructed with TFs, miRNAs, and compounds. Conclusion: This study identified six hub genes related to COVID-19 and NASH, providing a new perspective for disease diagnosis and drug development.
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spelling pubmed-103156822023-07-04 Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis Lu, Huishuang Ma, Jiaxiu Li, Yalan Zhang, Jin An, Yaxin Du, Wei Cai, Xuefei Front Mol Biosci Molecular Biosciences Introduction: Coronavirus disease 2019 (COVID-19) has become a global pandemic and poses a serious threat to human health. Many studies have shown that pre-existing nonalcoholic steatohepatitis (NASH) can worsen the clinical symptoms in patients suffering from COVID-19. However, the potential molecular mechanisms between NASH and COVID-19 remain unclear. To this end, key molecules and pathways between COVID-19 and NASH were herein explored by bioinformatic analysis. Methods: The common differentially expressed genes (DEGs) between NASH and COVID-19 were obtained by differential gene analysis. Enrichment analysis and protein-protein interaction (PPI) network analysis were carried out using the obtained common DEGs. The key modules and hub genes in PPI network were obtained by using the plug-in of Cytoscape software. Subsequently, the hub genes were verified using datasets of NASH (GSE180882) and COVID-19 (GSE150316), and further evaluated by principal component analysis (PCA) and receiver operating characteristic (ROC). Finally, the verified hub genes were analyzed by single-sample gene set enrichment analysis (ssGSEA) and NetworkAnalyst was used for the analysis of transcription factor (TF)-gene interactions, TF-microRNAs (miRNA) coregulatory network, and Protein-chemical Interactions. Results: A total of 120 DEGs between NASH and COVID-19 datasets were obtained, and the PPI network was constructed. Two key modules were obtained via the PPI network, and enrichment analysis of the key modules revealed the common association between NASH and COVID-19. In total, 16 hub genes were obtained by five algorithms, and six of them, namely, Kruppel-like factor 6 (KLF6), early growth response 1 (EGR1), growth arrest and DNA-damage-inducible 45 beta (GADD45B), JUNB, FOS, and FOS-like antigen 1 (FOSL1) were confirmed to be closely related to NASH and COVID-19. Finally, the relationship between hub genes and related pathways was analyzed, and the interaction network of six hub genes was constructed with TFs, miRNAs, and compounds. Conclusion: This study identified six hub genes related to COVID-19 and NASH, providing a new perspective for disease diagnosis and drug development. Frontiers Media S.A. 2023-06-19 /pmc/articles/PMC10315682/ /pubmed/37405258 http://dx.doi.org/10.3389/fmolb.2023.1164220 Text en Copyright © 2023 Lu, Ma, Li, Zhang, An, Du and Cai. 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 Molecular Biosciences
Lu, Huishuang
Ma, Jiaxiu
Li, Yalan
Zhang, Jin
An, Yaxin
Du, Wei
Cai, Xuefei
Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis
title Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis
title_full Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis
title_fullStr Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis
title_full_unstemmed Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis
title_short Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis
title_sort bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between covid-19 and non-alcoholic hepatitis
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315682/
https://www.ncbi.nlm.nih.gov/pubmed/37405258
http://dx.doi.org/10.3389/fmolb.2023.1164220
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