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Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals’ health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the mole...

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Autores principales: Huang, Tengda, Jiang, Nan, Song, Yujia, Pan, Hongyuan, Du, Ao, Yu, Bingxuan, Li, Xiaoquan, He, Jinyi, Yuan, Kefei, Wang, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591333/
https://www.ncbi.nlm.nih.gov/pubmed/37877121
http://dx.doi.org/10.3389/fmolb.2023.1274463
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author Huang, Tengda
Jiang, Nan
Song, Yujia
Pan, Hongyuan
Du, Ao
Yu, Bingxuan
Li, Xiaoquan
He, Jinyi
Yuan, Kefei
Wang, Zhen
author_facet Huang, Tengda
Jiang, Nan
Song, Yujia
Pan, Hongyuan
Du, Ao
Yu, Bingxuan
Li, Xiaoquan
He, Jinyi
Yuan, Kefei
Wang, Zhen
author_sort Huang, Tengda
collection PubMed
description Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals’ health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the molecular mechanisms underlying the association between MUO and COVID-19 are poorly understood. Methods: We sought to reveal the relationship between MUO and COVID-19 using bioinformatics and systems biology analysis approaches. Here, two datasets (GSE196822 and GSE152991) were employed to extract differentially expressed genes (DEGs) to identify common hub genes, shared pathways, transcriptional regulatory networks, gene-disease relationship and candidate drugs. Results: Based on the identified 65 common DEGs, the complement-related pathways and neutrophil degranulation-related functions are found to be mainly affected. The hub genes, which included SPI1, CD163, C1QB, SIGLEC1, C1QA, ITGAM, CD14, FCGR1A, VSIG4 and C1QC, were identified. From the interaction network analysis, 65 transcription factors (TFs) were found to be the regulatory signals. Some infections, inflammation and liver diseases were found to be most coordinated with the hub genes. Importantly, Paricalcitol, 3,3′,4,4′,5-Pentachlorobiphenyl, PD 98059, Medroxyprogesterone acetate, Dexamethasone and Tretinoin HL60 UP have shown possibility as therapeutic agents against COVID-19 and MUO. Conclusion: This study provides new clues and references to treat both COVID-19 and MUO.
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spelling pubmed-105913332023-10-24 Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients Huang, Tengda Jiang, Nan Song, Yujia Pan, Hongyuan Du, Ao Yu, Bingxuan Li, Xiaoquan He, Jinyi Yuan, Kefei Wang, Zhen Front Mol Biosci Molecular Biosciences Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals’ health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the molecular mechanisms underlying the association between MUO and COVID-19 are poorly understood. Methods: We sought to reveal the relationship between MUO and COVID-19 using bioinformatics and systems biology analysis approaches. Here, two datasets (GSE196822 and GSE152991) were employed to extract differentially expressed genes (DEGs) to identify common hub genes, shared pathways, transcriptional regulatory networks, gene-disease relationship and candidate drugs. Results: Based on the identified 65 common DEGs, the complement-related pathways and neutrophil degranulation-related functions are found to be mainly affected. The hub genes, which included SPI1, CD163, C1QB, SIGLEC1, C1QA, ITGAM, CD14, FCGR1A, VSIG4 and C1QC, were identified. From the interaction network analysis, 65 transcription factors (TFs) were found to be the regulatory signals. Some infections, inflammation and liver diseases were found to be most coordinated with the hub genes. Importantly, Paricalcitol, 3,3′,4,4′,5-Pentachlorobiphenyl, PD 98059, Medroxyprogesterone acetate, Dexamethasone and Tretinoin HL60 UP have shown possibility as therapeutic agents against COVID-19 and MUO. Conclusion: This study provides new clues and references to treat both COVID-19 and MUO. Frontiers Media S.A. 2023-10-09 /pmc/articles/PMC10591333/ /pubmed/37877121 http://dx.doi.org/10.3389/fmolb.2023.1274463 Text en Copyright © 2023 Huang, Jiang, Song, Pan, Du, Yu, Li, He, Yuan and Wang. 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
Huang, Tengda
Jiang, Nan
Song, Yujia
Pan, Hongyuan
Du, Ao
Yu, Bingxuan
Li, Xiaoquan
He, Jinyi
Yuan, Kefei
Wang, Zhen
Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients
title Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients
title_full Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients
title_fullStr Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients
title_full_unstemmed Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients
title_short Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients
title_sort bioinformatics and system biology approach to identify the influences of sars-cov-2 on metabolic unhealthy obese patients
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591333/
https://www.ncbi.nlm.nih.gov/pubmed/37877121
http://dx.doi.org/10.3389/fmolb.2023.1274463
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