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A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets

The novel coronavirus (SARS-CoV-2) has expanded rapidly worldwide. Now it has covered more than 150 countries worldwide. It is referred to as COVID-19. SARS-CoV-2 mainly affects the respiratory systems of humans that can lead up to serious illness or even death in the presence of different comorbidi...

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Autores principales: Shahjaman, Md, Rezanur Rahman, Md, Rabiul Auwul, Md
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372456/
https://www.ncbi.nlm.nih.gov/pubmed/34423108
http://dx.doi.org/10.1016/j.imu.2021.100702
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author Shahjaman, Md
Rezanur Rahman, Md
Rabiul Auwul, Md
author_facet Shahjaman, Md
Rezanur Rahman, Md
Rabiul Auwul, Md
author_sort Shahjaman, Md
collection PubMed
description The novel coronavirus (SARS-CoV-2) has expanded rapidly worldwide. Now it has covered more than 150 countries worldwide. It is referred to as COVID-19. SARS-CoV-2 mainly affects the respiratory systems of humans that can lead up to serious illness or even death in the presence of different comorbidities. However, most COVID-19 infected people show mild to moderate symptoms, and no medication is suggested. Still, drugs of other diseases have been used to treat COVID-19. Nevertheless, the absence of vaccines and proper drugs against the COVID-19 virus has increased the mortality rate. Albeit sex is a risk factor for COVID-19, none of the studies considered this risk factor for identifying biomarkers from the RNASeq count dataset. Men are more likely to undertake severe symptoms with different comorbidities and show greater mortality compared with women. From this standpoint, we aim to identify shared gene signatures between males and females from the human COVID-19 RNAseq count dataset of peripheral blood cells using a robust voom approach. We identified 1341 overlapping DEGs between male and female datasets. The gene ontology (GO) annotation and pathway enrichment analysis revealed that DEGs are involved in various BP categories such as nucleosome assembly, DNA conformation change, DNA packaging, and different KEGG pathways such as cell cycle, ECM-receptor interaction, progesterone-mediated oocyte maturation, etc. Ten hub-proteins (UBC, KIAA0101, APP, CDK1, SUMO2, SP1, FN1, CDK2, E2F1, and TP53) were unveiled using PPI network analysis. The top three miRNAs (mir-17–5p, mir-20a-5p, mir-93–5p) and TFs (PPARG, E2F1 and KLF5) were uncovered. In conclusion, the top ten significant drugs (roscovitine, curcumin, simvastatin, fulvestrant, troglitazone, alvocidib, L-alanine, tamoxifen, serine, and doxorubicin) were retrieved using drug repurposing analysis of overlapping DEGs, which might be therapeutic agents of COVID-19.
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spelling pubmed-83724562021-08-18 A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets Shahjaman, Md Rezanur Rahman, Md Rabiul Auwul, Md Inform Med Unlocked Article The novel coronavirus (SARS-CoV-2) has expanded rapidly worldwide. Now it has covered more than 150 countries worldwide. It is referred to as COVID-19. SARS-CoV-2 mainly affects the respiratory systems of humans that can lead up to serious illness or even death in the presence of different comorbidities. However, most COVID-19 infected people show mild to moderate symptoms, and no medication is suggested. Still, drugs of other diseases have been used to treat COVID-19. Nevertheless, the absence of vaccines and proper drugs against the COVID-19 virus has increased the mortality rate. Albeit sex is a risk factor for COVID-19, none of the studies considered this risk factor for identifying biomarkers from the RNASeq count dataset. Men are more likely to undertake severe symptoms with different comorbidities and show greater mortality compared with women. From this standpoint, we aim to identify shared gene signatures between males and females from the human COVID-19 RNAseq count dataset of peripheral blood cells using a robust voom approach. We identified 1341 overlapping DEGs between male and female datasets. The gene ontology (GO) annotation and pathway enrichment analysis revealed that DEGs are involved in various BP categories such as nucleosome assembly, DNA conformation change, DNA packaging, and different KEGG pathways such as cell cycle, ECM-receptor interaction, progesterone-mediated oocyte maturation, etc. Ten hub-proteins (UBC, KIAA0101, APP, CDK1, SUMO2, SP1, FN1, CDK2, E2F1, and TP53) were unveiled using PPI network analysis. The top three miRNAs (mir-17–5p, mir-20a-5p, mir-93–5p) and TFs (PPARG, E2F1 and KLF5) were uncovered. In conclusion, the top ten significant drugs (roscovitine, curcumin, simvastatin, fulvestrant, troglitazone, alvocidib, L-alanine, tamoxifen, serine, and doxorubicin) were retrieved using drug repurposing analysis of overlapping DEGs, which might be therapeutic agents of COVID-19. The Authors. Published by Elsevier Ltd. 2021 2021-08-18 /pmc/articles/PMC8372456/ /pubmed/34423108 http://dx.doi.org/10.1016/j.imu.2021.100702 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Shahjaman, Md
Rezanur Rahman, Md
Rabiul Auwul, Md
A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets
title A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets
title_full A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets
title_fullStr A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets
title_full_unstemmed A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets
title_short A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets
title_sort network-based systems biology approach for identification of shared gene signatures between male and female in covid-19 datasets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372456/
https://www.ncbi.nlm.nih.gov/pubmed/34423108
http://dx.doi.org/10.1016/j.imu.2021.100702
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