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Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data
BACKGROUND: Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored. METHODS: This study analyzed three RNA-Seq gene expression profiling...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441550/ https://www.ncbi.nlm.nih.gov/pubmed/36072597 http://dx.doi.org/10.3389/fimmu.2022.930866 |
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author | Dong, Zehua Yan, Qiyu Cao, Wenxiu Liu, Zhixian Wang, Xiaosheng |
author_facet | Dong, Zehua Yan, Qiyu Cao, Wenxiu Liu, Zhixian Wang, Xiaosheng |
author_sort | Dong, Zehua |
collection | PubMed |
description | BACKGROUND: Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored. METHODS: This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients. RESULTS: This analysis identified 13 genes significantly upregulated in COVID-19 patients’ leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes’ downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes. CONCLUSIONS: A strong antiviral immune response is essential in reducing severity of COVID-19. |
format | Online Article Text |
id | pubmed-9441550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94415502022-09-06 Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data Dong, Zehua Yan, Qiyu Cao, Wenxiu Liu, Zhixian Wang, Xiaosheng Front Immunol Immunology BACKGROUND: Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored. METHODS: This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients. RESULTS: This analysis identified 13 genes significantly upregulated in COVID-19 patients’ leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes’ downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes. CONCLUSIONS: A strong antiviral immune response is essential in reducing severity of COVID-19. Frontiers Media S.A. 2022-08-22 /pmc/articles/PMC9441550/ /pubmed/36072597 http://dx.doi.org/10.3389/fimmu.2022.930866 Text en Copyright © 2022 Dong, Yan, Cao, Liu 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 | Immunology Dong, Zehua Yan, Qiyu Cao, Wenxiu Liu, Zhixian Wang, Xiaosheng Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data |
title | Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data |
title_full | Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data |
title_fullStr | Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data |
title_full_unstemmed | Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data |
title_short | Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data |
title_sort | identification of key molecules in covid-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441550/ https://www.ncbi.nlm.nih.gov/pubmed/36072597 http://dx.doi.org/10.3389/fimmu.2022.930866 |
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