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Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions

COVID-19 (Coronavirus Disease 2019) has been an ongoing pandemic, resulting in an increase in people being infected globally. Understanding the potential risk of infection for people under different respiratory system conditions is important and will help prevent disease spreading. We explored and c...

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Autores principales: Zhang, Qiang, Yue, Yuanyi, Tan, Huiwen, Liu, Yishu, Zeng, Yin, Xiao, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7468458/
https://www.ncbi.nlm.nih.gov/pubmed/32973879
http://dx.doi.org/10.3389/fgene.2020.00942
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author Zhang, Qiang
Yue, Yuanyi
Tan, Huiwen
Liu, Yishu
Zeng, Yin
Xiao, Li
author_facet Zhang, Qiang
Yue, Yuanyi
Tan, Huiwen
Liu, Yishu
Zeng, Yin
Xiao, Li
author_sort Zhang, Qiang
collection PubMed
description COVID-19 (Coronavirus Disease 2019) has been an ongoing pandemic, resulting in an increase in people being infected globally. Understanding the potential risk of infection for people under different respiratory system conditions is important and will help prevent disease spreading. We explored and collected five published and one unpublished single-cell respiratory system tissue transcriptome datasets, including idiopathic pulmonary fibrosis (IPF), aging lungs (mouse origin data), lung cancers, and smoked branchial epithelium, for specifically reanalyzing the ACE2 and TMPRSS2 expression profiles. Compared to normal people, we found that smoking and lung cancer increase the risk for COVID-19 infection due to a higher expression of ACE2 and TMPRSS2 in lung cells. Aged lung does not show increased risk for infection. IPF patients may have a lower risk for original COVID-19 infection due to lower expression in AT2 cells but may have a higher risk for severity due to a broader expression spectrum of TMPRSS2. Further investigation and validation on these cell types are required. Nonetheless, this is the first report to predict the risk and potential severity for COVID-19 infection for people with different respiratory system conditions. Our analysis is the first systematic description and analysis to illustrate how the underlying respiratory system conditions contribute to a higher infection risk.
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spelling pubmed-74684582020-09-23 Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions Zhang, Qiang Yue, Yuanyi Tan, Huiwen Liu, Yishu Zeng, Yin Xiao, Li Front Genet Genetics COVID-19 (Coronavirus Disease 2019) has been an ongoing pandemic, resulting in an increase in people being infected globally. Understanding the potential risk of infection for people under different respiratory system conditions is important and will help prevent disease spreading. We explored and collected five published and one unpublished single-cell respiratory system tissue transcriptome datasets, including idiopathic pulmonary fibrosis (IPF), aging lungs (mouse origin data), lung cancers, and smoked branchial epithelium, for specifically reanalyzing the ACE2 and TMPRSS2 expression profiles. Compared to normal people, we found that smoking and lung cancer increase the risk for COVID-19 infection due to a higher expression of ACE2 and TMPRSS2 in lung cells. Aged lung does not show increased risk for infection. IPF patients may have a lower risk for original COVID-19 infection due to lower expression in AT2 cells but may have a higher risk for severity due to a broader expression spectrum of TMPRSS2. Further investigation and validation on these cell types are required. Nonetheless, this is the first report to predict the risk and potential severity for COVID-19 infection for people with different respiratory system conditions. Our analysis is the first systematic description and analysis to illustrate how the underlying respiratory system conditions contribute to a higher infection risk. Frontiers Media S.A. 2020-08-20 /pmc/articles/PMC7468458/ /pubmed/32973879 http://dx.doi.org/10.3389/fgene.2020.00942 Text en Copyright © 2020 Zhang, Yue, Tan, Liu, Zeng and Xiao. http://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 Genetics
Zhang, Qiang
Yue, Yuanyi
Tan, Huiwen
Liu, Yishu
Zeng, Yin
Xiao, Li
Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions
title Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions
title_full Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions
title_fullStr Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions
title_full_unstemmed Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions
title_short Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions
title_sort single cell rna-seq data analysis reveals the potential risk of sars-cov-2 infection among different respiratory system conditions
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7468458/
https://www.ncbi.nlm.nih.gov/pubmed/32973879
http://dx.doi.org/10.3389/fgene.2020.00942
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