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Gene expression network analysis provides potential targets against SARS-CoV-2

Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their bi...

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Autores principales: Hernández Cordero, Ana I., Li, Xuan, Yang, Chen Xi, Milne, Stephen, Bossé, Yohan, Joubert, Philippe, Timens, Wim, van den Berge, Maarten, Nickle, David, Hao, Ke, Sin, Don D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736291/
https://www.ncbi.nlm.nih.gov/pubmed/33318519
http://dx.doi.org/10.1038/s41598-020-78818-w
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author Hernández Cordero, Ana I.
Li, Xuan
Yang, Chen Xi
Milne, Stephen
Bossé, Yohan
Joubert, Philippe
Timens, Wim
van den Berge, Maarten
Nickle, David
Hao, Ke
Sin, Don D.
author_facet Hernández Cordero, Ana I.
Li, Xuan
Yang, Chen Xi
Milne, Stephen
Bossé, Yohan
Joubert, Philippe
Timens, Wim
van den Berge, Maarten
Nickle, David
Hao, Ke
Sin, Don D.
author_sort Hernández Cordero, Ana I.
collection PubMed
description Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their biological functions and potential as druggable targets. Using the gene expression profiles of 1,038 lung tissue samples, we performed a weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. We explored the biology of co-expressed genes using bioinformatics databases, and identified known drug-gene interactions. ACE2 was in a module of 681 co-expressed genes; 10 genes with moderate-high correlation with ACE2 (r > 0.3, FDR < 0.05) had known interactions with existing drug compounds. TMPRSS2 was in a module of 1,086 co-expressed genes; 31 of these genes were enriched in the gene ontology biologic process ‘receptor-mediated endocytosis’, and 52 TMPRSS2-correlated genes had known interactions with drug compounds. Dozens of genes are co-expressed with ACE2 and TMPRSS2, many of which have plausible links to COVID-19 pathophysiology. Many of the co-expressed genes are potentially targetable with existing drugs, which may accelerate the development of COVID-19 therapeutics.
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spelling pubmed-77362912020-12-15 Gene expression network analysis provides potential targets against SARS-CoV-2 Hernández Cordero, Ana I. Li, Xuan Yang, Chen Xi Milne, Stephen Bossé, Yohan Joubert, Philippe Timens, Wim van den Berge, Maarten Nickle, David Hao, Ke Sin, Don D. Sci Rep Article Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their biological functions and potential as druggable targets. Using the gene expression profiles of 1,038 lung tissue samples, we performed a weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. We explored the biology of co-expressed genes using bioinformatics databases, and identified known drug-gene interactions. ACE2 was in a module of 681 co-expressed genes; 10 genes with moderate-high correlation with ACE2 (r > 0.3, FDR < 0.05) had known interactions with existing drug compounds. TMPRSS2 was in a module of 1,086 co-expressed genes; 31 of these genes were enriched in the gene ontology biologic process ‘receptor-mediated endocytosis’, and 52 TMPRSS2-correlated genes had known interactions with drug compounds. Dozens of genes are co-expressed with ACE2 and TMPRSS2, many of which have plausible links to COVID-19 pathophysiology. Many of the co-expressed genes are potentially targetable with existing drugs, which may accelerate the development of COVID-19 therapeutics. Nature Publishing Group UK 2020-12-14 /pmc/articles/PMC7736291/ /pubmed/33318519 http://dx.doi.org/10.1038/s41598-020-78818-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Hernández Cordero, Ana I.
Li, Xuan
Yang, Chen Xi
Milne, Stephen
Bossé, Yohan
Joubert, Philippe
Timens, Wim
van den Berge, Maarten
Nickle, David
Hao, Ke
Sin, Don D.
Gene expression network analysis provides potential targets against SARS-CoV-2
title Gene expression network analysis provides potential targets against SARS-CoV-2
title_full Gene expression network analysis provides potential targets against SARS-CoV-2
title_fullStr Gene expression network analysis provides potential targets against SARS-CoV-2
title_full_unstemmed Gene expression network analysis provides potential targets against SARS-CoV-2
title_short Gene expression network analysis provides potential targets against SARS-CoV-2
title_sort gene expression network analysis provides potential targets against sars-cov-2
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736291/
https://www.ncbi.nlm.nih.gov/pubmed/33318519
http://dx.doi.org/10.1038/s41598-020-78818-w
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