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Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study
Coronavirus disease 2019 (COVID-19) is a viral pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that led to more than 800,00 deaths and continues to be a major threat worldwide. The scientific community has been studying the risk factors associated with SARS-CoV-2 infe...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8358088/ https://www.ncbi.nlm.nih.gov/pubmed/34401607 http://dx.doi.org/10.1016/j.genrep.2021.101312 |
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author | Manivannan, Jeganathan Sundaresan, Lakshmikirupa |
author_facet | Manivannan, Jeganathan Sundaresan, Lakshmikirupa |
author_sort | Manivannan, Jeganathan |
collection | PubMed |
description | Coronavirus disease 2019 (COVID-19) is a viral pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that led to more than 800,00 deaths and continues to be a major threat worldwide. The scientific community has been studying the risk factors associated with SARS-CoV-2 infection and pathogenesis. Recent studies highlight the possible contribution of atmospheric air pollution, specifically particulate matter (PM) exposure as a co-factor in COVID-19 severity. Hence, meaningful translation of suitable omics datasets of SARS-CoV-2 infection and PM exposure is warranted to understand the possible involvement of airborne exposome on COVID-19 outcome. Publicly available transcriptomic data (microarray and RNA-Seq) related to COVID-19 lung biopsy, SARS-CoV-2 infection in epithelial cells and PM exposure (lung tissue, epithelial and endothelial cells) were obtained in addition with proteome and interactome datasets. System-wide pathway/network analysis was done through appropriate software tools and data resources. The primary findings are; 1. There is no robust difference in the expression of SARS-CoV-2 entry factors upon particulate exposure, 2. The upstream pathways associated with upregulated genes during SARS-CoV-2 infection considerably overlap with that of PM exposure, 3. Similar pathways were differentially expressed during SARS-CoV-2 infection and PM exposure, 4. SARS-CoV-2 interacting host factors were predicted to be associated with the molecular impact of PM exposure and 5. Differentially expressed pathways during PM exposure may increase COVID-19 severity. Based on the observed molecular mechanisms (direct and indirect effects) the current study suggests that airborne PM exposure has to be considered as an additional co-factor in the outcome of COVID-19. |
format | Online Article Text |
id | pubmed-8358088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83580882021-08-12 Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study Manivannan, Jeganathan Sundaresan, Lakshmikirupa Gene Rep Article Coronavirus disease 2019 (COVID-19) is a viral pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that led to more than 800,00 deaths and continues to be a major threat worldwide. The scientific community has been studying the risk factors associated with SARS-CoV-2 infection and pathogenesis. Recent studies highlight the possible contribution of atmospheric air pollution, specifically particulate matter (PM) exposure as a co-factor in COVID-19 severity. Hence, meaningful translation of suitable omics datasets of SARS-CoV-2 infection and PM exposure is warranted to understand the possible involvement of airborne exposome on COVID-19 outcome. Publicly available transcriptomic data (microarray and RNA-Seq) related to COVID-19 lung biopsy, SARS-CoV-2 infection in epithelial cells and PM exposure (lung tissue, epithelial and endothelial cells) were obtained in addition with proteome and interactome datasets. System-wide pathway/network analysis was done through appropriate software tools and data resources. The primary findings are; 1. There is no robust difference in the expression of SARS-CoV-2 entry factors upon particulate exposure, 2. The upstream pathways associated with upregulated genes during SARS-CoV-2 infection considerably overlap with that of PM exposure, 3. Similar pathways were differentially expressed during SARS-CoV-2 infection and PM exposure, 4. SARS-CoV-2 interacting host factors were predicted to be associated with the molecular impact of PM exposure and 5. Differentially expressed pathways during PM exposure may increase COVID-19 severity. Based on the observed molecular mechanisms (direct and indirect effects) the current study suggests that airborne PM exposure has to be considered as an additional co-factor in the outcome of COVID-19. Elsevier Inc. 2021-12 2021-08-12 /pmc/articles/PMC8358088/ /pubmed/34401607 http://dx.doi.org/10.1016/j.genrep.2021.101312 Text en © 2021 Elsevier Inc. All rights reserved. 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 Manivannan, Jeganathan Sundaresan, Lakshmikirupa Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study |
title | Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study |
title_full | Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study |
title_fullStr | Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study |
title_full_unstemmed | Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study |
title_short | Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome – A multi-omics big data study |
title_sort | systems level insights into the impact of airborne exposure on sars-cov-2 pathogenesis and covid-19 outcome – a multi-omics big data study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8358088/ https://www.ncbi.nlm.nih.gov/pubmed/34401607 http://dx.doi.org/10.1016/j.genrep.2021.101312 |
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