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Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis
Considering that some researchers point to a possible influence of air pollution on COVID-19 transmission, severity, and death rate, the aim of our in silico study was to determine the relationship between the key air pollutants [sulphur dioxide (SO), carbon monoxide (CO), (2)particulate matter (PM(...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Sciendo
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9287838/ https://www.ncbi.nlm.nih.gov/pubmed/35792766 http://dx.doi.org/10.2478/aiht-2022-73-3631 |
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author | Đukić-Ćosić, Danijela Baralić, Katarina Filipović, Teodora Božić, Dragica Živančević, Katarina Miljaković, Evica Antonijević Đorđević, Aleksandra Buha Bulat, Zorica Antonijević, Biljana Ćurčić, Marijana |
author_facet | Đukić-Ćosić, Danijela Baralić, Katarina Filipović, Teodora Božić, Dragica Živančević, Katarina Miljaković, Evica Antonijević Đorđević, Aleksandra Buha Bulat, Zorica Antonijević, Biljana Ćurčić, Marijana |
author_sort | Đukić-Ćosić, Danijela |
collection | PubMed |
description | Considering that some researchers point to a possible influence of air pollution on COVID-19 transmission, severity, and death rate, the aim of our in silico study was to determine the relationship between the key air pollutants [sulphur dioxide (SO), carbon monoxide (CO), (2)particulate matter (PM(x)), nitrogen dioxide (NO(2)), and ozone (O(3))] and COVID-19 complications using the publicly available toxicogenomic analytical and prediction tools: (i) Comparative Toxicogenomic Database (CTD) to identify genes common to air pollutants and COVID-19 complications; (ii) GeneMANIA to construct a network of these common and related genes; (iii) ToppGene Suite to extract the most important biological processes and molecular pathways; and (iv) DisGeNET to search for the top gene-disease pairs. SO(2), CO, PM(x), NO(2), and O(3) interacted with 6, 6, 18, 9, and 12 COVID-19-related genes, respectively. Four of these are common for all pollutants (IL10, IL6, IL1B, and TNF) and participate in most (77.64 %) physical interactions. Further analysis pointed to cytokine binding and cytokine-mediated signalling pathway as the most important molecular function and biological process, respectively. Other molecular functions and biological processes are mostly related to cytokine activity and inflammation, which might be connected to the cytokine storm and resulting COVID-19 complications. The final step singled out the link between the CEBPA gene and acute myelocytic leukaemia and between TNFRSF1A and TNF receptor-associated periodic fever syndrome. This indicates possible complications in COVID-19 patients suffering from these diseases, especially those living in urban areas with poor air quality. |
format | Online Article Text |
id | pubmed-9287838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Sciendo |
record_format | MEDLINE/PubMed |
spelling | pubmed-92878382022-07-27 Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis Đukić-Ćosić, Danijela Baralić, Katarina Filipović, Teodora Božić, Dragica Živančević, Katarina Miljaković, Evica Antonijević Đorđević, Aleksandra Buha Bulat, Zorica Antonijević, Biljana Ćurčić, Marijana Arh Hig Rada Toksikol Original Article Considering that some researchers point to a possible influence of air pollution on COVID-19 transmission, severity, and death rate, the aim of our in silico study was to determine the relationship between the key air pollutants [sulphur dioxide (SO), carbon monoxide (CO), (2)particulate matter (PM(x)), nitrogen dioxide (NO(2)), and ozone (O(3))] and COVID-19 complications using the publicly available toxicogenomic analytical and prediction tools: (i) Comparative Toxicogenomic Database (CTD) to identify genes common to air pollutants and COVID-19 complications; (ii) GeneMANIA to construct a network of these common and related genes; (iii) ToppGene Suite to extract the most important biological processes and molecular pathways; and (iv) DisGeNET to search for the top gene-disease pairs. SO(2), CO, PM(x), NO(2), and O(3) interacted with 6, 6, 18, 9, and 12 COVID-19-related genes, respectively. Four of these are common for all pollutants (IL10, IL6, IL1B, and TNF) and participate in most (77.64 %) physical interactions. Further analysis pointed to cytokine binding and cytokine-mediated signalling pathway as the most important molecular function and biological process, respectively. Other molecular functions and biological processes are mostly related to cytokine activity and inflammation, which might be connected to the cytokine storm and resulting COVID-19 complications. The final step singled out the link between the CEBPA gene and acute myelocytic leukaemia and between TNFRSF1A and TNF receptor-associated periodic fever syndrome. This indicates possible complications in COVID-19 patients suffering from these diseases, especially those living in urban areas with poor air quality. Sciendo 2022-07-07 /pmc/articles/PMC9287838/ /pubmed/35792766 http://dx.doi.org/10.2478/aiht-2022-73-3631 Text en © 2022 Danijela Đukić-Ćosić, Katarina Baralić, Teodora Filipović, Dragica Božić, Katarina Živančević, Evica Antonijević Miljaković, Aleksandra Buha Đorđević, Zorica Bulat, Biljana Antonijević, and Marijana Ćurčić, published by Sciendo https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Original Article Đukić-Ćosić, Danijela Baralić, Katarina Filipović, Teodora Božić, Dragica Živančević, Katarina Miljaković, Evica Antonijević Đorđević, Aleksandra Buha Bulat, Zorica Antonijević, Biljana Ćurčić, Marijana Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis |
title | Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis |
title_full | Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis |
title_fullStr | Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis |
title_full_unstemmed | Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis |
title_short | Joint Impact of Key Air Pollutants on COVID-19 Severity: Prediction based on Toxicogenomic Data Analysis |
title_sort | joint impact of key air pollutants on covid-19 severity: prediction based on toxicogenomic data analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9287838/ https://www.ncbi.nlm.nih.gov/pubmed/35792766 http://dx.doi.org/10.2478/aiht-2022-73-3631 |
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