Cargando…

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(...

Descripción completa

Detalles Bibliográficos
Autores principales: Đukić-Ćosić, Danijela, Baralić, Katarina, Filipović, Teodora, Božić, Dragica, Živančević, Katarina, Miljaković, Evica Antonijević, Đorđević, Aleksandra Buha, Bulat, Zorica, Antonijević, Biljana, Ćurčić, Marijana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2022
Materias:
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
_version_ 1784748336728768512
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
work_keys_str_mv AT đukiccosicdanijela jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT baralickatarina jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT filipovicteodora jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT bozicdragica jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT zivancevickatarina jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT miljakovicevicaantonijevic jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT đorđevicaleksandrabuha jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT bulatzorica jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT antonijevicbiljana jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis
AT curcicmarijana jointimpactofkeyairpollutantsoncovid19severitypredictionbasedontoxicogenomicdataanalysis