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Joint impact of key air pollutants on COVID-19 severity: prediction based on toxicogenomic data analysis

Danijela Đukić-Ćosić

Danijela Đukić-Ćosić

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Đukić-Ćosić, Danijela
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Katarina Baralić

Katarina Baralić

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Baralić, Katarina
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Teodora Filipović

Teodora Filipović

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Filipović, Teodora
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Dragica Božić

Dragica Božić

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Božić, Dragica
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Katarina Živančević

Katarina Živančević

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Živančević, Katarina
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Evica Antonijević Miljaković

Evica Antonijević Miljaković

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Miljaković, Evica Antonijević
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Aleksandra Buha Đorđević

Aleksandra Buha Đorđević

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Đorđević, Aleksandra Buha
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Zorica Bulat

Zorica Bulat

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Bulat, Zorica
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Biljana Antonijević

Biljana Antonijević

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Antonijević, Biljana
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Marijana Ćurčić

Marijana Ćurčić

University of Belgrade Faculty of Pharmacy, Department of Toxicology “Akademik Danilo Soldatović”Belgrade, Serbia
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Ćurčić, Marijana
  
07 lip 2022
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Kategoria artykułu: Original article
Data publikacji: 07 lip 2022
Zakres stron: 119 - 125
Otrzymano: 01 lut 2022
Przyjęty: 01 maj 2022
DOI: https://doi.org/10.2478/aiht-2022-73-3631
Słowa kluczowe
© 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
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

Flow chart of toxicogenomic analysis to identify relationships between air pollutants and COVID-19. CTD – Comparative Toxicogenomic Database (http://CTD.mdibl.org)
Flow chart of toxicogenomic analysis to identify relationships between air pollutants and COVID-19. CTD – Comparative Toxicogenomic Database (http://CTD.mdibl.org)

Figure 2

Network of genes associated with SO2, CO, PMx, NO2, and O3 exposure and COVID-19 disease complications (IL10, IL6, IL1B, and TNF) (black circles) and 20 related genes predicted by the GeneMANIA tool (http://geneMANIA.org/plug-in/) (grey circles). Panel A shows prevalence of interaction types (in percentages) and panel B networks for each interaction type
Network of genes associated with SO2, CO, PMx, NO2, and O3 exposure and COVID-19 disease complications (IL10, IL6, IL1B, and TNF) (black circles) and 20 related genes predicted by the GeneMANIA tool (http://geneMANIA.org/plug-in/) (grey circles). Panel A shows prevalence of interaction types (in percentages) and panel B networks for each interaction type

Influence of air pollutants (SO2, CO, PMx, NO2 and O3) on protein secretion, mRNA expression, and protein expression of genes related to these air pollutants and COVID-19 disease complications (CTD Database; http://CTD_mdibl_org)

Air pollutant Interaction IL10 IL6 IL1B TNF
SO2 Protein secretion ↑
mRNA expression
Protein expression ↑ ↑ ↑
CO Protein secretion ↑
mRNA expression ↑
Protein expression ↑ ↑ ↑↓ ↑↓
PMx Protein secretion ↑↓ ↑ ↑ ↑
mRNA expression ↑↓ ↑↓ ↑↓
Protein expression ↑↓ ↑ ↑↓ ↑↓
NO2 Protein secretion ↑ ↓
mRNA expression ↑ ↑↓ ↓ ↑
Protein expression ↑ ↑ ↑ ↑
O3 Protein secretion ↑ ↑
mRNA expression ↓ ↑ ↑↓ ↓
Protein expression ↓ ↑ ↑↓ ↑↓

Top 10 gene-disease pairs for genes related to both COVID-19 complications and air pollutants, along with the 20 predicted genes (DisGeNET database; http://www_disgenet_org)

Gene Disease Disease class (DisGeNET) Score
CEBPA acute myelocytic leukaemia neoplasms 1.000
TNFRSF1A TNF receptor-associated periodic fever syndrome (TRAPS) pathological conditions, signs and symptoms; congenital, hereditary, and neonatal diseases and abnormalities; skin and connective tissue diseases 1.000
TNFAIP3 familial Behcet-like autoinflammatory syndrome / 0.710
TNF rheumatoid arthritis skin and connective tissue diseases; musculoskeletal diseases; immune system diseases 0.700
IL10 inflammatory bowel diseases digestive system diseases 0.700
IL10 systemic lupus erythematosus, systemic skin and connective tissue diseases diseases; immune system 0.700
IL10 Crohn's disease digestive system diseases 0.700
IL6 fever pathological conditions, signs and symptoms 0.700
TNFAIP3 systemic lupus erythematosus skin and connective tissue diseases; immune system diseases 0.700
SQSTM1 amyotrophic lateral sclerosis nutritional and metabolic diseases diseases; nervous system 0.700
Języki:
Angielski, Croatian, Slovenian
Częstotliwość wydawania:
4 razy w roku
Dziedziny czasopisma:
Medycyna, Podstawowe nauki medyczne, Podstawowe nauki medyczne, inne
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