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Quantification of Cytokine Storms During Virus Infections

Highly pathogenic virus infections usually trigger cytokine storms, which may have adverse effects on vital organs and result in high mortalities. The two cytokines interleukin (IL)-4 and interferon (IFN)-γ play key roles in the generation and regulation of cytokine storms. However, it is still uncl...

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Autores principales: Yuan, Shu, Jiang, Si-Cong, Zhang, Zhong-Wei, Fu, Yu-Fan, Hu, Jing, Li, Zi-Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165266/
https://www.ncbi.nlm.nih.gov/pubmed/34079547
http://dx.doi.org/10.3389/fimmu.2021.659419
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author Yuan, Shu
Jiang, Si-Cong
Zhang, Zhong-Wei
Fu, Yu-Fan
Hu, Jing
Li, Zi-Lin
author_facet Yuan, Shu
Jiang, Si-Cong
Zhang, Zhong-Wei
Fu, Yu-Fan
Hu, Jing
Li, Zi-Lin
author_sort Yuan, Shu
collection PubMed
description Highly pathogenic virus infections usually trigger cytokine storms, which may have adverse effects on vital organs and result in high mortalities. The two cytokines interleukin (IL)-4 and interferon (IFN)-γ play key roles in the generation and regulation of cytokine storms. However, it is still unclear whether the cytokine with the largest induction amplitude is the same under different virus infections. It is unknown which is the most critical and whether there are any mathematical formulas that can fit the changing rules of cytokines. Three coronaviruses (SARS-CoV, MERS-CoV, and SARS-CoV-2), three influenza viruses (2009H1N1, H5N1 and H7N9), Ebola virus, human immunodeficiency virus, dengue virus, Zika virus, West Nile virus, hepatitis B virus, hepatitis C virus, and enterovirus 71 were included in this analysis. We retrieved the cytokine fold change (FC), viral load, and clearance rate data from these highly pathogenic virus infections in humans and analyzed the correlations among them. Our analysis showed that interferon-inducible protein (IP)-10, IL-6, IL-8 and IL-17 are the most common cytokines with the largest induction amplitudes. Equations were obtained: the maximum induced cytokine (max) FC = IFN-γ FC × (IFN-γ FC/IL-4 FC) (if IFN-γ FC/IL-4 FC > 1); max FC = IL-4 FC (if IFN-γ FC/IL-4 FC < 1). For IFN-γ-inducible infections, 1.30 × log2 (IFN-γ FC) = log10 (viral load) − 2.48 − 2.83 × (clearance rate). The clinical relevance of cytokines and their antagonists is also discussed.
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spelling pubmed-81652662021-06-01 Quantification of Cytokine Storms During Virus Infections Yuan, Shu Jiang, Si-Cong Zhang, Zhong-Wei Fu, Yu-Fan Hu, Jing Li, Zi-Lin Front Immunol Immunology Highly pathogenic virus infections usually trigger cytokine storms, which may have adverse effects on vital organs and result in high mortalities. The two cytokines interleukin (IL)-4 and interferon (IFN)-γ play key roles in the generation and regulation of cytokine storms. However, it is still unclear whether the cytokine with the largest induction amplitude is the same under different virus infections. It is unknown which is the most critical and whether there are any mathematical formulas that can fit the changing rules of cytokines. Three coronaviruses (SARS-CoV, MERS-CoV, and SARS-CoV-2), three influenza viruses (2009H1N1, H5N1 and H7N9), Ebola virus, human immunodeficiency virus, dengue virus, Zika virus, West Nile virus, hepatitis B virus, hepatitis C virus, and enterovirus 71 were included in this analysis. We retrieved the cytokine fold change (FC), viral load, and clearance rate data from these highly pathogenic virus infections in humans and analyzed the correlations among them. Our analysis showed that interferon-inducible protein (IP)-10, IL-6, IL-8 and IL-17 are the most common cytokines with the largest induction amplitudes. Equations were obtained: the maximum induced cytokine (max) FC = IFN-γ FC × (IFN-γ FC/IL-4 FC) (if IFN-γ FC/IL-4 FC > 1); max FC = IL-4 FC (if IFN-γ FC/IL-4 FC < 1). For IFN-γ-inducible infections, 1.30 × log2 (IFN-γ FC) = log10 (viral load) − 2.48 − 2.83 × (clearance rate). The clinical relevance of cytokines and their antagonists is also discussed. Frontiers Media S.A. 2021-05-17 /pmc/articles/PMC8165266/ /pubmed/34079547 http://dx.doi.org/10.3389/fimmu.2021.659419 Text en Copyright © 2021 Yuan, Jiang, Zhang, Fu, Hu and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Yuan, Shu
Jiang, Si-Cong
Zhang, Zhong-Wei
Fu, Yu-Fan
Hu, Jing
Li, Zi-Lin
Quantification of Cytokine Storms During Virus Infections
title Quantification of Cytokine Storms During Virus Infections
title_full Quantification of Cytokine Storms During Virus Infections
title_fullStr Quantification of Cytokine Storms During Virus Infections
title_full_unstemmed Quantification of Cytokine Storms During Virus Infections
title_short Quantification of Cytokine Storms During Virus Infections
title_sort quantification of cytokine storms during virus infections
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165266/
https://www.ncbi.nlm.nih.gov/pubmed/34079547
http://dx.doi.org/10.3389/fimmu.2021.659419
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