Cytokine Signature Associated With Disease Severity in COVID-19
Copyright © 2021 Guo, Wang, Xia, Shi, Chen, Zheng, Chen, Gao, Guo, Ji, Huang, Luo, Zhang, Zuo, Chen, Xu, Xia, Zhu, Xu, Qiu, Sheng, Xu and Li..
Coronavirus disease 2019 (COVID-19) broke out and then became a global epidemic at the end of 2019. With the increasing number of deaths, early identification of disease severity and interpretation of pathogenesis are very important. Aiming to identify biomarkers for disease severity and progression of COVID-19, 75 COVID-19 patients, 34 healthy controls and 23 patients with pandemic influenza A(H1N1) were recruited in this study. Using liquid chip technology, 48 cytokines and chemokines were examined, among which 33 were significantly elevated in COVID-19 patients compared with healthy controls. HGF and IL-1β were strongly associated with APACHE II score in the first week after disease onset. IP-10, HGF and IL-10 were correlated positively with virus titers. Cytokines were significantly correlated with creatinine, troponin I, international normalized ratio and procalcitonin within two weeks after disease onset. Univariate analyses were carried out, and 6 cytokines including G-CSF, HGF, IL-10, IL-18, M-CSF and SCGF-β were found to be associated with the severity of COVID-19. 11 kinds of cytokines could predict the severity of COVID-19, among which IP-10 and M-CSF were excellent predictors for disease severity. In conclusion, the levels of cytokines in COVID-19 were significantly correlated with the severity of the disease in the early stage, and serum cytokines could be used as warning indicators of the severity and progression of COVID-19. Early stratification of disease and intervention to reduce hypercytokinaemia may improve the prognosis of COVID-19 patients.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
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| Enthalten in: |
Frontiers in immunology - 12(2021) vom: 06., Seite 681516 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Guo, Jing [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarker |
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| Anmerkungen: |
Date Completed 15.09.2021 Date Revised 03.04.2024 published: Electronic-eCollection Citation Status MEDLINE |
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| doi: |
10.3389/fimmu.2021.681516 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM330323156 |
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| 520 | |a Copyright © 2021 Guo, Wang, Xia, Shi, Chen, Zheng, Chen, Gao, Guo, Ji, Huang, Luo, Zhang, Zuo, Chen, Xu, Xia, Zhu, Xu, Qiu, Sheng, Xu and Li. | ||
| 520 | |a Coronavirus disease 2019 (COVID-19) broke out and then became a global epidemic at the end of 2019. With the increasing number of deaths, early identification of disease severity and interpretation of pathogenesis are very important. Aiming to identify biomarkers for disease severity and progression of COVID-19, 75 COVID-19 patients, 34 healthy controls and 23 patients with pandemic influenza A(H1N1) were recruited in this study. Using liquid chip technology, 48 cytokines and chemokines were examined, among which 33 were significantly elevated in COVID-19 patients compared with healthy controls. HGF and IL-1β were strongly associated with APACHE II score in the first week after disease onset. IP-10, HGF and IL-10 were correlated positively with virus titers. Cytokines were significantly correlated with creatinine, troponin I, international normalized ratio and procalcitonin within two weeks after disease onset. Univariate analyses were carried out, and 6 cytokines including G-CSF, HGF, IL-10, IL-18, M-CSF and SCGF-β were found to be associated with the severity of COVID-19. 11 kinds of cytokines could predict the severity of COVID-19, among which IP-10 and M-CSF were excellent predictors for disease severity. In conclusion, the levels of cytokines in COVID-19 were significantly correlated with the severity of the disease in the early stage, and serum cytokines could be used as warning indicators of the severity and progression of COVID-19. Early stratification of disease and intervention to reduce hypercytokinaemia may improve the prognosis of COVID-19 patients | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Chen, Yu |e verfasserin |4 aut | |
| 700 | 1 | |a Zheng, Shufa |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Yanfei |e verfasserin |4 aut | |
| 700 | 1 | |a Gao, Hainv |e verfasserin |4 aut | |
| 700 | 1 | |a Guo, Feifei |e verfasserin |4 aut | |
| 700 | 1 | |a Ji, Zhongkang |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Chenjie |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Rui |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Zuo, Jian |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Yunbo |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Xia, Jiafeng |e verfasserin |4 aut | |
| 700 | 1 | |a Zhu, Chunxia |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Xiaowei |e verfasserin |4 aut | |
| 700 | 1 | |a Qiu, Yunqing |e verfasserin |4 aut | |
| 700 | 1 | |a Sheng, Jifang |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Kaijin |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Lanjuan |e verfasserin |4 aut | |
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