Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors

Huan Han, Qingfeng Ma, Cong Li, Rui Liu, Li Zhao, Wei Wang, Pingan Zhang, Xinghui Liu, Guosheng Gao, Fang Liu, Yingan Jiang, Xiaoming Cheng, Chengliang Zhu, Yuchen Xia, Huan Han, Qingfeng Ma, Cong Li, Rui Liu, Li Zhao, Wei Wang, Pingan Zhang, Xinghui Liu, Guosheng Gao, Fang Liu, Yingan Jiang, Xiaoming Cheng, Chengliang Zhu, Yuchen Xia

Abstract

Since the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, it has rapidly spread across many other countries. While the majority of patients were considered mild, critically ill patients involving respiratory failure and multiple organ dysfunction syndrome are not uncommon, which could result death. We hypothesized that cytokine storm is associated with severe outcome. We enrolled 102 COVID-19 patients who were admitted to Renmin Hospital (Wuhan, China). All patients were classified into moderate, severe and critical groups according to their symptoms. 45 control samples of healthy volunteers were also included. Inflammatory cytokines and C-Reactive Protein (CRP) profiles of serum samples were analyzed by specific immunoassays. Results showed that COVID-19 patients have higher serum level of cytokines (TNF-α, IFN-γ, IL-2, IL-4, IL-6 and IL-10) and CRP than control individuals. Within COVID-19 patients, serum IL-6 and IL-10 levels are significantly higher in critical group (n = 17) than in moderate (n = 42) and severe (n = 43) group. The levels of IL-10 is positively correlated with CRP amount (r = 0.41, P < 0.01). Using univariate logistic regression analysis, IL-6 and IL-10 are found to be predictive of disease severity and receiver operating curve analysis could further confirm this result (AUC = 0.841, 0.822 respectively). Our result indicated higher levels of cytokine storm is associated with more severe disease development. Among them, IL-6 and IL-10 can be used as predictors for fast diagnosis of patients with higher risk of disease deterioration. Given the high levels of cytokines induced by SARS-CoV-2, treatment to reduce inflammation-related lung damage is critical.

Keywords: COVID-19; Interleukin 10; Interleukin 6; SARS-CoV-2; cytokine storm; inflammatory cytokines.

Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
The levels of cytokines in COVID-19 patients and controls. The serum concentration of TNF-α, IFN-γ, IL-2, IL-4, IL-6 and IL-10 from 102 COVID-19 patients and 42 controls were analyzed immediately after hospital admission. Median with range were presented.
Figure 1.
Figure 1.
The levels of cytokines in COVID-19 patients and controls. The serum concentration of TNF-α, IFN-γ, IL-2, IL-4, IL-6 and IL-10 from 102 COVID-19 patients and 42 controls were analyzed immediately after hospital admission. Median with range were presented.
Figure 2.
Figure 2.
The levels of cytokines in COVID-19 patients with different severity. 102 COVID-19 patients were divided into three groups: moderate, severe and critical. The serum concentration of TNF-α, IFN-γ, IL-2, IL-4, IL-6 and IL-10 were analyzed. Median with range were presented.
Figure 2.
Figure 2.
The levels of cytokines in COVID-19 patients with different severity. 102 COVID-19 patients were divided into three groups: moderate, severe and critical. The serum concentration of TNF-α, IFN-γ, IL-2, IL-4, IL-6 and IL-10 were analyzed. Median with range were presented.
Figure 3.
Figure 3.
The kinetics of cytokines and CRP in COVID-19 patients during hospitalization. The serum cytokines levels and CRP of moderate, severe and critical patients during hospitalization were presented. The x-axis represents days after admission. Median with range were presented.
Figure 3.
Figure 3.
The kinetics of cytokines and CRP in COVID-19 patients during hospitalization. The serum cytokines levels and CRP of moderate, severe and critical patients during hospitalization were presented. The x-axis represents days after admission. Median with range were presented.
Figure 4.
Figure 4.
The relationship between CRP and IL-10. Spearman rank correlation analysis was performed to evaluate the correlation of serum IL-10with CRP in the patients with COVID-19.
Figure 4.
Figure 4.
The relationship between CRP and IL-10. Spearman rank correlation analysis was performed to evaluate the correlation of serum IL-10with CRP in the patients with COVID-19.
Figure 5.
Figure 5.
ROC curve of cytokines and CRP. Univariate logistic regression analysis was conducted. Performance of ROC curves of TNF-α, IFN-γ, IL-2, IL-4, IL-6, IL-10 and CRP for predicting COVID-19.
Figure 5.
Figure 5.
ROC curve of cytokines and CRP. Univariate logistic regression analysis was conducted. Performance of ROC curves of TNF-α, IFN-γ, IL-2, IL-4, IL-6, IL-10 and CRP for predicting COVID-19.
Figure 6.
Figure 6.
ROC curve for diagnosis of severe and critical patients with COVID-19. Univariate logistic regression analysis was used to identify the severe and critical patients from controls and moderate COVID-19 patients. Performance of ROC curves of TNF-α, IFN-γ, IL-2, IL-4, IL-6, IL-10 and CRP for predicting severe and critical COVID-19 patients.
Figure 6.
Figure 6.
ROC curve for diagnosis of severe and critical patients with COVID-19. Univariate logistic regression analysis was used to identify the severe and critical patients from controls and moderate COVID-19 patients. Performance of ROC curves of TNF-α, IFN-γ, IL-2, IL-4, IL-6, IL-10 and CRP for predicting severe and critical COVID-19 patients.
Figure 7.
Figure 7.
ROC curve for diagnosis of severe and critical patients with COVID-19. Univariate logistic regression analysis was used to identify the critical patients from moderate, severe COVID-19 patients and controls. Performance of ROC curves of TNF-α, IFN-γ, IL-2, IL-4, IL-6, IL-10 and CRP for predicting critical COVID-19 patients.
Figure 7.
Figure 7.
ROC curve for diagnosis of severe and critical patients with COVID-19. Univariate logistic regression analysis was used to identify the critical patients from moderate, severe COVID-19 patients and controls. Performance of ROC curves of TNF-α, IFN-γ, IL-2, IL-4, IL-6, IL-10 and CRP for predicting critical COVID-19 patients.

References

    1. Yang X, Yu Y, Xu J, et al. . Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020 Feb 24. doi:10.1016/s2213-2600(20)30079-5.
    1. Xu Z, Shi L, Wang Y, et al. . Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020 Feb 18. doi:10.1016/s2213-2600(20)30076-x.
    1. Tetro JA. Is COVID-19 receiving ADE from other coronaviruses? Microbes Infect. 2020 Feb 22. doi:10.1016/j.micinf.2020.02.006.
    1. Gu Y, Hsu AC, Pang Z, et al. . Role of the innate cytokine storm induced by the influenza A virus. Viral Immunol. 2019 Jul/Aug;32(6):244–251. doi:10.1089/vim.2019.0032.
    1. Ferrero-Miliani L, Nielsen OH, Andersen PS, et al. . Chronic inflammation: importance of NOD2 and NALP3 in interleukin-1beta generation. Clin Exp Immunol. 2007 Feb;147(2):227–235. doi:10.1111/j.1365-2249.2006.03261.x.
    1. Takeuchi O, Akira S.. Innate immunity to virus infection. Immunol Rev. 2009 Jan;227(1):75–86. doi:10.1111/j.1600-065X.2008.00737.x.
    1. Lin L, Li TS.. Interpretation of “guidelines for the diagnosis and treatment of novel coronavirus (2019-nCoV) infection by the National Health Commission (Trial Version 5)”. Zhonghua Yi Xue Za Zhi. 2020 Feb 7;100(0):E001. doi:10.3760/cma.j.issn.0376-2491.2020.0001.
    1. Zu ZY, Jiang MD, Xu PP, et al. . Coronavirus disease 2019 (COVID-19): a perspective from China. Radiology. 2020 Feb 21:200490. doi:10.1148/radiol.2020200490.
    1. Jin YH, Cai L, Cheng ZS, et al. . A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Mil Med Res. 2020 Feb 6;7(1):4. doi:10.1186/s40779-020-0233-6.
    1. Diagnosis and clinical management of 2019 novel coronavirus infection: an operational recommendation of Peking Union Medical College Hospital (V2.0). Zhonghua Nei Ke Za Zhi. 2020 Feb 4;59(3):186–188. doi:10.3760/cma.j.issn.0578-1426.2020.03.003.
    1. Wang D, Hu B, Hu C, et al. . Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-Infected pneumonia in Wuhan, China. JAMA. 2020 Feb 7. doi:10.1001/jama.2020.1585.
    1. Zhang J, Zhou L, Yang Y, et al. . Therapeutic and triage strategies for 2019 novel coronavirus disease in fever clinics. Lancet Respir Med. 2020 Mar;8(3):e11–e12. doi:10.1016/s2213-2600(20)30071-0.
    1. Chen L, Liu HG, Liu W, et al. . Analysis of clinical features of 29 patients with 2019 novel coronavirus pneumonia. Zhonghua Jie He He Hu Xi Za Zhi. 2020 Feb 6;43(0):E005. doi:10.3760/cma.j.issn.1001-0939.2020.0005.
    1. Liu Y, Yang Y, Zhang C, et al. . Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung injury. Sci China Life Sci. 2020 Mar;63(3):364–374. doi:10.1007/s11427-020-1643-8.
    1. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Zhonghua Liu Xing Bing Xue Za Zhi. 2020 Feb 17;41(2):145–151. doi:10.3760/cma.j.issn.0254-6450.2020.02.003.
    1. Huang C, Wang Y, Li X, et al. . Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020 Feb 15;395(10223):497–506. doi:10.1016/s0140-6736(20)30183-5.
    1. Hui DSC, Zumla A.. Severe acute respiratory syndrome: historical, epidemiologic, and clinical features. Infect Dis Clin North Am. 2019 Dec;33(4):869–889. doi:10.1016/j.idc.2019.07.001.
    1. Azhar EI, Hui DSC, Memish ZA, et al. . The Middle East respiratory syndrome (MERS). Infect Dis Clin North Am. 2019 Dec;33(4):891–905. doi:10.1016/j.idc.2019.08.001.
    1. Li G, Fan Y, Lai Y, et al. . Coronavirus infections and immune responses. J Med Virol. 2020 Apr;92(4):424–432. doi:10.1002/jmv.25685.
    1. Gadient RA, Patterson PH.. Leukemia inhibitory factor, Interleukin 6, and other cytokines using the GP130 transducing receptor: roles in inflammation and injury. Stem Cells. 1999;17(3):127–137. doi:10.1002/stem.170127.
    1. McKinstry KK, Strutt TM, Buck A, et al. . IL-10 deficiency unleashes an influenza-specific Th17 response and enhances survival against high-dose challenge. J Immunol. 2009 Jun 15;182(12):7353–7363. doi:10.4049/jimmunol.0900657.
    1. Fattori E, Cappelletti M, Costa P, et al. . Defective inflammatory response in interleukin 6-deficient mice. J Exp Med. 1994 Oct 1;180(4):1243–1250. doi:10.1084/jem.180.4.1243.
    1. Stuber F, Wrigge H, Schroeder S, et al. . Kinetic and reversibility of mechanical ventilation-associated pulmonary and systemic inflammatory response in patients with acute lung injury. Intensive Care Med. 2002 Jul;28(7):834–841. doi:10.1007/s00134-002-1321-7.
    1. Parsons PE, Eisner MD, Thompson BT, et al. . Lower tidal volume ventilation and plasma cytokine markers of inflammation in patients with acute lung injury. Crit Care Med. 2005 Jan;33(1):1–6; discussion 230-2. doi:10.1097/01.ccm.0000149854.61192.dc.
    1. Kim GW, Lee NR, Pi RH, et al. . IL-6 inhibitors for treatment of rheumatoid arthritis: past, present, and future. Arch Pharm Res. 2015;38(5):575–584. doi:10.1007/s12272-015-0569-8.
    1. Kotch C, Barrett D, Teachey DT.. Tocilizumab for the treatment of chimeric antigen receptor T cell-induced cytokine release syndrome. Expert Rev Clin Immunol. 2019 Aug;15(8):813–822. doi:10.1080/1744666x.2019.1629904.

Source: PubMed

Sponsorzy i współpracownicy

Warunki medyczne

Interwencje lekowe

3
Subskrybuj