Plasma IP-10 and MCP-3 levels are highly associated with disease severity and predict the progression of COVID-19 - 22/07/20

Doi : 10.1016/j.jaci.2020.04.027

Yang Yang, MD ^a,^{^{∗
These authors contributed equally to this work.}}, Chenguang Shen, PhD ^a,^{^{∗
These authors contributed equally to this work.}}, Jinxiu Li, MD ^a,^{^{∗
These authors contributed equally to this work.}}, Jing Yuan, MD ^a, Jinli Wei, MM ^a, Fengmin Huang, MD ^b, Fuxiang Wang, MD ^a, Guobao Li, MD ^a, Yanjie Li, MM ^a, Li Xing, MM ^a, Ling Peng, MM ^a, Minghui Yang, PhD ^a, Mengli Cao, MM ^a, Haixia Zheng, MM ^a, Weibo Wu, MM ^a, Rongrong Zou, MD ^a, Delin Li, PhD ^a, Zhixiang Xu, MM ^a, Haiyan Wang, PhD ^a, Mingxia Zhang, MM ^a, Zheng Zhang, MD ^a, George F. Gao, DPhil ^c, Chengyu Jiang, PhD ^b,^⁎,^{^{‡
These authors contributed equally to this work.}} , Lei Liu, MD ^a,^⁎,^{^{‡
These authors contributed equally to this work.}} , Yingxia Liu, MD ^a,^⁎,^{^{‡
These authors contributed equally to this work.}}
^a Shenzhen Key Laboratory of Pathogen and Immunity, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People’s Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
^b State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Department of Biochemistry, Peking Union Medical College, Beijing, China
^c CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Science, Beijing, China

^∗Corresponding author: Yingxia Liu, MD, and Lei Liu, MD, Shenzhen Third People’s Hospital, Second Hospital Affiliated to Southern University of Science and Technology, No. 29, Bulan Rd, Longgang District, Shenzhen 518112, China.Shenzhen Third People’s HospitalSecond Hospital Affiliated to Southern University of Science and TechnologyNo. 29Bulan RdLonggang DistrictShenzhen518112China^∗∗Chengyu Jiang, PhD, Chinese Academy of Medical Sciences, Department of Biochemistry, Peking Union Medical College, Beijing, China.Chinese Academy of Medical SciencesDepartment of BiochemistryPeking Union Medical CollegeBeijingChina

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Abstract

Background

The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 was first reported in Wuhan, December 2019, and continuously poses a serious threat to public health, highlighting the urgent need of identifying biomarkers for disease severity and progression.

Objective

We sought to identify biomarkers for disease severity and progression of COVID-19.

Methods

Forty-eight cytokines in the plasma samples from 50 COVID-19 cases including 11 critically ill, 25 severe, and 14 moderate patients were measured and analyzed in combination with clinical data.

Results

Levels of 14 cytokines were found to be significantly elevated in COVID-19 cases and showed different expression profiles in patients with different disease severity. Moreover, expression levels of IFN-γ–induced protein 10, monocyte chemotactic protein-3, hepatocyte growth factor, monokine-induced gamma IFN, and macrophage inflammatory protein 1 alpha, which were shown to be highly associated with disease severity during disease progression, were remarkably higher in critically ill patients, followed by severe and then the moderate patients. Serial detection of the 5 cytokines in 16 cases showed that continuously high levels were associated with deteriorated progression of disease and fatal outcome. Furthermore, IFN-γ–induced protein 10 and monocyte chemotactic protein-3 were excellent predictors for the progression of COVID-19, and the combination of the 2 cytokines showed the biggest area under the curve of the receiver-operating characteristics calculations with a value of 0.99.

Conclusions

In this study, we report biomarkers that are highly associated with disease severity and progression of COVID-19. These findings add to our understanding of the immunopathologic mechanisms of severe acute respiratory syndrome coronavirus 2 infection, and provide potential therapeutic targets and strategies.

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Key words : COVID-19, SARS-CoV-2, biomarkers, disease progression, prediction

Abbreviations used : ARDS, AUC, COVID-19, dao, FiO₂, HGF, IP-10, MCP-3, MIG, MIP-1α, MERS-CoV, PaO₂, ROC, SARS-CoV-2

Mappa

Methods

Patient information and data collection

Disease severity classification

Quantification of hypoxia and Murray score

Measurement of plasma cytokines

Statistical analysis

Results

Epidemiological and clinical characteristics

Differential expression profile of cytokines in patients with different disease severity

IP-10, MCP-3, and IL-1ra are independent predictors for the progression of COVID-19

Expression levels of IP-10, MCP-3, HGF, MIG, MIP-1α and IL-1ra were highly associated with disease severity and progression

Discussion

Conclusions

This study was supported by the National Natural Science Foundation of China (grant nos. 81802004 and 81788101), Ministry of Science and Technology (grant no. 2020YFC0846300), the National Science and Technology Major Project (grant nos. 2018ZX10711001, 2017ZX10204401, and 2017ZX10103011), Shenzhen Science and Technology Research and Development Project (grant nos. JCYJ20180228162201541 and 202002073000001), Sanming Project of Medicine in Shenzhen (grant no. SZSM201512005), and the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (grant no. 2017-I2M-1-009).

Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest.

Esportazione

Vol 146 - N° 1

P. 119 - Luglio 2020 Ritorno al numero

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Plasma IP-10 and MCP-3 levels are highly associated with disease severity and predict the progression of COVID-19 - 22/07/20

Abstract

Background

Objective

Methods

Results

Conclusions

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