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

https://doi.org/10.1016/j.jaci.2020.04.027Get rights and content

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.

Key words

COVID-19
SARS-CoV-2
biomarkers
disease progression
prediction

Abbreviations used

ARDS
Acute respiratory distress syndrome
AUC
Area under the curve
COVID-19
Coronavirus disease 2019
dao
Days after onset
FiO2
Fraction of inspired oxygen
HGF
Hepatocyte growth factor
IP-10
IFN-γ–induced protein 10
MCP-3
Monocyte chemotactic protein-3
MIG
Monokine-induced gamma IFN
MIP-1α
Macrophage inflammatory protein 1 alpha
MERS-CoV
Middle East respiratory syndrome coronavirus
PaO2
Arterial oxygen partial pressure
ROC
Receiver-operating characteristic
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2

Cited by (0)

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.

These authors contributed equally to this work.

These authors contributed equally to this work.

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