Abstract
The outbreak of the 2019-nCoV infection began in December 2019 in Wuhan, Hubei province, and rapidly spread to many provinces in China as well as other countries. Here we report the epidemiological, clinical, laboratory, and radiological characteristics, as well as potential biomarkers for predicting disease severity in 2019-nCoV-infected patients in Shenzhen, China. All 12 cases of the 2019-nCoV-infected patients developed pneumonia and half of them developed acute respiratory distress syndrome (ARDS). The most common laboratory abnormalities were hypoalbuminemia, lymphopenia, decreased percentage of lymphocytes (LYM) and neutrophils (NEU), elevated C-reactive protein (CRP) and lactate dehydrogenase (LDH), and decreased CD8 count. The viral load of 2019-nCoV detected from patient respiratory tracts was positively linked to lung disease severity. ALB, LYM, LYM (%), LDH, NEU (%), and CRP were highly correlated to the acute lung injury. Age, viral load, lung injury score, and blood biochemistry indexes, albumin (ALB), CRP, LDH, LYM (%), LYM, and NEU (%), may be predictors of disease severity. Moreover, the Angiotensin II level in the plasma sample from 2019-nCoV infected patients was markedly elevated and linearly associated to viral load and lung injury. Our results suggest a number of potential diagnosis biomarkers and angiotensin receptor blocker (ARB) drugs for potential repurposing treatment of 2019-nCoV infection.
Electronic Supplementary Material
Supplementary material is available for this article at 10.1007/s11427-020-1643-8 and is accessible for authorized users.
Keywords: 2019-nCoV, Angiotensin II, ARDS
Electronic supplementary material
Acknowledgements
The authors would like to thank a scientist who insists on being anonymous. The authors would also like to thank Shunwang Li and Xiaoyun Li who helped data analysis and making figures and tables. This work was supported by the National Science and Technology Major Project (2017ZX10103011 and 2017ZX10204401), Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2017-I2M-1-009), Shenzhen Science and Technology Research and Development Project (JCYJ20180504165549581 and JCYJ20170413141236903), China Postdoctoral Science Foundation (2019T120147).
Compliance and ethics The author(s) declare that they have no conflict of interest.
Footnotes
Contributed equally to this work
Contributor Information
Yingxia Liu, Email: yingxialiu@hotmail.com.
Chengyu Jiang, Email: jiang@pumc.edu.cn.
Lei Liu, Email: liulei3322@aliyun.com.
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