Severe COVID-19 patients account for most of the mortality of this disease. Early detection and effective treatment of severe patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model correctly classified severe patients with an accuracy of 93.5%, and was further validated using ten independent patients, seven of which were correctly classified. We identified molecular changes in the sera of COVID-19 patients implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study shows that it is possible to predict progression to severe COVID-19 disease using serum protein and metabolite biomarkers. Our data also uncovered molecular pathophysiology of COVID-19 with potential for developing anti-viral therapies.
Funding: This work is supported by grants from Westlake Special Program for COVID19 (2020), and Tencent foundation (2020), National Natural Science Foundation of China (81972492, 21904107, 81672086), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Hangzhou Agriculture and Society Advancement Program (20190101A04).
Conflict of Interest: The research group of T.G. is partly supported by Tencent, Thermo Fisher Scientific, SCIEX and Pressure Biosciences Inc. C.Z., Z.K., Z.K. and S.Q. are employees of DIAN Diagnostics.
Shen, Bo and Yi, Xiao and Sun, Yaoting and Bi, Xiaojie and Du, Juping and Zhang, Chao and Quan, Sheng and Zhang, Fangfei and Sun, Rui and Qian, Liujia and Ge, Weigang and Liu, Wei and Liang, Shuang and Chen, Hao and Zhang, Ying and Li, Jun and Xu, Jiaqin and He, Zebao and Chen, Baofu and Wang, Jing and Yan, Haixi and Zheng, Yufen and Wang, Donglian and Zhu, Jiansheng and Kong, Ziqing and Kang, Zhouyang and Liang, Xiao and Ding, Xuan and Ruan, Guan and Xiang, Nan and Cai, Xue and Gao, Huanhuan and Li, Lu and Li, Sainan and Xiao, Qi and Lu, Tian and Zhu, Yi and Liu, Huafen and Chen, Haixiao and Guo, Tiannan, Proteomic and Metabolomic Characterization of COVID-19 Patient Sera. Available at SSRN: https://ssrn.com/abstract=3570565 or http://dx.doi.org/10.2139/ssrn.3570565
This version of the paper has not been formally peer reviewed.
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