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Proteomic and Metabolomic Characterization of COVID-19 Patient Sera
Bo Shen ,
Xiao Yi ,
Yaoting Sun ,
Xiaojie Bi ,
Juping Du ,
Chao Zhang ,
Sheng Quan ,
Fangfei Zhang ,
Rui Sun ,
Liujia Qian ,
Weigang Ge ,
Wei Liu ,
Shuang Liang ,
Hao Chen ,
Ying Zhang ,
Jun Li ,
Jiaqin Xu ,
Zebao He ,
Baofu Chen ,
Jing Wang ,
Haixi Yan ,
Yufen Zheng ,
Donglian Wang ,
Jiansheng Zhu ,
Ziqing Kong ,
Zhouyang Kang ,
Xiao Liang ,
Xuan Ding ,
Guan Ruan ,
Nan Xiang ,
Xue Cai ,
Huanhuan Gao ,
Lu Li ,
Sainan Li ,
Qi Xiao ,
Tian Lu ,
Yi Zhu ,
Huafen Liu ,
Haixiao Chen ,
Tiannan Guo
May 2020
May 2020
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Abstract
Summary
Early detection and effective treatment of severe COVID-19 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 was validated using ten independent patients, seven of which were correctly
classified. Targeted proteomics and metabolomics assays were employed to further validate
this molecular classifier in a second test cohort of 19 new COVID-19 patients, leading
to 16 correct assignments. We identified molecular changes in the sera of COVID-19
patients compared to other groups implicating dysregulation of macrophage, platelet
degranulation and complement system pathways, and massive metabolic suppression. This
study revealed characteristic protein and metabolite changes in the sera of severe
COVID-19 patients, which might be used in selection of potential blood biomarkers
for severity evaluation.