The COVID-19 pandemic is a global public health crisis. However, little is known about the pathogenesis and biomarkers of COVID-19. Herein, we profiled host responses to COVID-19 by performing plasma proteomics of a cohort of COVID-19 patients including non-survivors and survivors recovered from mild or severe symptoms, and uncovered numerous COVID-19-associated alterations of plasma proteins. We developed a machine learning-based pipeline to identify 11 proteins as biomarkers and a set of biomarker combinations, which were validated by an independent cohort and accurately distinguished and predicted COVID-19 outcomes. Some of the biomarkers were further validated by ELISA using a larger cohort. These markedly altered proteins, including the biomarkers mediate pathophysiological pathways such as immune or inflammatory responses, platelet degranulation and coagulation, and metabolism, that likely contribute to the pathogenesis. Our findings provide valuable knowledge about COVID-19 biomarkers, and shed light on the pathogenesis and potential therapeutic targets of COVID-19.

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