COVID-19 complications still present a huge burden on healthcare systems and warrant predictive risk models to triage patients and inform early intervention. Here, we profile 893 plasma proteins from 50 severe and 50 mild-moderate COVID-19 patients, and 50 healthy controls, and show that 375 proteins are differentially expressed in the plasma of severe COVID-19 patients. These differentially expressed plasma proteins are implicated in the pathogenesis of COVID-19 and present targets for candidate drugs to prevent or treat severe complications. Based on the plasma proteomics and clinical lab tests, we also report a 12-plasma protein signature and a model of seven routine clinical tests that validate in an independent cohort as early risk predictors of COVID-19 severity and patient survival. The risk predictors and candidate drugs described in our study can be used and developed for personalized management of SARS-CoV-2 infected patients.
COVID-19 complications present a huge burden on healthcare systems and warrant a predictive risk model for disease severity of SARS-CoV-2 infection to enable early intervention, prospective decision-making and triaging of patients. We profiled plasma proteins from COVID-19 patients (severe n=50, and mild n=50) and controls (n=50) using function- and pathway-based panels developed with the highly specific proximity extension assays. Several biological pathways were specific for patients with severe complications. Based on these dysregulated profiles, we propose candidate FDA-approved drugs that target multiple upregulated proteins to treat severe complications. In addition, the set of differentially expressed plasma proteins in severe disease contained a robust 46-protein signature, the COVID-19 molecular severity score, which predicts the risk of severe complications. We cross-validated this molecular severity score in an independent cohort and found it useful within three days after hospital admission to predict COVID-19 severity and outcomes. Associated with the molecular severity score, we identified a set of clinical parameters available at admission, that act as a clinical risk score for complications. The molecular and clinical risk scores described in our study may be prognostic tools for severe COVID-19 disease and help alleviate the pressure on healthcare systems during infection peaks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.