Institution: | 1. Segal Cancer Proteomics Centre, Lady Davis Institute for Medical Research, McGill University, Montreal, Quebec, Canada;2. MRM Proteomics, Montreal, Canada;3. Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia;4. Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands;5. Genome BC Proteomics Centre, University of Victoria, Victoria, Canada;6. Manitoba Centre for Proteomics & Systems Biology, John Buhler Research Centre, University of Manitoba, Winnipeg, Canada;7. Department of Internal Medicine, University of Manitoba, Winnipeg, Canada;8. Gerald Bronfman Department of Oncology, Division of Experimental Medicine, Lady Davis Institute for Medical Research, McGill University, Montreal, Canada;9. Department of Pathology, McGill University, Montreal, Canada |
Abstract: | The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors’ samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients. |