Abstract
Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.
Funder
Deutsche Forschungsgemeinschaft
German Ministry of Education and Research
Berlin Institute of Health
Wellcome Trust
MRC University Unit Programme Grant
Alzheimer's Disease Research UK project grant
Medical Research Council grant
Medical Research Council
Ministry of Science and Higher Education
Austrian Science Fund
Austrian Research Promotion Agency
BMBF/DLR
Berlin University Alliance
UK Coronavirus Immunology Consortium
Charité-BIH Centrum für Therapieforschung
BBSRC
Cancer Research UK
UK Medical Research Council
BMBF-MSCoresys
BMBF
Chief Scientist Office of the Scottish Government Health Directorates
Scottish Funding Council
National Institute for Health Research
BIH-Charité Digital Clinician Scientist Program
Bundesministerium für Bildung und Forschung
Publisher
Public Library of Science (PLoS)