Proteomic and Metabolomic Characterization of COVID-19 Patient Sera

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 10 independent patients, 7 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 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, 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.
Graphical Abstract
Highlights • 93 proteins show differential expression in severe COVID-19 patient sera • 204 metabolites in COVID-19 patient sera correlate with disease severity • A model composed of 29 serum factors shows patient stratification potential • Pathway analysis highlights metabolic and immune dysregulation in COVID-19 patients
Proteomic and metabolomic analysis of COVID-19 sera identifies differentially expressed factors that correlate with disease severity and highlights dysregulation of multiple immune and metabolic components in clinically severe patients.