Proteomic and metabolomic characterization of COVID-19 patient sera
Autor
Shen, Bo
Yi, Xiao
Sun, Yaoting
Liu, Huafen
Chen, Haixiao
Guo, Tiannan
Institución
Resumen
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.