Plasma Proteomic Profiling Yields a High-Performance Biomarker Panel for Predicting a Poor Prognosis in Patients with COVID-19

Background The coronavirus disease 2019
(COVID-19)
pandemic increased the demand for reliable tests to predict disease
severity and mortality. Methods In training cohort, we
obtained traditional clinical data and plasma proteomics performed
using the Olink proteomics platform from 52 fatal COVID-19 cases (COVID-19-F),
50 severe COVID-19 cases (COVID-19-S), 55 moderate/mild COVID-19 cases
(COVID-19-M), and 54 healthy controls. Receiver operating characteristic
(ROC) curves and logistic regression were applied to judge the accuracy
of biomarkers to predict in-hospital mortality and build combined
panel. An independent external cohort was used for validation. Results In total, 19 clinical parameters and 92 proteins were
assessed. Traditional clinical indices did not show adequate predictive
value of short-term mortality in severe COVID-19. In proteomics analysis,
75 proteins were differentially expressed among the four groups. Pathway
analysis revealed an imbalance of inflammatory responses and excessive
immunity in COVID-19-F. Subsequently, a novel plasma biomarker panel
(including interleukin 8 and osteoprotegerin) was developed, with
AUC values of 0.791 and 0.781 when comparing COVID-19-F to COVID-19-M
or COVID-19-S, respectively. The predictive power of the panel was
verified in an external cohort. Conclusions Our standardized
assays yielded a prediction panel of mortality during hospitalization
in patients with COVID-19.