High mortality rate in SARS-CoV-2–infected individuals requires accurate markers for predicting COVID-19 severity. MALDI-TOF analysis revealed differential plasma levels of SAA1 and SAA2 associated with higher risk of hospitalization and can be used to improve COVID-19 monitoring and therapy. SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that predict high (hospitalized) and low-risk (outpatients) cases of COVID-19 identified by a platform that combines machine learning with matrix-assisted laser desorption ionization mass spectrometry analysis. Sample preparation, MS, and data analysis parameters were optimized to achieve an overall accuracy of 92%, sensitivity of 93%, and specificity of 92% in dataset without feature selection. We identified two distinct regions in the MALDI-TOF profile belonging to the same proteoforms. A combination of SDS–PAGE and quantitative bottom-up proteomic analysis allowed the identification of intact and truncated forms of serum amyloid A-1 and A-2 proteins, both already described as biomarkers for viral infections in the acute phase. Unbiased discrimination of high- and low-risk COVID-19 patients using a technology that is currently in clinical use may have a prompt application in the noninvasive prognosis of COVID-19. Further validation will consolidate its clinical utility.
【초록키워드】 COVID-19, viral infection, mass spectrometry, therapy, Biomarker, Biomarkers, Hospitalized, Prognosis, Hospitalization, SARS-COV-2 infection, COVID-19 severity, Proteins, viral infections, Health crisis, sensitivity, specificity, Region, Health, Viral, Accuracy, therapeutic, Data analysis, plasma, dataset, outpatients, proteome, mortality rate, Quantitative, Critical, predict, platform, proteomic, Feature selection, marker, Combination, Analysis, Plasma levels, COVID-19 patient, noninvasive, Clinical use, higher risk, acute phase, individual, serum amyloid, effort, clinical utility, high mortality rate, parameter, Saa1, SAA2, SDS–PAGE, IMPROVE, described, identify, Sample, form, can be used, 【제목키워드】 COVID-19, Accuracy, plasma, Analysis,