Prognostic accuracy of MALDI mass spectrometric analysis of plasma in COVID-19

Purpose: SARS-CoV-2 infection poses a global public health problem. There is a critical need for improvements in the noninvasive prognosis of COVID-19. We hypothesized that matrix-assisted laser desorption ionization mass spectrometry (MALDI-TOF MS) analysis combined with bottom-up proteomic analysis of plasma proteins might identify features to predict high and low risk cases of COVID-19. Patients and Methods: We used MALDI-TOF MS to analyze plasma small proteins and peptides isolated using C18 micro-columns from a cohort containing a total of 117 cases of high (hospitalized) and low risk (outpatients) cases split into training (n = 88) and validation sets (n= 29). The plasma protein/peptide fingerprint obtained was used to train the algorithm before validation using a blinded test cohort. Results: Several sample preparation, MS and data analysis parameters were optimized to achieve an overall accuracy of 85%, sensitivity of 90%, and specificity of 81% in the training set. In the blinded test set, this signature reached an overall accuracy of 93.1%, sensitivity of 87.5%, and specificity of 100%. From this signature, we identified two distinct regions in the MALDI-TOF profile belonging to the same proteoforms. A combination of 1D 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. Conclusions: We found a plasma proteomic profile that discriminates against patients with high and low risk COVID-19. Proteomic analysis of C18-fractionated plasma may have a role in the noninvasive prognosis of COVID-19. Further validation will consolidate its clinical utility.