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. What is the key question? Do individuals infected with SARS-CoV-2 harboring different degree of disease severity have a plasma protein profile that differentiate them and predict the COVID-19 outcome? What is the bottom line? In a series of 117 patients with COVID-19 divided in hospitalized (60) and outpatients (57), differential expression of serum amyloid A-1 (SAA1) and A-2 (SAA2) predict their outcome. Why read on? The high mortality rate in SARS-CoV-2 infected individuals requires accurate markers for predicting COVID-19 severity. Plasma levels of SAA1 and SAA2 indicate higher risk of hospitalization and can be used to improve COVID-19 monitoring and therapy. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by FAPESP, GP (2018/18257-1, 2018/15549-1, 2020/04923-0), CW (2015/26722-8, 2017/03966-4), CRFM (2018/20468-0) and JCN (2020/04705-2). GP, CW, and CRFM were supported by CNPq. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Plasma from a total of 117 patients with COVID-19 divided into high risk (n = 57) and low risk (n = 60) was collected prospectively from a Brazilian cohort at the Heart Institute (InCor) and Central Institute, University of Sao Paulo Medical School, Brazil, between March 2020 to July 2020. The study was appproved by the COMISSAO NACIONAL DE ETICA EM PESQUISA (CAAE 30299620.7.0000.0068 ). All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Raw data were submitted to PRIDE (), project number PXD021581. * (ACN) : Acetonitrile (HCCA) : Alpha-cyano-hydroxycinnamic acid (AUC) : Area under curve (CV) : Coefficient of variance (COVID-19) : Coronavirus disease 2019 (CRP) : C-reactive protein (DHB) : Dihydroxybenzoic acid (EDTA) : Ethylenediamine tetra acetic acid (IQR) : Interquartile range (MALDI-TOF MS) : Matrix-assisted laser desorption ionization mass spectrometry (PR) : Precision-recall curve (ROC) : Receiver operating characteristic curve (SAA) : Serum amyloid A1/A2 (SA) : Sinapinic acid (SDS-PAGE) : Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (TFA) : Trifluoroacetic acid