Use of Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Analysis of Serum Peptidome to Classify and Predict Coronavirus Disease 2019 Severity
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Abstract
Background
Classification and early detection of severe coronavirus disease 2019 (COVID-19) patients is required to establish an effective treatment. We tested the utility of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) to classify and predict the severity of COVID-19.
Methods
We used MALDI-TOF MS to analyze the serum peptidome from 72 patients with COVID-19 (training cohort), clinically classified as mild (28), severe (23), and critical (21), and 20 healthy controls. The resulting matrix of peak intensities was used for Machine Learning (ML) approaches to classify and predict COVID-19 severity of 22 independent patients (validation cohort). Finally, we analyzed all sera by liquid chromatography mass spectrometry (LC-MS/MS) to identify the most relevant proteins associated with disease severity.
Results
We found a clear variability of the serum peptidome profile depending on COVID-19 severity. Forty-two peaks exhibited a log fold change ≥1 and 17 were significantly different and at least 4-fold more intense in the set of critical patients than in the mild ones. The ML approach classified clinical stable patients according to their severity with 100% accuracy and correctly predicted the evolution of the nonstable patients in all cases. The LC-MS/MS identified 5 proteins that were significantly upregulated in the critical patients. They included the serum amyloid protein A2, which probably yielded the most intense peak detected by MALDI-TOF MS.
Conclusions
We demonstrate the potential of the MALDI-TOF MS as a bench to bedside technology to aid clinicians in their decision making regarding patients with COVID-19.
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SciScore for 10.1101/2020.10.30.20223057: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: All human samples were taken after written consent of the participants.
IRB: They were informed of the purposes of the study, which was approved by the Ethics Review Board of the Illes Balears (CEI).Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Liquid chromatography-mass data processing: The resultant mass spectrometric data were analysed using Proteome Discoverer (Version 2.2.0.388, Thermo Fisher Scientific) using a protein database composed of the Homo sapiens fasta database downloaded from UniProtKB on 12 Jul 2020, … SciScore for 10.1101/2020.10.30.20223057: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: All human samples were taken after written consent of the participants.
IRB: They were informed of the purposes of the study, which was approved by the Ethics Review Board of the Illes Balears (CEI).Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Liquid chromatography-mass data processing: The resultant mass spectrometric data were analysed using Proteome Discoverer (Version 2.2.0.388, Thermo Fisher Scientific) using a protein database composed of the Homo sapiens fasta database downloaded from UniProtKB on 12 Jul 2020, containing 20,304 reviewed protein sequences, and the SARS-CoV-2 virus fasta downloaded from UniProtKB on 20 May 2020, containing 13 protein sequences. Proteome Discoverersuggested: (Proteome Discoverer, RRID:SCR_014477)UniProtKBsuggested: (UniProtKB, RRID:SCR_004426)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:One of the potential limitations of our study is that due to the rapid response required in the initial stages of the pandemic situation, we collected samples from the patients that were admitted in our hospital using as unique criteria that they were hospitalized due to a SARS-CoV-2 infection. Therefore our study did not take in account some confounding factors, like age. Nonetheless, the change of the intensity of the peaks between groups substantially exceeded the variability observed within each group with ages ranging from 33 to 89, suggesting that differences in the peptidomes profiles of different groups are poorly influenced by confounding factors. Two of the most intense peaks detected in the sera from critical patients had m/z of 11,530 and 11,686 that might correspond to two different isoforms of the serum amyloid A protein (11). This acute phase markers, induced by the proinflammatory cytokine IL-6, were two of the predominant proteins detected by both Shen et al and Messner et al in their respective studies (4,5). As in our study, they also detected CRP, LBP and FGG as clear protein biomarkers for COVID-19 severity. In conclusion, our study supports the potential of the MALDI-TOF MS as a fast and clinically available technology to aid clinicians in their decisions on COVID-19 patients and identifies serum amyloid protein A2 as an excellent biomarker to monitor COVID-19 patients.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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