An altered metabolism in leukocytes showing in vitro igG memory from SARS-CoV-2-infected patients

  1. G. Fanelli
  2. F. Gevi
  3. G. Zarletti
  4. M. Tiberi
  5. V. De Molfetta
  6. G. Scapigliati
  7. A.M. Timperio

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Abstract

Coronavirus disease 2019 (COVID 19) is a systemic infection that exerts a significant impact on cell metabolism. In this study we performed metabolomic profiling coupled with multivariate statistics analysis obtained from 43 in vitro cultures of peripheral blood mononuclear cells (PBMC), 19 of which displaying IgG memory for spike-S1 antigen 60-90 days after infection. By using mass spectrometry analysis, a significant up regulation of S-adenosyl-Homocysteine, Sarcosine and Arginine was found in leukocytes showing IgG memory. These metabolites are known to be involved in physiological recovering from viral infections and immune activities, and our findings might represent a novel and easy measure that could be of help in understanding SARS-Cov-2 effects on leukocytes.

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    SciScore for 10.1101/2021.05.27.445918: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsConsent: All participants provided informed written consent to participate in the research project, and the study was approved by the Regional Ethical Board in Ospedale L.
    IRB: All participants provided informed written consent to participate in the research project, and the study was approved by the Regional Ethical Board in Ospedale L.
    Sex as a biological variable43 subjects (24 males and 19 females, dataset) undergoing COVID-19 serological analysis (Centro Polispecialistico Giovanni Paolo I, Viterbo, I) were enrolled in this study from October 2020 to March 2021.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Replicates were exported as.mzXML files and processed through MAVEN.5.2. Multivariate (PLS-DA) and Univariate (Volcano plot) statistical analyses were performed on the entire metabolomics data set using the MetaboAnalyst 5.0 software.
    MetaboAnalyst
    suggested: (MetaboAnalyst, RRID:SCR_015539)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.05.27.445918v1 on bioRxiv