Metabolomics and computational analysis of the role of monoamine oxidase activity in delirium and SARS-COV-2 infection

  1. Miroslava Cuperlovic-Culf
  2. Emma L. Cunningham
  3. Hossen Teimoorinia
  4. Anuradha Surendra
  5. Xiaobei Pan
  6. Steffany A. L. Bennett
  7. Mijin Jung
  8. Bernadette McGuiness
  9. Anthony Peter Passmore
  10. David Beverland
  11. Brian D. Green

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Abstract

Delirium is an acute change in attention and cognition occurring in ~ 65% of severe SARS-CoV-2 cases. It is also common following surgery and an indicator of brain vulnerability and risk for the development of dementia. In this work we analyzed the underlying role of metabolism in delirium-susceptibility in the postoperative setting using metabolomic profiling of cerebrospinal fluid and blood taken from the same patients prior to planned orthopaedic surgery. Distance correlation analysis and Random Forest (RF) feature selection were used to determine changes in metabolic networks. We found significant concentration differences in several amino acids, acylcarnitines and polyamines linking delirium-prone patients to known factors in Alzheimer’s disease such as monoamine oxidase B (MAOB) protein. Subsequent computational structural comparison between MAOB and angiotensin converting enzyme 2 as well as protein–protein docking analysis showed that there potentially is strong binding of SARS-CoV-2 spike protein to MAOB. The possibility that SARS-CoV-2 influences MAOB activity leading to the observed neurological and platelet-based complications of SARS-CoV-2 infection requires further investigation.

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  1. Version published to 10.1038/s41598-021-90243-1
  2. Version published to 10.1101/2020.06.16.20128660v3 on medRxiv
  3. Version published to 10.1101/2020.06.16.20128660v2 on medRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.06.16.20128660: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Samples and experimental analyses: Preoperative blood and CSF samples were collected within an observational cohort study of patients aged over 65 years without a diagnosis of dementia presenting for planned hip and knee replacements prior to the SARS-CoV-2 pandemic (approved by Office for Research Ethics Committee for Northern Ireland (REC ref: 10/NIR01/5)).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data analysis and Protein simulations: Different machine learning and statistical methods running under Matlab 2020 (Matworks
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)
    Machine learning analysis was performed using Python and Matlab with the results of Python Random Forest classification with SHAP (SHapley Additive exPlanations) algorithm shown to explain the output of machine learning (Lundberg and Lee, 2017).
    Python
    suggested: (IPython, RRID:SCR_001658)
    A comparison of the protein structures of MAOB and ACE2 bonded to SARS-CoV-2 Spike protein are analyzed using UCSF Chimera, Schrodinger software package (Schrodinger Inc.) and PDB Data Bank structure analysis methodologies including jFATCAT (Ye and Godzik, 2003)
    Schrodinger
    suggested: (Schrodinger, RRID:SCR_014879)
    Computational analysis of the spike-MAOB docking was performed using Schrodinger’s BioLuminate package with spike protein obtained from 6M0J PDB entry was used as ligand and each MAOB chain obtained from 6FWC PDB entry was used as a receptor.
    Schrodinger’s
    suggested: (Maestro, RRID:SCR_016748)
    BioLuminate
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    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.

    About SciScore

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  5. Version published to 10.1101/2020.06.16.20128660v1 on medRxiv