COVID-19 infection alters kynurenine and fatty acid metabolism, correlating with IL-6 levels and renal status

  1. Tiffany Thomas
  2. Davide Stefanoni
  3. Julie A. Reisz
  4. Travis Nemkov
  5. Lorenzo Bertolone
  6. Richard O. Francis
  7. Krystalyn E. Hudson
  8. James C. Zimring
  9. Kirk C. Hansen
  10. Eldad A. Hod
  11. Steven L. Spitalnik
  12. Angelo D’Alessandro

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Abstract

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  1. Version published to 10.1172/jci.insight.140327
  2. ScreenIT

    SciScore for 10.1101/2020.05.14.20102491: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Blood collection and processing: This observational study was conducted according to the Declaration of Helsinki, in accordance with good clinical practice guidelines, and approved by the Columbia University Institutional Review Board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Graphs and statistical analyses were prepared with GraphPad Prism 8.0 (GraphPad Software, Inc, La Jolla, CA)
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    , GENE E (Broad Institute, Cambridge, MA, USA), and MetaboAnalyst 4.0.
    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: We detected the following sentences addressing limitations in the study:
    The present study has several limitations. First, the analyses were performed on sera obtained as a byproduct of routine clinical laboratory testing. Although immediately refrigerated and stored overnight for less than 24h, technical bias may have been introduced and propagated across all samples owing to the collection procedures. Protocols are currently being implemented to prospectively collect and bank fresh samples of serum and plasma, red blood cells, and buffy coats. In addition, males are disproportionally represented in our study: 75% of the COVID-19-positive patients. As such, no sex-specific analysis was performed, and future investigations on larger, prospectively enrolled cohorts are currently underway to address this issue. Similarly, the mean age of COVID-19-positive patients was 56, whereas the control population was generally younger (mean age: 33 years old). Nonetheless, comparisons to prior studies on the effect of aging on the plasma/whole blood metabolome does not suggest that the observations reported here are due to age alone (71, 72). In addition, the COVID-19 patients in this study had significant disease, by definition, because they were all inpatients; future studies will investigate patients with milder disease and asymptomatic infected patients. Finally, it will be important to study serial samples from patients throughout their clinical course to evaluate changes in the serum metabolome as a function of clinical status (e.g., on or off a ventilat...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04280705CompletedAdaptive COVID-19 Treatment Trial (ACTT)

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.05.14.20102491v1 on medRxiv