Kynurenic acid may underlie sex-specific immune responses to COVID-19

  1. Yuping Cai
  2. Daniel J. Kim
  3. Takehiro Takahashi
  4. David I. Broadhurst
  5. Hong Yan
  6. Shuangge Ma
  7. Nicholas J. W. Rattray
  8. Arnau Casanovas-Massana
  9. Benjamin Israelow
  10. Jon Klein
  11. Carolina Lucas
  12. Tianyang Mao
  13. Adam J. Moore
  14. M. Catherine Muenker
  15. Ji Eun Oh
  16. Julio Silva
  17. Patrick Wong
  18. Yale IMPACT Research team
  19. Albert I. Ko
  20. Sajid A. Khan
  21. Akiko Iwasaki
  22. Caroline H. Johnson

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Abstract

Compared to females, male COVID-19 patients have more kynurenic acid, which may underlie their poorer immune response.

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  1. Version published to 10.1126/scisignal.abf8483
  2. ScreenIT

    SciScore for 10.1101/2020.09.06.20189159: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableCohort A consisted of 39 patients aged ≥ 18 years old that tested positive for SARS-CoV-2 by RT-PCR from nasopharyngeal and/or oropharyngeal swabs (females n = 22, males n = 17)34.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    raw) were converted to mzML files using ProteoWizard MSConvert
    ProteoWizard
    suggested: (ProteoWizard, RRID:SCR_012056)
    The files were then processed in R (version 3.4.3), using the XCMS package for feature detection, retention time correction, and alignment36.
    XCMS
    suggested: (XCMS, RRID:SCR_015538)
    ” After loading the expression data into R with the CePa package, Pearson correlation coefficients were calculated for pairs of target genes within each tissue of each sex, and data was visualized as a heatmap displaying the difference between male and female coefficients using the ComplexHeatmap package.
    ComplexHeatmap
    suggested: (ComplexHeatmap, RRID:SCR_017270)
    Male-specific correlations were validated by scatter plots and linear regressions, which were generated using the ggplot2 R package.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your code and 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

    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 10.1101/2020.09.06.20189159v1 on medRxiv
  4. Version published to 10.1101/2020.09.06.20189159v2 on medRxiv