Cutting Edge: Severe SARS-CoV-2 Infection in Humans Is Defined by a Shift in the Serum Lipidome, Resulting in Dysregulation of Eicosanoid Immune Mediators

  1. Benjamin Schwarz
  2. Lokesh Sharma
  3. Lydia Roberts
  4. Xiaohua Peng
  5. Santos Bermejo
  6. Ian Leighton
  7. Arnau Casanovas-Massana
  8. Maksym Minasyan
  9. Shelli Farhadian
  10. Albert I Ko
  11. Yale IMPACT Team
  12. Charles S Dela Cruz
  13. Catharine M Bosio

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Abstract

The COVID-19 pandemic has affected more than 20 million people worldwide, with mortality exceeding 800,000 patients. Risk factors associated with severe disease and mortality include advanced age, hypertension, diabetes, and obesity. Each of these risk factors pathologically disrupts the lipidome, including immunomodulatory eicosanoid and docosanoid lipid mediators (LMs). We hypothesized that dysregulation of LMs may be a defining feature of the severity of COVID-19. By examining LMs and polyunsaturated fatty acid precursor lipids in serum from hospitalized COVID-19 patients, we demonstrate that moderate and severe disease are separated by specific differences in abundance of immune-regulatory and proinflammatory LMs. This difference in LM balance corresponded with decreased LM products of ALOX12 and COX2 and an increase LMs products of ALOX5 and cytochrome p450. Given the important immune-regulatory role of LMs, these data provide mechanistic insight into an immuno-lipidomic imbalance in severe COVID-19.

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  1. Version published to 10.4049/jimmunol.2001025
  2. Version published to 10.1101/2020.07.09.20149849v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.07.09.20149849: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics Statement: This study was approved by Yale Human Research Protection Program Institutional Review Boards (FWA00002571, Protocol ID.
    Consent: Patients in this study were enrolled through the IMPACT biorepository study after obtaining informed consent.
    RandomizationSample order was randomized throughout each extraction.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Ethics Statement: This study was approved by Yale Human Research Protection Program Institutional Review Boards (FWA00002571, Protocol ID.
    Yale Human Research Protection Program
    suggested: None
    44 Univariate and multivariate analysis was performed in MarkerView® Software 1.3.1.
    MarkerView®
    suggested: None
    38 Data was read into Seurat v3.0 and each cluster’s cellular identity was annotated per Wilk, et al Nature Medicine 2020.38 Expression levels of ALOX and CYP genes within specific cell types in healthy controls and COVID-19 patients was visualized using Seurat’s DotPlot
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    To investigate the difference in the control, moderate and severe groups, GraphPad Prism (version 8.4.2) was used.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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.

  4. Version published to 10.1101/2020.07.09.20149849v1 on medRxiv