Differential Cytokine Signatures of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Influenza Infection Highlight Key Differences in Pathobiology

  1. Andrew H Karaba
  2. Weiqiang Zhou
  3. Leon L Hsieh
  4. Alexis Figueroa
  5. Guido Massaccesi
  6. Richard E Rothman
  7. Katherine Z J Fenstermacher
  8. Lauren Sauer
  9. Kathryn Shaw-Saliba
  10. Paul W Blair
  11. Matthew L Robinson
  12. Sherry Leung
  13. Russell Wesson
  14. Nada Alachkar
  15. Ramy El-Diwany
  16. Hongkai Ji
  17. Andrea L Cox

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Abstract

Background

Several inflammatory cytokines are upregulated in severe coronavirus disease 2019 (COVID-19). We compared cytokines in COVID-19 versus influenza to define differentiating features of the inflammatory response to these pathogens and their association with severe disease. Because elevated body mass index (BMI) is a known risk factor for severe COVID-19, we examined the relationship of BMI to cytokines associated with severe disease.

Methods

Thirty-seven cytokines and chemokines were measured in plasma from 135 patients with COVID-19, 57 patients with influenza, and 30 healthy controls. Controlling for BMI, age, and sex, differences in cytokines between groups were determined by linear regression and random forest prediction was used to determine the cytokines most important in distinguishing severe COVID-19 and influenza. Mediation analysis was used to identify cytokines that mediate the effect of BMI and age on disease severity.

Results

Interleukin-18 (IL-18), IL-1β, IL-6, and tumor necrosis factor-α (TNF-α) were significantly increased in COVID-19 versus influenza patients, whereas granulocyte macrophage colony-stimulating factor, interferon-γ (IFN-γ), IFN-λ1, IL-10, IL-15, and monocyte chemoattractant protein 2 were significantly elevated in the influenza group. In subgroup analysis based on disease severity, IL-18, IL-6, and TNF-α were elevated in severe COVID-19, but not in severe influenza. Random forest analysis identified high IL-6 and low IFN-λ1 levels as the most distinct between severe COVID-19 and severe influenza. Finally, IL-1RA was identified as a potential mediator of the effects of BMI on COVID-19 severity.

Conclusions

These findings point to activation of fundamentally different innate immune pathways in severe acute respiratory syndrome coronavirus 2 and influenza infection, and emphasize drivers of severe COVID-19 to focus both mechanistic and therapeutic investigations.

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  1. Version published to 10.1093/cid/ciab376
  2. ScreenIT

    SciScore for 10.1101/2021.01.29.21250317: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Study Participants and Samples: All studies were approved by the Johns Hopkins (JH) Institutional Review Board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Cytokine measurement: Plasma was thawed and cytokines and chemokines (IFN-α2a, IFN-β, IL-18, IL-1RA, IL-23, IFN-λ1, IL-2Ra, MCP-2, GM-CSF, IL-23p40, IL-15, IL-16, IL-17A, IL-1α, IL-5, IL-7, TNF-β, VEGF, Eotaxin, Eotaxin-3, IP-10, MCP-1, MCP-4, MDC, MIP-1α, MIP-1β, TARC, IFN-γ, IL-10, IL-12p70, IL-13, IL-1β, IL-2, IL-4, IL-6, IL-8, TNF-α) were measured using a custom multiplex kit from Meso Scale Discovery (MSD, Rockville, MD) according to the manufacture’s protocol and data were acquired on a MESO QuickPlex SQ 120.
    MCP-1
    suggested: None
    Software and Algorithms
    SentencesResources
    To further examine cytokines/chemokines that drive the difference between the two diseases, a multivariate analysis using R packages caret [45] and randomForest [46] based on a machine learning model, random forest were utilized.
    randomForest
    suggested: (RandomForest Package in R, RRID:SCR_015718)

    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:
    Limitations to our study include that outpatients with mild COVID-19 were not included. However, we would predict that differences between those with and without severe disease in our study would only be more significant if milder disease were included. In addition, our study subjects with influenza also had disease severe enough to warrant hospitalization, making them an appropriate comparator. An additional limitation is that we examined a single timepoint. It is possible that the dynamics of these cytokines during the course of hospitalization would change in such a way that the cytokine profiles would become even more or less distinct from influenza. However, as patients remain hospitalized, complications from critical illness arise that could obfuscate the comparison to influenza. Finally, the influenza cohort was, on average, younger than the COVID-19 cohort. However, we adjusted for age in our analysis. This study provides insight into pathways activated by SARS-CoV-2 and influenza, demonstrating that some inflammatory cytokines elevated in COVID-19 likely reflect common pathways activated in respiratory tract inflammation, while others are more specific to COVID-19 pathogenesis. We identified IL-1RA as a potential mediator of the effect of increased BMI on COVID-19 disease severity. In summary, this study demonstrates activation of a proinflammatory cytokine macrophage pathway and a role for IL-1RA in severe COVID-19, highlighting potential therapeutic targets.

    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.
    • Thank you for including a protocol registration statement.

    About SciScore

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  3. Version published to 10.1101/2021.01.29.21250317v1 on medRxiv