Severe COVID-19 infection is associated with aberrant cytokine production by infected lung epithelial cells rather than by systemic immune dysfunction

  1. Sherin J Rouhani
  2. Jonathan A Trujillo
  3. Athalia R Pyzer
  4. Jovian Yu
  5. Jessica Fessler
  6. Alexandra Cabanov
  7. Emily F Higgs
  8. Kyle R. Cron
  9. Yuanyuan Zha
  10. Yihao Lu
  11. Jeffrey C. Bloodworth
  12. Mustafa Fatih Abasiyanik
  13. Susan Okrah
  14. Blake A Flood
  15. Ken Hatogai
  16. Michael YK Leung
  17. Apameh Pezeshk
  18. Lara Kozloff
  19. Robin Reschke
  20. Garth W. Strohbehn
  21. Carolina Soto Chervin
  22. Madan Kumar
  23. Stephen Schrantz
  24. Maria Lucia Madariaga
  25. Kathleen G Beavis
  26. Kiang-Teck J. Yeo
  27. Randy F. Sweis
  28. Jeremy Segal
  29. Savaş Tay
  30. Evgeny Izumchenko
  31. Jeffrey Mueller
  32. Lin S Chen
  33. Thomas F Gajewski

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Abstract

The mechanisms explaining progression to severe COVID-19 remain poorly understood. It has been proposed that immune system dysregulation/over-stimulation may be implicated, but it is not clear how such processes would lead to respiratory failure. We performed comprehensive multiparameter immune monitoring in a tightly controlled cohort of 128 COVID-19 patients, and used the ratio of oxygen saturation to fraction of inspired oxygen (SpO2 / FiO2) as a physiologic measure of disease severity. Machine learning algorithms integrating 139 parameters identified IL-6 and CCL2 as two factors predictive of severe disease, consistent with the therapeutic benefit observed with anti-IL6-R antibody treatment. However, transcripts encoding these cytokines were not detected among circulating immune cells. Rather, in situ analysis of lung specimens using RNAscope and immunofluorescent staining revealed that elevated IL-6 and CCL2 were dominantly produced by infected lung type II pneumocytes. Severe disease was not associated with higher viral load, deficient antibody responses, or dysfunctional T cell responses. These results refine our understanding of severe COVID-19 pathophysiology, indicating that aberrant cytokine production by infected lung epithelial cells is a major driver of immunopathology. We propose that these factors cause local immune regulation towards the benefit of the virus.

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    SciScore for 10.1101/2021.12.09.21266492: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Patients, sample collection: The COVID-19 biobank study was approved by the University of Chicago Institutional Review Board (IRB 20-0520), and all procedures were performed in accordance with the ethical standards set forth in the 1964 Helsinki Declaration.
    Consent: Informed consent was obtained using paper consent, or a Redcap electronic consent form (when possible) to minimize risk of infection.
    Sex as a biological variablenot detected.
    RandomizationTo determine which features were predictive of disease severity, the Random Forest R package randomForest69 was used and area under the ROC curve (AUC) calculated.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Anti-SARS-CoV-2 antibody ELISA: The SARS-CoV-2 full-length Spike and Receptor Binding Domain (RBD) protein expression constructs were obtained from Florian Krammer and Patrick Wilson65, and used to generate recombinant protein for an enzyme-linked immunosorbent assay (ELISA) adapted from established protocols66.
    Anti-SARS-CoV-2
    suggested: None
    SARS-CoV-2 full-length Spike and Receptor Binding Domain ( RBD
    suggested: None
    After 3 washes in 0.05% PBS-Tween 20, an HRP-conjugated secondary antibody specific for either total Ig (goat anti-human immunoglobulin Ig, SouthernBiotech), IgM (anti-human IgM, μ-chain specific, Millipore Sigma), or IgG (
    anti-human immunoglobulin Ig , SouthernBiotech) , IgM
    suggested: None
    anti-human IgM , μ-chain specific , Millipore Sigma) , or IgG
    suggested: None
    Brilliant stain buffer plus (BD), CXCR3 PECy7 (G025H7, Biolegend, 5 uL), CXCR5 BV750 (RF8B2, BD, 1.2 uL), CCR6 BV711 (G034E3, Biolegend, 1.2 uL), and TCRgd PCPCeF710 (B1.1, Thermo, 5 uL) were added for 10 minutes, and the remainder of extracellular antibodies (CD101 BUV563 (V7.1, BD, 5 uL), CD11b PCPCy5.5 (ICRF44, Biolegend, 0.6 uL), CD11c BUV661 (B-ly6, BD, 3.5 uL),
    CXCR3
    suggested: (BioLegend Cat# 353731, RRID:AB_2563532)
    G025H7
    suggested: (BioLegend Cat# 353731, RRID:AB_2563532)
    CXCR5
    suggested: (BD Biosciences Cat# 741316, RRID:AB_2870835)
    CCR6
    suggested: (BioLegend Cat# 353436, RRID:AB_2629608)
    CD101
    suggested: (BD Biosciences Cat# 749167, RRID:AB_2873548)
    ICRF44
    suggested: (Fitzgerald Industries International Cat# 10R-CD11bcHU, RRID:AB_1283000)
    PepTivator SARS-CoV-2 peptide pools consisting of 15-mer sequences with 11 amino acids overlap against the immunodominant sequence of the surface glycoprotein (“ S”), and complete sequences of the membrane glycoprotein (“ M”) and nucleocapsid phosphoprotein (“ N”) (all from Miltenyi Biotec) were combined and used at 1 ug/mL, along with 0.5 ug anti-CD28/CD49D antibodies (clone L293/L25, BD biosciences).
    the membrane glycoprotein ( “ M” )
    suggested: None
    anti-CD28/CD49D
    suggested: None
    The remainder of the extracellular antibodies (TCRgd PCPCeF710 (B1.1, Thermo, 5 uL), CD3 BV510 (OKT3, Biolegend, 5 uL), PD-1 BV785 (EH12.2H7, Biolegend, 5 uL), CD56 BUV737 (NCAM16.2, BD, 3.5 uL), HLA-DR APCF750 (L243, Biolegend, 2.5 uL)
    CD3
    suggested: None
    OKT3
    suggested: (BD Biosciences Cat# 750971, RRID:AB_2875040)
    PD-1
    suggested: (Nanostring Cat# 121300104, RRID:AB_2893077)
    CD56
    suggested: (BD Biosciences Cat# 564447, RRID:AB_2744432)
    The tissue sections were blocked with Co-Detection antibody diluent (ACD) and incubated with anti-TTF1 antibody (SPT24, BioCare Medical) overnight at 4° C, washed in PBS-T buffer, incubated in 10% Neutral Buffered Formalin for 30 min at RT, and washed in PBS-T.
    anti-TTF1
    suggested: None
    SPT24
    suggested: (Leica Biosystems Cat# PA0368, RRID:AB_10555979)
    The TTF1 primary antibody was detected with HRP-conjugated secondary antibody (Opal Polymer HRP Ms + Rb, Perkin Elmer) and Opal 690 dye.
    Opal Polymer HRP Ms + Rb , Perkin Elmer
    suggested: None
    Subsequent staining on the same sections was performed with an antibody against CD45 (Leukocyte Common Antigen Cocktail: PD7/26/16 and 2B11, BioCare Medical) and detected with HRP-conjugated secondary antibody and Opal 520 dye.
    CD45
    suggested: None
    Co-staining for IL-6 RNA and macrophages was performed using RNAscope® probe Hs-IL-6, which was fluorescently labeled with OPAL 690 dye, and an antibody against either CD68 (Clone KP1, BioCare Medical; diluted in Da Vinci Green diluent) or CD163 (Clone 10D6, BioCare Medical; diluted in Renoir Red diluent) and detected with HRP-conjugated secondary antibody (Opal Polymer HRP MS+ RB) and OPAL 540 dye.
    CD68
    suggested: None
    CD163
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Recombinant proteins were produced using a Chinese hamster ovary (CHO) cell line expression system and purified using metal-chelate affinity chromatography.
    Chinese hamster ovary ( CHO )
    suggested: None
    Software and Algorithms
    SentencesResources
    Fluorescence was read using a QX200 droplet reader (Bio-Rad) and analyzed with Quantasoft software.
    Quantasoft
    suggested: None
    Clinical data warehouse: Clinical data was exported through a clinical data warehouse and was also abstracted by a clinical data manager into a standardized RedCap database.
    RedCap
    suggested: (REDCap, RRID:SCR_003445)
    Flow cytometry data were processed using FlowJo V10.7.1.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Graphs were created and statistics performed using either GraphPad Prism v9.0.0 or R 4.0.3 (R Core Team,
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 46 and 38. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  2. Version published to 10.1101/2021.12.09.21266492v1 on medRxiv