Distinguishing Incubation and Acute Disease Stages of Mild-to-Moderate COVID-19

  1. Michael Müller
  2. Johann Volzke
  3. Behnam Subin
  4. Christian Johann Schmidt
  5. Hilte Geerdes-Fenge
  6. Emil Christian Reisinger
  7. Brigitte Müller-Hilke

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Abstract

While numerous studies have already compared the immune responses against SARS-CoV-2 in severely and mild-to-moderately ill COVID-19 patients, longitudinal trajectories are still scarce. We therefore set out to analyze serial blood samples from mild-to-moderately ill patients in order to define the immune landscapes for differently progressed disease stages. Twenty-two COVID-19 patients were subjected to consecutive venipuncture within seven days after diagnosis or admittance to hospital. Flow cytometry was performed to analyze peripheral blood immune cell compositions and their activation as were plasma levels of cytokines and SARS-CoV-2 specific immunoglobulins. Healthy donors served as controls. Integrating the kinetics of plasmablasts and SARS-CoV-2 specific antibodies allowed for the definition of three disease stages of early COVID-19. The incubation phase was characterized by a sharp increase in pro-inflammatory monocytes and terminally differentiated cytotoxic T cells. The latter correlated significantly with elevated concentrations of IP-10. Early acute infection featured a peak in PD-1+ cytotoxic T cells, plasmablasts and increasing titers of virus specific antibodies. During late acute infection, immature neutrophils were enriched, whereas all other parameters returned to baseline. Our findings will help to define landmarks that are indispensable for the refinement of new anti-viral and anti-inflammatory therapeutics, and may also inform clinicians to optimize treatment and prevent fatal outcomes.

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  1. Version published to 10.3390/v14020203
  2. ScreenIT

    SciScore for 10.1101/2021.09.07.21263200: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study was approved by the ethics committee of the University Medical Center of Rostock.
    Consent: It is filed under A 2020-0086 and written informed consent was obtained from all participants.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The following amounts of antibody:fluorophore-combinations were used: 0.25 µg CD127:APC/R700 (clone HIL-7R-M21), 1 µg CD147:BV421 (TRA-1-85), 0.5 µg CD45RO:BV480 (UCHL1, BD Biosciences, Franklin Lakes/NJ, United States), 1 µg CD11b:PerCP/Cy5.5 (ICRF44), 0.8 µg CD11c:BV785 (3.9), 0.56 µg CD14:BV510 (
    antibody:fluorophore-combinations
    suggested: None
    UCHL1
    suggested: (BioLegend Cat# 304233, RRID:AB_11219394)
    After washing, PE-conjugated anti-human IgG/IgM detection antibodies were added to the samples followed by incubation for 1.5 h at room temperature and 600 rpm.
    anti-human IgG/IgM
    suggested: (MyBioSource Cat# MBS703131, RRID:AB_10887474)
    4.5 Cytokine analysis: For the determination of cytokine concentrations in plasma samples, the LEGENDplexTM Human Anti-Virus Response Panel (Biolegend) was used containing capture beads and detection antibodies for Interleukin (IL-)1β, IL-6, IL-8, IL-10, IL-12p70, Interferon (IFN)α
    IL-6
    suggested: (Bio-Rad Cat# M60009RDPD, RRID:AB_2857368)
    IL-8
    suggested: None
    IL-10
    suggested: (Bio-Rad Cat# M60009RDPD, RRID:AB_2857368)
    Experimental Models: Cell Lines
    SentencesResources
    In detail, the kit provided unstimulated HeLa cells, HeLa cells stimulated with tumor necrosis factor (TNF)α/Calyculin A, MCF7 cells stimulated with insulin-like growth factor 1 and A431 cells stimulated with epidermal growth factor.
    HeLa
    suggested: None
    MCF7
    suggested: None
    A431
    suggested: CLS Cat# 300112/p753_A-431, RRID:CVCL_0037)
    Software and Algorithms
    SentencesResources
    Analysis of flow cytometry data was done using the FlowJo software version 10.7 (FlowJo, Ashland/OR, United States) with the manual gating strategy shown in supplemental Figure 1.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Data acquisition was performed using the Cytek® Aurora (Cytek Biosciences). 4.6 Statistics: Data analysis and visualization were performed using R (version 3.5.1), InStat (GraphPad, San Diego/CA, United States) and SPSS (IBM, Armonk/NY, United States).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 8, 38, 6 and 7. 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.

  3. Version published to 10.1101/2021.09.07.21263200v1 on medRxiv