Immunological Profiling of COVID-19 Patients with Pulmonary Sequelae

  1. Jianghua Wu
  2. Lu Tang
  3. Yanling Ma
  4. Yu Li
  5. Dongmei Zhang
  6. Qian Li
  7. Heng Mei
  8. Yu Hu

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Abstract

A considerable proportion of COVID-19 survivors have residual lung lesions such as ground-glass opacity and fiber streak shadow. To determine the relationship between host immunity and residual lung lesions, we performed an extensive analysis of immune responses in convalescent patients with COVID-19 1 year after discharge.

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  1. Version published to 10.1128/mbio.01599-21
  2. ScreenIT

    SciScore for 10.1101/2021.06.03.447023: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (#2020/0004), and written informed consents were obtained from all participants.
    Consent: This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (#2020/0004), and written informed consents were obtained from all participants.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Detection of serum SARS-CoV-2 IgG and IgM antibodies was evaluated by IgM/IgG antibody detection kit (Abbott Laboratories,
    IgM
    suggested: None
    After 5 hours at 37 °C, the cells were stained with fluorochrome associated antibodies specific for surface molecules; next, the cells underwent fixation and permeabilization for intracellular staining with antibodies specific for the following intracellular proteins: IL-2, IL-4, IL-17A, IFN-γ and TNF-α.
    IL-2
    suggested: None
    IL-4 , IL-17A
    suggested: None
    IFN-γ
    suggested: None
    TNF-α
    suggested: None
    Software and Algorithms
    SentencesResources
    Detection of serum SARS-CoV-2 IgG and IgM antibodies was evaluated by IgM/IgG antibody detection kit (Abbott Laboratories,
    Abbott Laboratories
    suggested: None
    Flow cytometry was performed using a BD LSRFortessa X-20 (BD Biosciences), and data were analyzed with FlowJo V10 software.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    All statistical data were analyzed using SPSS version 25.0 Statistical Software (Chicago, IL, USA),
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    , GraphPad Prism 8 software (GraphPad Software, La Jolla, California) or R software Version 4.0.2 (Institute for Statistics and Mathematics, Vienna, Austria).
    GraphPad
    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: We detected the following sentences addressing limitations in the study:
    Although our study confirms some findings and provides new data on the innate and adaptive immune landscape of patients with PS who have recovered from COVID-19 one year after discharge, we recognize limitations that might be overcome with larger sample sizes and matched control populations. Furthermore, there is a lack of understanding of the phenotype and function of immune cells from the lungs, which may directly participate in the formation of PS. Hence, the hierarchy of immunodominant circulating blood immune cells may not exactly reflect immunophenotypic features in the lungs. In summary, our study first shows significant differences in immunological characteristics between PPSs and NPSs one year after discharge. Although the detailed mechanisms by which cellular immunity participates in the development of PS remain to be investigated, our in-depth analysis of immunological profiling contributes to our understanding of the immunopathogenesis of COVID-19, facilitating the tailoring of more effective and proactive therapies for these patients.

    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 page 35. 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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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 10.1101/2021.06.03.447023v1 on bioRxiv