Deregulated cellular circuits driving immunoglobulins and complement consumption associate with the severity of COVID‐19 patients

  1. Ana Marcos‐Jiménez
  2. Santiago Sánchez‐Alonso
  3. Ana Alcaraz‐Serna
  4. Laura Esparcia
  5. Celia López‐Sanz
  6. Miguel Sampedro‐Núñez
  7. Tamara Mateu‐Albero
  8. Ildefonso Sánchez‐Cerrillo
  9. Pedro Martínez‐Fleta
  10. Ligia Gabrie
  11. Luciana del Campo Guerola
  12. José Miguel Rodríguez‐Frade
  13. José M. Casasnovas
  14. Hugh T. Reyburn
  15. Mar Valés‐Gómez
  16. Margarita López‐Trascasa
  17. Enrique Martín‐Gayo
  18. María José Calzada
  19. Santos Castañeda
  20. Hortensia de la Fuente
  21. Isidoro González‐Álvaro
  22. Francisco Sánchez‐Madrid
  23. Cecilia Muñoz‐Calleja
  24. Arantzazu Alfranca

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Abstract

SARS‐CoV‐2 infection causes an abrupt response by the host immune system, which is largely responsible for the outcome of COVID‐19. We investigated whether the specific immune responses in the peripheral blood of 276 patients were associated with the severity and progression of COVID‐19. At admission, dramatic lymphopenia of T, B, and NK cells is associated with severity. Conversely, the proportion of B cells, plasmablasts, circulating follicular helper T cells (cTfh) and CD56 – CD16 + NK‐cells increased. Regarding humoral immunity, levels of IgM, IgA, and IgG were unaffected, but when degrees of severity were considered, IgG was lower in severe patients. Compared to healthy donors, complement C3 and C4 protein levels were higher in mild and moderate, but not in severe patients, while the activation peptide of C5 (C5a) increased from the admission in every patient, regardless of their severity. Moreover, total IgG, the IgG1 and IgG3 isotypes, and C4 decreased from day 0 to day 10 in patients who were hospitalized for more than two weeks, but not in patients who were discharged earlier. Our study provides important clues to understand the immune response observed in COVID‐19 patients, associating severity with an imbalanced humoral response, and identifying new targets for therapeutic intervention.

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  1. Version published to 10.1002/eji.202048858
  2. ScreenIT

    SciScore for 10.1101/2020.06.15.20131706: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Study approval: This study was approved by the local Research Ethics Committee (register number 4070) and it was carried out following the ethical principles established in the Declaration of Helsinki.
    Consent: All included patients were informed about the study and gave an oral informed consent because of COVID-19 emergency as proposed by AEMPS.
    RandomizationA subgroup of 84 patients were randomly selected during the period of study for an extensive characterization of their lymphocyte subsets.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    These patients, as well as 19 healthy donors, were studied with an extended panel of multicolor monoclonal antibodies (mAbs): anti-CD4 FITC, anti-CD107 FITC, anti-IgD FITC, anti-PD-1 PE, anti-CD56 PE, anti-CD27 PE, anti-CD38 PerCP/Cy5.5, anti-CXCR5 AF647
    anti-CD4 FITC
    suggested: (BD Biosciences Cat# 340573, RRID:AB_400476)
    anti-CD107 FITC
    suggested: (Antibodies-Online Cat# ABIN288592, RRID:AB_10765326)
    anti-IgD FITC
    suggested: None
    anti-PD-1 PE
    suggested: None
    anti-CD56
    suggested: None
    anti-CD27 PE
    suggested: None
    anti-CD38
    suggested: (SouthernBiotech Cat# 1640-31, RRID:AB_2795082)
    anti-CXCR5
    suggested: None
    Software and Algorithms
    SentencesResources
    At least 100 cells of the less represented subsets were collected and data were analyzed with the FACSDiva and FlowJo Softwares from BD Biosciences.
    FACSDiva
    suggested: (BD FACSDiva Software, RRID:SCR_001456)
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    To analyse distribution of lymphocyte in COVID-19 patients and healthy donors, an automated clustering and dimensionality reduction was performed using viSNE and FlowSOM tools (Cytobank)
    FlowSOM
    suggested: (FlowSOM, RRID:SCR_016899)
    Cytobank
    suggested: (Cytobank, RRID:SCR_014043)
    Differences in normalized cells between healthy donors and severity groups (adjusted by sex and age) were assessed with a moderated t-test using limma R package(36).
    limma
    suggested: (LIMMA, RRID:SCR_010943)
    GraphPad Prism 4 software was also used for graphics.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: Thank you for sharing your code.

    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.

  3. Version published to 10.1101/2020.06.15.20131706v1 on medRxiv