Autoantibodies linked to autoimmune diseases associate with COVID-19 outcomes

  1. Gabriela Crispim Baiocchi
  2. Aristo Vojdani
  3. Avi Z Rosenberg
  4. Elroy Vojdani
  5. Gilad Halpert
  6. Yuri Ostrinski
  7. Israel Zyskind
  8. Igor Salerno Filgueiras
  9. Lena F. Schimke
  10. Alexandre H. C. Marques
  11. Lasse M. Giil
  12. Yael Bublil Lavi
  13. Jonathan I. Silverberg
  14. Jason Zimmerman
  15. Dana Ashley Hill
  16. Amanda Thornton
  17. Myungjin Kim
  18. Roberta De Vito
  19. Dennyson Leandro M. Fonseca
  20. Desireé Rodrigues Plaça
  21. Paula Paccielli Freire
  22. Niels Olsen Saraiva Camara
  23. Vera Lúcia Garcia Calich
  24. Harald Heidecke
  25. Miriam T. Lattin
  26. Hans D. Ochs
  27. Gabriela Riemekasten
  28. Howard Amital
  29. Otavio Cabral-Marques
  30. Yehuda Shoenfeld

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Abstract

The SARS-CoV-2 infection is associated with increased levels of autoantibodies targeting immunological proteins such as cytokines and chemokines. Reports further indicate that COVID-19 patients may develop a wide spectrum of autoimmune diseases due to reasons not fully understood. Even so, the landscape of autoantibodies induced by SARS-CoV-2 infection remains uncharted territory. To gain more insight, we carried out a comprehensive assessment of autoantibodies known to be linked to diverse autoimmune diseases observed in COVID-19 patients, in a cohort of 248 individuals, of which171 were COVID-19 patients (74 with mild, 65 moderate, and 32 with severe disease) and 77were healthy controls. Dysregulated autoantibody serum levels, characterized mainly by elevated concentrations, occurred mostly in patients with moderate or severe COVID-19 infection, and was accompanied by a progressive disruption of physiologic IgG and IgA autoantibody signatures. A similar perturbation was found in patients with anosmia. Notably, autoantibody levels often accompanied anti-SARS-CoV-2 antibody concentrations, being both indicated by random forest classification as strong predictors of COVID-19 outcome, together with age. Moreover, higher levels of autoantibodies (mainly IgGs) were seen in the elderly with severe disease compared with young COVID-19 patients with severe disease. These findings suggest that the SARS-CoV-2 infection induces a broader loss of self-tolerance than previously thought, providing new ideas for therapeutic interventions.

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    SciScore for 10.1101/2022.02.17.22271057: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Measurements of anti-SARS-CoV-2 antibody and autoantibodies linked to autoimmune diseases: All collected sera were tested for IgG anti-SARS-CoV-2 antibody using the ZEUS SARS-CoV-2 ELISA Test System according to the manufacturer’s instructions (ZEUS Scientific, New Jersey, USA).
    anti-SARS-CoV-2
    suggested: None
    Serum IgG autoantibodies against nuclear antigen (ANA), extractable nuclear antigen (ENA), double-stranded DNA (dsDNA), actin, mitochondrial M2, and rheumatoid factor (RF) were measured using commercial ELISA kits obtained from INOVA Diagnostics (San Diego, CA, USA).
    antigen ( ANA) , extractable nuclear antigen ( ENA
    suggested: None
    dsDNA) , actin
    suggested: None
    Plates were washed and the serum samples from healthy controls and the SARS-CoV-2 patients were diluted at 1:50 for the determination of IgA antibody, and 1:100 for the determination of IgG antibody in serum diluent buffer or 1% BSA in PBS containing 0.05% Tween 20 was added to the wells of ELISA plates, which were then incubated for one hour at room temperature.
    IgA
    suggested: (LSBio (LifeSpan Cat# LS-C21944-6, RRID:AB_900131)
    Software and Algorithms
    SentencesResources
    Differences in autoantibody levels: Box plots showing differences in autoantibodies from COVID-19 patient groups (mild, moderate and severe) and healthy controls were generated using the R version 4.0.5 (The R Project for Statistical Computing.
    R Project for Statistical
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    We trained the random forest model using the functionalities of the R package randomForest (version 4.6.14)65.
    randomForest
    suggested: (RandomForest Package in R, RRID:SCR_015718)
    In addition, circle plots of autoantibody correlation were built using the R packages qgraph, ggplot2, psych, inlmisc to visualize the patterns of Spearman’s rank correlation coefficients between autoantibodies.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are limitations of our worlk that need consideration. For instance, our study did not have longitudinal data to analyze the pharmacokinetics of the IgG and IgA autoantibodies, from disease onset to convalescence or post-acute COVID-19 syndrome. Our study cohort did not include asymptomatic patients. Moreover, we cannot exclude the possibility that at least some of our patients had high levels of autoantibodies prior to SARS-CoV-2 infection, or that autoantibodies to some antigens (e.g., heparin) could have been induced by anticoagulant therapy with heparin. In addition, we did not assess alterations in the number of circulating B lymphocytes and whether this could explain the higher serum levels of autoantibodies. In addition, future studies are required to clarify the role of virus and host genetics in the production of autoantibodies. On the other hand, our work raises new questions such as whether the dysregulated levels of autoantibodies remain after COVID-19 remission and these levels are in patients with post-COVID-19 syndrome. Taken together, our work provides a comprehensive view of the spectrum of autoantibodies linked with autoimmune diseases that are induced by SARS-CoV-2 infection. This work maps the intersection of COVID-19 and autoimmunity93–95, demonstrating the dysregulation of multiple autoantibodies that are linked to autoimmune diseases during SARS-CoV-2 infections, and the altered correlation signatures according to disease severity and anosmia. The ...

    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.

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

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  2. Version published to 10.1101/2022.02.17.22271057v1 on medRxiv