Plasmodium infection is associated with cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein

  1. Sarah Lapidus
  2. Feimei Liu
  3. Arnau Casanovas-Massana
  4. Yile Dai
  5. John D. Huck
  6. Carolina Lucas
  7. Jon Klein
  8. Renata B. Filler
  9. Madison S. Strine
  10. Mouhamad Sy
  11. Awa B. Deme
  12. Aida S. Badiane
  13. Baba Dieye
  14. Ibrahima Mbaye Ndiaye
  15. Younous Diedhiou
  16. Amadou Moctar Mbaye
  17. Cheikh Tidiane Diagne
  18. Inés Vigan-Womas
  19. Alassane Mbengue
  20. Bacary D. Sadio
  21. Moussa M. Diagne
  22. Adam J. Moore
  23. Khadidiatou Mangou
  24. Fatoumata Diallo
  25. Seynabou D. Sene
  26. Mariama N. Pouye
  27. Rokhaya Faye
  28. Babacar Diouf
  29. Nivison Nery
  30. Federico Costa
  31. Mitermayer G. Reis
  32. M. Catherine Muenker
  33. Daniel Z. Hodson
  34. Yannick Mbarga
  35. Ben Z. Katz
  36. Jason R. Andrews
  37. Melissa Campbell
  38. Ariktha Srivathsan
  39. Kathy Kamath
  40. Elisabeth Baum-Jones
  41. Ousmane Faye
  42. Amadou Alpha Sall
  43. Juan Carlos Quintero Vélez
  44. Michael Cappello
  45. Michael Wilson
  46. Choukri Ben-Mamoun
  47. Richard Tedder
  48. Myra McClure
  49. Peter Cherepanov
  50. Fabrice A. Somé
  51. Roch K. Dabiré
  52. Carole Else Eboumbou Moukoko
  53. Jean Bosco Ouédraogo
  54. Yap Boum
  55. John Shon
  56. Daouda Ndiaye
  57. Adam Wisnewski
  58. Sunil Parikh
  59. Akiko Iwasaki
  60. Craig B. Wilen
  61. Albert I. Ko
  62. Aaron M. Ring
  63. Amy K. Bei

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Sero-surveillance can monitor and project disease burden and risk. However, SARS-CoV-2 antibody test results can produce false positive results, limiting their efficacy as a sero-surveillance tool. False positive SARS-CoV-2 antibody results are associated with malaria exposure, and understanding this association is essential to interpret sero-surveillance results from malaria-endemic countries. Here, pre-pandemic samples from eight malaria endemic and non-endemic countries and four continents were tested by ELISA to measure SARS-CoV-2 Spike S1 subunit reactivity. Individuals with acute malaria infection generated substantial SARS-CoV-2 reactivity. Cross-reactivity was not associated with reactivity to other human coronaviruses or other SARS-CoV-2 proteins, as measured by peptide and protein arrays. ELISAs with deglycosylated and desialated Spike S1 subunits revealed that cross-reactive antibodies target sialic acid on N-linked glycans of the Spike protein. The functional activity of cross-reactive antibodies measured by neutralization assays showed that cross-reactive antibodies did not neutralize SARS-CoV-2 in vitro. Since routine use of glycosylated or sialated assays could result in false positive SARS-CoV-2 antibody results in malaria endemic regions, which could overestimate exposure and population-level immunity, we explored methods to increase specificity by reducing cross-reactivity. Overestimating population-level exposure to SARS-CoV-2 could lead to underestimates of risk of continued COVID-19 transmission in sub-Saharan Africa.

Article activity feed

  1. Version published to 10.1038/s41598-022-26709-7
  2. ScreenIT

    SciScore for 10.1101/2021.05.10.21256855: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.
    • No funding statement was detected.
    • 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 10.1101/2021.05.10.21256855v1 on medRxiv