Virological Characterization of Critically Ill Patients With COVID-19 in the United Kingdom: Interactions of Viral Load, Antibody Status, and B.1.1.7 Infection

  1. Jeremy Ratcliff
  2. Dung Nguyen
  3. Matthew Fish
  4. Jennifer Rynne
  5. Aislinn Jennings
  6. Sarah Williams
  7. Farah Al-Beidh
  8. David Bonsall
  9. Amy Evans
  10. Tanya Golubchik
  11. Anthony C Gordon
  12. Abigail Lamikanra
  13. Pat Tsang
  14. Nick A Ciccone
  15. Ullrich Leuscher
  16. Wendy Slack
  17. Emma Laing
  18. Paul R Mouncey
  19. Sheba Ziyenge
  20. Marta Oliveira
  21. Rutger Ploeg
  22. Kathryn M Rowan
  23. Manu Shankar-Hari
  24. David J Roberts
  25. David K Menon
  26. Lise Estcourt
  27. Peter Simmonds
  28. Heli Harvala
  29. REMAP-CAP Immunoglobulin Domain UK Investigators

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Abstract

Background

Convalescent plasma containing neutralizing antibody to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is under investigation for coronavirus disease 2019 (COVID-19) treatment. We report diverse virological characteristics of UK intensive care patients enrolled in the Immunoglobulin Domain of the REMAP-CAP randomized controlled trial that potentially influence treatment outcomes.

Methods

SARS-CoV-2 RNA in nasopharyngeal swabs collected pretreatment was quantified by PCR. Antibody status was determined by spike-protein ELISA. B.1.1.7 was differentiated from other SARS-CoV-2 strains using allele-specific probes or restriction site polymorphism (SfcI) targeting D1118H.

Results

Of 1274 subjects, 90% were PCR positive with viral loads 118–1.7 × 1011IU/mL. Median viral loads were 40-fold higher in those IgG seronegative (n = 354; 28%) compared to seropositives (n = 939; 72%). Frequencies of B.1.1.7 increased from <1% in November 2020 to 82% of subjects in January 2021. Seronegative individuals with wild-type SARS-CoV-2 had significantly higher viral loads than seropositives (medians 5.8 × 106 and 2.0 × 105 IU/mL, respectively; P = 2 × 10−15).

Conclusions

High viral loads in seropositive B.1.1.7-infected subjects and resistance to seroconversion indicate less effective clearance by innate and adaptive immune responses. SARS-CoV-2 strain, viral loads, and antibody status define subgroups for analysis of treatment efficacy.

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  1. Version published to 10.1093/infdis/jiab283
  2. ScreenIT

    SciScore for 10.1101/2021.02.24.21251989: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by London-Surrey Borders Research Ethics Committee London Centre (18/LO/0660).
    Consent: Written or verbal informed consent, in accordance with regional legislation, is obtained from all patients or their surrogates.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Serology: Baseline blood samples were also collected from all patients to determine the presence of SARS-CoV-2 IgG antibodies against spike protein at the time of transfusion.
    SARS-CoV-2 IgG
    suggested: None

    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: 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 10.1101/2021.02.24.21251989v1 on medRxiv