SARS-CoV-2 antibody magnitude and detectability are driven by disease severity, timing, and assay

  1. Michael J. Peluso
  2. Saki Takahashi
  3. Jill Hakim
  4. J. Daniel Kelly
  5. Leonel Torres
  6. Nikita S. Iyer
  7. Keirstinne Turcios
  8. Owen Janson
  9. Sadie E. Munter
  10. Cassandra Thanh
  11. Joanna Donatelli
  12. Christopher C. Nixon
  13. Rebecca Hoh
  14. Viva Tai
  15. Emily A. Fehrman
  16. Yanel Hernandez
  17. Matthew A. Spinelli
  18. Monica Gandhi
  19. Mary-Ann Palafox
  20. Ana Vallari
  21. Mary A. Rodgers
  22. John Prostko
  23. John Hackett
  24. Lan Trinh
  25. Terri Wrin
  26. Christos J. Petropoulos
  27. Charles Y. Chiu
  28. Philip J. Norris
  29. Clara DiGermanio
  30. Mars Stone
  31. Michael P. Busch
  32. Susanna K. Elledge
  33. Xin X. Zhou
  34. James A. Wells
  35. Albert Shu
  36. Theodore W. Kurtz
  37. John E. Pak
  38. Wesley Wu
  39. Peter D. Burbelo
  40. Jeffrey I. Cohen
  41. Rachel L. Rutishauser
  42. Jeffrey N. Martin
  43. Steven G. Deeks
  44. Timothy J. Henrich
  45. Isabel Rodriguez-Barraquer
  46. Bryan Greenhouse

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Abstract

Antibody detection of prior SARS-CoV-2 infection depends on severity, assay, and timing with implications for serosurveillance.

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  1. Version published to 10.1126/sciadv.abh3409
  2. ScreenIT

    SciScore for 10.1101/2021.03.03.21251639: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All volunteers signed informed consents for the study.
    IACUC: Statistical Analyses: Ethical considerations: All participants signed a written informed consent form.
    IRB: The study was approved by the University of California, San Francisco Institutional Review Board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, there are several limitations. The cohort was not population-based and therefore not truly representative of all individuals with SARS-CoV-2 infection. Despite this, we endeavored to recruit a cohort that spanned the spectrum of SARS-CoV-2 infection. Second, this analysis included only a small number of asymptomatic individuals, which are likely to differ from symptomatic patients in terms of initial and possibly longitudinal responses based on our limited data and prior results;11 additional asymptomatic individuals are being recruited for future analyses. Third, the current analysis is limited to samples obtained up to four months after infection. Data from longer follow-up times will be very useful in order to estimate the longer term kinetics of antibody responses in all platforms with more certainty. The assumption of linearity, while empirically appropriate on the time-scales of data that we have here, may not be accurate for extrapolation into the distant future as antibody responses often follow more complex dynamics of boosting and waning over time.28 Finally, it is important to recognize that assays optimally suited for serosurveillance may not be equally suitable for other use-cases, such as identifying recent infection, detecting reinfection, determining protective capacity, or determining potency of COVID-19 convalescent plasma.29 Evaluating the performance of assays for each of these use-cases will require different study designs and sample sets. As SAR...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04362150Active, not recruitingLong-term Impact of Infection With Novel Coronavirus (COVID-…

    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 10.1101/2021.03.03.21251639 on medRxiv