Health care worker seromonitoring reveals complex relationships between common coronavirus antibodies and COVID-19 symptom duration

  1. Sigrid Gouma
  2. Madison E. Weirick
  3. Marcus J. Bolton
  4. Claudia P. Arevalo
  5. Eileen C. Goodwin
  6. Elizabeth M. Anderson
  7. Christopher M. McAllister
  8. Shannon R. Christensen
  9. Debora Dunbar
  10. Danielle Fiore
  11. Amanda Brock
  12. JoEllen Weaver
  13. John Millar
  14. Stephanie DerOhannessian
  15. The UPenn COVID Processing Unit
  16. Ian Frank
  17. Daniel J. Rader
  18. E. John Wherry
  19. Scott E. Hensley

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Some studies suggest that recent common coronavirus (CCV) infections are associated with reduced COVID-19 severity upon SARS-CoV-2 infection. We completed serological assays using samples collected from health care workers to identify antibody types associated with SARS-CoV-2 protection and COVID-19 symptom duration. Rare SARS-CoV-2 cross-reactive antibodies elicited by past CCV infections were not associated with protection; however, the duration of symptoms following SARS-CoV-2 infections was significantly reduced in individuals with higher common betacoronavirus (βCoV) antibody titers. Since antibody titers decline over time after CCV infections, individuals in our cohort with higher βCoV antibody titers were more likely recently infected with common βCoVs compared with individuals with lower antibody titers. Therefore, our data suggest that recent βCoV infections potentially limit the duration of symptoms following SARS-CoV-2 infections through mechanisms that do not involve cross-reactive antibodies. Our data are consistent with the emerging hypothesis that cellular immune responses elicited by recent common βCoV infections transiently reduce symptom duration following SARS-CoV-2 infections.

Article activity feed

  1. Version published to 10.1172/jci.insight.150449
  2. ScreenIT

    SciScore for 10.1101/2021.04.12.21255324: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: We collected serum samples from each participant and quantified SARS-CoV-2 S-RBD antibodies by ELISAs within 36-48 hours after sample collection.
    Consent: Informed consent was collected from all participants prior to the baseline visit.
    IRB: This study was approved by the Institutional Review Board of the University of Pennsylvania under IRB #842847.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    We collected NP swabs from all health care workers who possessed SARS-CoV-2 S-RBD IgG and/or IgM antibodies and we completed SARS-CoV-2 PCR testing on these samples to identify active or recent infections.
    IgM
    suggested: None
    Enzyme-linked immunosorbent assay (ELISA): ELISAs measuring antibodies against SARS-CoV-2 and against OC43, HKU1, 229E and NL63 were completed as previously described (13).
    OC43
    suggested: (Virostat Cat# 3879, RRID:AB_2889994)
    HKU1
    suggested: None
    After 2 hours of incubation, plates were washed with PBS-T and 50 μL of 1:5,000 diluted goat anti-human IgG-HRP (Jackson ImmunoResearch Laboratories) or 1:1,000 diluted goat anti-human IgM-HRP (SouthernBiotech) was added to each well.
    anti-human IgG-HRP
    suggested: None
    Plasmids to express the CR3022 monoclonal antibody were provided by Ian Wilson (Scripps).
    CR3022
    suggested: None
    SARS-CoV-2 S-RBD antibody concentrations below this cutoff at 0.48 arbitrary units/mL were assigned a value of 0.40 arbitrary units/mL.
    SARS-CoV-2 S-RBD
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    SARS-CoV-2 S-FL and S-RBD were produced in 293F cells and purified using Ni-NTA (Qiagen).
    293F
    suggested: RRID:CVCL_D615)
    Software and Algorithms
    SentencesResources
    Prism version 9 (GraphPad) and R version 3.5.3 were used for analyses.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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 10.1101/2021.04.12.21255324 on medRxiv