Serological responses to SARS-CoV-2 following non-hospitalised infection: clinical and ethnodemographic features associated with the magnitude of the antibody response

  1. Adrian M Shields
  2. Sian E Faustini
  3. Marisol Perez-Toledo
  4. Sian Jossi
  5. Joel D Allen
  6. Saly Al-Taei
  7. Claire Backhouse
  8. Lynsey A Dunbar
  9. Daniel Ebanks
  10. Beena Emmanuel
  11. Aduragbemi A Faniyi
  12. Mark Garvey
  13. Annabel Grinbergs
  14. Golaleh McGinnell
  15. Joanne O'Neill
  16. Yasunori Watanabe
  17. Max Crispin
  18. David C Wraith
  19. Adam F Cunningham
  20. Mark T Drayson
  21. Alex G Richter

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Abstract

To determine clinical and ethnodemographic correlates of serological responses against the SARS-CoV-2 spike glycoprotein following mild-to-moderate COVID-19.

Design

A retrospective cohort study of healthcare workers who had self-isolated due to COVID-19.

Setting

University Hospitals Birmingham NHS Foundation Trust, UK (UHBFT).

Participants

956 healthcare workers were recruited by open invitation via UHBFT trust email and social media between 27 April 2020 and the 8 June 2020.

Intervention

Participants volunteered a venous blood sample that was tested for the presence of anti-SARS-CoV-2 spike glycoprotein antibodies. Results were interpreted in the context of the symptoms of their original illness and ethnodemographic variables.

Results

Using an assay that simultaneously measures the combined IgG, IgA and IgM response against the spike glycoprotein (IgGAM), the overall seroprevalence within this cohort was 46.2% (n=442/956). The seroprevalence of immunoglobulin isotypes was 36.3%, 18.7% and 8.1% for IgG, IgA and IgM, respectively. IgGAM identified serological responses in 40.6% (n=52/128) of symptomatic individuals who reported a negative SARS-CoV-2 PCR test. Increasing age, non-white ethnicity and obesity were independently associated with greater IgG antibody response against the spike glycoprotein. Self-reported fever and fatigue were associated with greater IgG and IgA responses against the spike glycoprotein. The combination of fever and/or cough and/or anosmia had a positive predictive value of 92.3% for seropositivity in self-isolating individuals a time when Wuhan strain SARS-CoV-2 was predominant.

Conclusions and relevance

Assays employing combined antibody detection demonstrate enhanced seroepidemiological sensitivity and can detect prior viral exposure even when PCR swabs have been negative. We demonstrate an association between known ethnodemographic risk factors associated with mortality from COVID-19 and the magnitude of serological responses in mild-to-moderate disease.

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  1. Version published to 10.1136/bmjresp-2020-000872
  2. ScreenIT

    SciScore for 10.1101/2020.11.12.20230763: (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 the London - Camden & Kings Cross Research Ethics Committee reference 20/HRA/1817.
    Consent: All participants provided written, informed consent prior to enrolment in the study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    All individuals volunteered a venous blood sample that was tested for anti-SARS-CoV-2 spike glycoprotein antibodies using a commercially available IgGAM ELISA that measures the total antibody response (Product code: MK654, The Binding Site (TBS), Birmingham).
    anti-SARS-CoV-2 spike glycoprotein
    suggested: None
    TBS anti-SARS-CoV-2 spike plates were also used to assess individual IgG, IgA, and IgM antibodies.
    IgM
    suggested: None
    Antibodies were detected using sheep-anti-human HRP-conjugated polyclonal antibodies against IgG (1:16,000), IgA (1:2000), and IgM (1:8000) (TBS, UK).
    HRP-conjugated polyclonal antibodies against IgG
    suggested: (GeneTex Cat# GTX29106, RRID:AB_369669)
    IgA
    suggested: None
    The relationship between age, body mass index (BMI), and antibody responses was considered using Pearson’s correlation coefficient.
    BMI
    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: We detected the following sentences addressing limitations in the study:
    Furthermore, these data highlight potential limitations in PCR testing to confirm acute COVID-19. Only 26.6% of symptomatic individuals received a PCR test highlighting the lack of available testing during the first-wave of the COVID-19 pandemic. However, an antibody response was detectable in 40.6% of symptomatic individuals who tested negative by PCR, although the magnitude of this response was significantly less than those who tested PCR positive. This was not explained by differences in the time allowed for maturation of the antibody response which was equivalent between the groups, but notably, patients who tested PCR negative reported, on average, fewer symptoms than those who tested PCR positive. Previous studies have demonstrated the upper respiratory tract viral load, estimated by PCR cycle threshold values, is equivalent in asymptomatic and symptomatic individuals [32]. These data would support a hypothesis that some individuals may experience fewer symptoms because they achieve more rapid immunological control over viral replication; this in turn may narrow the window of PCR positivity and highlight potential end-to-end operational insensitivities when PCR is used for the detection of mild disease. Such issues have previously been highlighted in more seriously unwell hospitalised patients [33, 34] and must be very carefully considered when PCR is used as the gold-standard diagnostic reference point to assess the performance of other molecular and serological assays...

    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 10.1101/2020.11.12.20230763v1 on medRxiv