SARS-CoV-2 responsive T cell numbers and anti-Spike IgG levels are both associated with protection from COVID-19: A prospective cohort study in keyworkers

  1. David Wyllie
  2. Hayley E Jones
  3. Ranya Mulchandani
  4. Adam Trickey
  5. Sian Taylor-Phillips
  6. Tim Brooks
  7. Andre Charlett
  8. AE Ades
  9. EDSAB-HOME investigators
  10. Philippa Moore
  11. John Boyes
  12. Anil Hormis
  13. Neil Todd
  14. Ian Reckless
  15. Andrew Makin
  16. Isabel Oliver

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Immune correlates of protection from COVID-19 are incompletely understood. 2,826 keyworkers had T-SPOT ® Discovery SARS-CoV-2 tests (measuring interferon-γ secreting, SARS-CoV-2 responsive T cells, Oxford Immunotec Ltd), and anti-Spike S1 domain IgG antibody levels (EuroImmun AG) performed on recruitment into a cohort study. 285/2,826 (10.1%) of participants had positive SARS-CoV-2 RT-PCR tests, predominantly associated with symptomatic illness, during 200 days followup. T cell responses to Spike, Nucleoprotein and Matrix proteins (SNM responses) were detected in some participants at recruitment, as were anti-Spike S1 IgG antibodies; higher levels of both were associated with protection from subsequent SARS-CoV-2 test positivity. In volunteers with moderate antibody responses, who represented 39% (252/654) of those with detectable anti-Spike IgG, protection was partial, and higher with higher circulating T cell SNM responses. SARS-CoV-2 responsive T cell numbers predict protection in individuals with low anti-Spike IgG responses; serology alone underestimates the proportion of the population protected after infection.

Article activity feed

  3. Version published to 10.1101/2020.11.02.20222778v2 on medRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.11.02.20222778: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationAdditionally, results obtained from any individuals tested as part of national surveillance studies of randomly selected asymptomatic individuals were excluded, since the positive predictive value of results is much lower in the absence of symptoms(26).
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot 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: We detected the following sentences addressing limitations in the study:
    There are several limitations. First, numbers of individuals developing illness during follow-up remain small at present, with about 0.7% of those followed up developing illness. While disease acquisition is associated with T-SPOT SNM results (p=0.007), we cannot precisely quantify the T cell number / protection relationship. The 12 spot cutoff used here was selected since it discriminates individuals at low risk of SARS-CoV-2 from those with proven past COVID-19 disease, but it is not necessarily optimally predictive of disease risk going forward. We plan on publishing updated analyses as case numbers rise which may help address this, while also permitting co-modelling of disease risk using clinical COVID-19 risk factors (e.g. age, ethnicity (1-4)). Secondly, we counted circulating SARS-CoV-2 responsive interferon-γ secreting cells, but did not phenotype them (16), and so may have missed prognostic immunophenotypes and mucosally restricted T-cell populations. Finally, we only measured symptomatic COVID-19 infection; we did not investigate asymptomatic infection (which may be important for transmission, and over which immune control is at present uncertain (20)). We considered potential confounders of the association we observed. Participants knew their symptom history and antibody status; seropositive or previously symptomatic participants may have been more likely to allow themselves to be exposed to SARS-CoV-2. Secondly, some individuals may have been infected without bein...

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

    IdentifierStatusTitle
    ISRCTN5660922NANA
    ISRCTN56609224NANA

    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.

  5. Version published to 10.1101/2020.11.02.20222778v1 on medRxiv