Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors in two UK longitudinal studies

  1. Nathan J Cheetham
  2. Milla Kibble
  3. Andrew Wong
  4. Richard J Silverwood
  5. Anika Knuppel
  6. Dylan M Williams
  7. Olivia KL Hamilton
  8. Paul H Lee
  9. Charis Bridger Staatz
  10. Giorgio Di Gessa
  11. Jingmin Zhu
  12. Srinivasa Vittal Katikireddi
  13. George B Ploubidis
  14. Ellen J Thompson
  15. Ruth CE Bowyer
  16. Xinyuan Zhang
  17. Golboo Abbasian
  18. Maria Paz Garcia
  19. Deborah Hart
  20. Jeffrey Seow
  21. Carl Graham
  22. Neophytos Kouphou
  23. Sam Acors
  24. Michael H Malim
  25. Ruth E Mitchell
  26. Kate Northstone
  27. Daniel Major-Smith
  28. Sarah Matthews
  29. Thomas Breeze
  30. Michael Crawford
  31. Lynn Molloy
  32. Alex SF Kwong
  33. Katie Doores
  34. Nishi Chaturvedi
  35. Emma L Duncan
  36. Nicholas J Timpson
  37. Claire J Steves

  • Curated by eLife

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    eLife assessment

    The authors collected and analyzed blood samples from >9,000 participants from two cross-sectional cohort studies in the UK, the ALSPAC cohort and the TwinsUK cohort. They measured anti-Nucleocapsid and anti-Spike antibodies using the collected blood samples. They investigated the variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination. They identify that following the third vaccination, risk factors associated with low antibody response after the first vaccination are less likely to lead to sub-protective levels. While this finding is of potential importance, the presentation of the data is diffuse and not focused at times, and more discussion is needed to highlight its relevance to the current stage of the pandemic.

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. Higher levels of SARS-CoV-2 anti-Spike antibodies are known to be associated with increased protection against future SARS-CoV-2 infection. However, variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination have not been explored across a wide range of socio-demographic, SARS-CoV-2 infection and vaccination, and health factors within population-based cohorts.

Methods:

Samples were collected from 9361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies and tested for SARS-CoV-2 antibodies. Cross-sectional sampling was undertaken jointly in April-May 2021 (TwinsUK, N=4256; ALSPAC, N=4622), and in TwinsUK only in November 2021-January 2022 (N=3575). Variation in antibody levels after first, second, and third SARS-CoV-2 vaccination with health, socio-demographic, SARS-CoV-2 infection, and SARS-CoV-2 vaccination variables were analysed. Using multivariable logistic regression models, we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection, and SARS-CoV-2 vaccination variables.

Results:

Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had threefold greater odds of SARS-CoV-2 infection over the next 6–9 months (OR = 2.9, 95% CI: 1.4, 6.0), compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK ‘Shielded Patient List’ had consistently greater odds (two- to fourfold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations.

Conclusions:

These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies.

Funding:

Antibody testing was funded by UK Health Security Agency. The National Core Studies program is funded by COVID-19 Longitudinal Health and Wellbeing – National Core Study (LHW-NCS) HMT/UKRI/MRC ([MC_PC_20030] and [MC_PC_20059]). Related funding was also provided by the NIHR 606 (CONVALESCENCE grant [COV-LT-0009]). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. The UK Medical Research Council and Wellcome (Grant ref: [217065/Z/19/Z]) and the University of Bristol provide core support for ALSPAC.

Article activity feed

  1. Version published to 10.7554/elife.80428 on eLife
  2. eLife

    eLife assessment

    The authors collected and analyzed blood samples from >9,000 participants from two cross-sectional cohort studies in the UK, the ALSPAC cohort and the TwinsUK cohort. They measured anti-Nucleocapsid and anti-Spike antibodies using the collected blood samples. They investigated the variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination. They identify that following the third vaccination, risk factors associated with low antibody response after the first vaccination are less likely to lead to sub-protective levels. While this finding is of potential importance, the presentation of the data is diffuse and not focused at times, and more discussion is needed to highlight its relevance to the current stage of the pandemic.

  3. eLife

    Reviewer #1 (Public Review):

    This paper uses 2 cohorts from the UK and links a) risk factors associated with low antibody levels after vaccination and b) risk factors for infection. The paper makes the important point that following the third vaccination, risk factors associated with low antibody response after the first vaccination, are less likely to lead to sub-protective levels. This highlights the importance of obtaining a booster shot. Though it is not a primary finding of the paper, the observed discordance between self-reported infection and anti-nucleocapsid positivity is an important finding. While these findings are potentially useful, the presentation of the data is somewhat unfocused, and the message is presented in a diffuse fashion. Moreover, certain key components of the analysis such as the assay threshold and timing of samples after the 2nd vaccine are a bit confusing and require clarification. The use of univariate analyses can be misleading. Finally, the relevance of the findings relative to our current stage of the pandemic with multiple new VOCs requires a clearer explication.

  4. eLife

    Reviewer #2 (Public Review):

    In this study, the authors collected and analyzed blood samples from >9,000 participants from two cross-sectional cohort studies in the UK. The ALSPAC cohort only collected data during April and May 2021, whereas the TwinsUK cohort collected data during April and May 2021 and November 2021 to January 2022. They measured anti-Nucleocapsid and anti-Spike antibodies using the collected blood samples. They investigated the variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination across a wide range of socio-demographic, SARS-CoV-2 infection and vaccination, and health factors. Alongside the descriptive analysis, the authors performed some multivariable regression analysis.

  5. ScreenIT

    SciScore for 10.1101/2022.05.19.22275214: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableALSPAC is a prospective population-based cohort of pregnant women with expected delivery dates between April 1991 and December 1992 who lived in Bristol, UK and the nearby surrounding area; with follow-up of these women and their partners (collectively known as Generation 0, G0), and their children (Generation 1, G1), ever since [34,35].
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    In addition to the above criteria, for analysis of variables associated with post-vaccination infection within TwinsUK, individuals must have participated in Q2 antibody testing followed by either Q4 antibody testing and/or concurrent COVID-19 questionnaire.
    Q4
    suggested: None
    Questionnaires administered during the COVID-19 pandemic: TwinsUK COVID-19 questionnaires were administered in April-May 2020 [51], July-August 2020, October-December 2020, April-July 2021 (approximating first round of antibody testing, Q2), and November 2021-February 2022 (approximating second round of antibody testing, Q4).
    Q2
    suggested: None
    Quantitative IgG anti-Spike SARS-CoV-2 antibody levels and qualitative IgG anti-Nucleocapsid antibody status were assayed using CE-marked capillary blood Roche Elecsys Anti-SARS-CoV-2 immunoassays [59].
    anti-Spike SARS-CoV-2
    suggested: None
    Quantitative enzyme-linked immunosorbent (ELISA) assays testing anti-Nucleocapsid and anti-Spike antibody levels were performed using previously published methods [4].
    anti-Nucleocapsid
    suggested: None
    Multivariable models testing associations with low anti-Spike antibody levels used the following set of adjustment variables: age, sex, most recent vaccine received and number of weeks since most recent vaccination.
    anti-Spike
    suggested: None
    Software and Algorithms
    SentencesResources
    ALSPAC analyses were performed using python v3.9.7 and packages: numpy v1.20.3, pandas v1.3.4, matplotlib v3.4.3, and seaborn v0.11.2, and R v4.1.2 [81] and packages: plyr v1.8.6, dplyr v1.0.7 and broom v0.7.11.
    python
    suggested: (IPython, RRID:SCR_001658)
    matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)

    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:
    This exposes a limitation to our analytical approach, as we have limited scale and power to examine the intersection of likely risk factors in combination. Further, of the several variables associated with antibody levels, only serology-based evidence of prior SARS-CoV-2 infection was directly associated (here, negatively associated) with subsequent post-vaccination infection between April-May 2021 and November 2021-January 2022 (with the majority sampled before the peak of the current Omicron wave). We found no consistent associations of lower antibody levels with age or employment status, but a very strong age gradient (lower incidence with older age) and lower likelihood among retired (vs. employed) individuals of post-vaccination infection. These results again are consistent with risk of infection being a complex combination of SARS-CoV-2 case prevalence, individual immune response to vaccination, and individual level of exposure (i.e., behaviour). Such aspects often oppose each other by design (for example, higher shielding behaviours by more elderly individuals). Nevertheless, given the ongoing relaxation of measures across many countries, groups previously less exposed may become more at risk. Consequently, our findings regarding factors associated with post-vaccination infection may change over time, to align more closely with variables identified as associated with lower antibody levels. Longitudinal antibody testing within TwinsUK at Q4 highlighted the effectiveness...

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  6. Version published to 10.1101/2022.05.19.22275214v1 on medRxiv