Clinical Variables Correlate with Serum Neutralizing Antibody Titers after COVID-19 mRNA Vaccination in an Adult, US-based Population

  1. Min Zhao
  2. Rebecca Slotkin
  3. Amar H. Sheth
  4. Lauren Pischel
  5. Tassos C. Kyriakides
  6. Brinda Emu
  7. Cynthia McNamara
  8. Qiaosu Shi
  9. Jaden Delgobbo
  10. Jin Xu
  11. Elizabeth Marhoffer
  12. Aleagia Mercer-Falkoff
  13. Jürgen Holleck
  14. David Ardito
  15. Richard E. Sutton
  16. Shaili Gupta

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Abstract

Background

We studied whether comorbid conditions impact strength and duration of immune responses after SARS-CoV-2 mRNA vaccination in a US-based, adult population.

Methods

Sera (pre-and-post-BNT162b2 vaccination) were tested serially up to 12 months after two doses of vaccine for SARS-CoV-2-anti-Spike neutralizing capacity by pseudotyping assay in 124 individuals; neutralizing titers were correlated to clinical variables with multivariate regression. Post-booster (third dose) effect was measured at 1 and 3 months in 72 and 88 subjects respectively.

Results

After completion of primary vaccine series, neutralizing antibody IC50 values were high at one month (14-fold increase from pre-vaccination), declined at six months (3.3-fold increase), and increased at one month post-booster (41.5-fold increase). Three months post-booster, IC50 decreased in COVID-naïve individuals (18-fold increase) and increased in prior COVID-19+ individuals (132-fold increase). Age >65 years (β=-0.94, p=0.001) and malignancy (β=-0.88, p=0.002) reduced strength of response at 1 month. Both strength and durability of response at 6 months, respectively, were negatively impacted by end-stage renal disease [(β=-1.10, p=0.004); (β=-0.66, p=0.014)], diabetes mellitus [(β=-0.57, p=0.032); (β=-0.44, p=0.028)], and systemic steroid use [(β=-0.066, p=0.032); (β=-0.55, p=0.037)]. Post-booster IC50 was robust against WA-1 and B.1.617.2, but the immune response decreased with malignancy (β =-0.68, p=0.03) and increased with prior COVID-19 (p-value < 0.0001).

Conclusion

Multiple clinical factors impact the strength and duration of neutralization response post-primary series vaccination, but not the post-booster dose strength. Prior COVID-19 infection enhances the booster-dose response except in individuals with malignancy, suggesting a need for clinically guiding vaccine dosing regimens.

Summary

Multiple clinical factors impact the strength and duration of neutralization response post-primary series vaccination. All subjects, irrespective of prior COVID infection, benefited from a third dose. Malignancy decreased response following third dose, suggesting the importance of clinically guided vaccine regimens.

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  1. ScreenIT

    SciScore for 10.1101/2022.04.03.22273355: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Renal function was calculated by estimating glomerular filtration rate (GFR) by using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.22 2.2 Ethics: The study was approved by the Institutional Review Board at the VACHS.
    Consent: Written informed consent was obtained from each participant.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    2.3 Evaluation of anti-SARS-CoV-2 neutralizing antibodies: Sera were tested for neutralization activity against SARS-CoV-2 using a single cycle infectivity assay with Spike-pseudotyped virus particles as described previously.
    anti-SARS-CoV-2
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    These pseudotyped particles were titered on 293T-hACE2 cells seeded in 96 well plates.
    293T-hACE2
    suggested: None
    Software and Algorithms
    SentencesResources
    Curve-fitting using GraphPad PRISM was employed to calculate the neutralization titer half-maximal inhibitory concentration (IC-50 value) for each sample at each time-point.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    PRISM
    suggested: (PRISM, RRID:SCR_005375)
    2.5 Visualizations: All univariate association figures were created using the Python package seaborn.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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 study has some important limitations. Our sample size is relatively small, and similar clinical correlations in larger samples may better inform vaccine responses based upon select clinical variables. We evaluated the neutralizing antibody titers over a six month time period after completion of the primary vaccine series. Evaluation beyond that time point in individuals who did not receive the booster dose may reveal further associations between clinical variables and duration of response. Similarly, we defined strength of the response based on the highest level of IC-50 obtained by each individual. Since the time-points when we collected samples were predetermined, it is possible that the true peak response occurs before or after the 1 month time-point. While this may affect the fold-change values, it will likely not alter the correlation of strength of response with clinical factors. Another limitation of our study is that we excluded subjects from statistical analysis if they had known history of COVID-19 before vaccination. The number of these subjects in our study was too small (13) to conduct multiple regression analysis. Further investigation of clinical factors that associate with vaccine responses in individuals with prior SARS-CoV-2 infection would be valuable, especially when compared with those who were not previously infected. Lastly, this work does not include memory B-cell and memory T-cell responses and how those correlate to clinical factors and IC-50 va...

    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.

  2. Version published to 10.1101/2022.04.03.22273355 on medRxiv