Predictors for reactogenicity and humoral immunity to SARS-CoV-2 following infection and mRNA vaccination: A regularized, mixed-effects modelling approach
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Abstract
The influence of pre-existing humoral immunity, inter-individual demographic factors, and vaccine-associated reactogenicity on immunogenicity following COVID vaccination remains poorly understood.
Methods
Ten-fold cross-validated least absolute shrinkage and selection operator (LASSO) and linear mixed effects models were used to evaluate symptoms experienced by COVID+ participants during natural infection and following SARS-CoV-2 mRNA vaccination along with demographics as predictors for antibody (AB) responses to recombinant spike protein in a longitudinal cohort study.
Results
In previously infected individuals (n=33), AB were more durable and robust following primary vaccination when compared to natural infection alone. Higher AB were associated with experiencing dyspnea during natural infection, as was the total number of symptoms reported during the COVID-19 disease course. Both local and systemic symptoms following 1 st and 2 nd dose (n=49 and 48, respectively) of SARS-CoV-2 mRNA vaccines were predictive of higher AB after vaccination. Lastly, there was a significant temporal relationship between AB and days since infection or vaccination, suggesting that vaccination in COVID+ individuals is associated with a more robust immune response.
Discussion
Experiencing systemic and local symptoms post-vaccine was suggestive of higher AB, which may confer greater protection.
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SciScore for 10.1101/2022.04.05.22273450: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Following the written informed consent process, participants answered questions detailing their demographics, lifestyle habits, past medical history (including COVID-19), and COVID-19 infection symptoms. Sex as a biological variable not detected. Randomization The selected predictors from each of the best-fitting cross-validated LASSO models were then included as fixed effects in follow-up LMMs with by-participant random intercepts, allowing us to control for individual differences. Blinding not detected. Power Analysis not detected. Table 2: Resources
Antibodies Sentences Resources Plates were washed three times with 0.1% PBST followed by addition of a 1:3,000 dilution of goat anti-human … SciScore for 10.1101/2022.04.05.22273450: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Following the written informed consent process, participants answered questions detailing their demographics, lifestyle habits, past medical history (including COVID-19), and COVID-19 infection symptoms. Sex as a biological variable not detected. Randomization The selected predictors from each of the best-fitting cross-validated LASSO models were then included as fixed effects in follow-up LMMs with by-participant random intercepts, allowing us to control for individual differences. Blinding not detected. Power Analysis not detected. Table 2: Resources
Antibodies Sentences Resources Plates were washed three times with 0.1% PBST followed by addition of a 1:3,000 dilution of goat anti-human IgG–horseradish peroxidase (HRP) conjugated secondary antibody (50μl) well and incubated 1h. anti-human IgG–horseradishsuggested: NoneSoftware and Algorithms Sentences Resources Plots were produced using the ggplot2 [30]. ggplot2suggested: (ggplot2, RRID:SCR_014601)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:Our study has several limitations. Sample sizes for each cohort examined were small due to variability in vaccination timelines and participant scheduling. Some individuals were excluded due to a confounding effect on our predictive modeling, which is controlled by the fixed effect of time. The natural infection group was further limited by the study timeline, as the first SARS-CoV-2 vaccination became available shortly after enrollment began and therefore limited the number of individuals we were able to follow longitudinally. Additionally, our analysis only included quantitative antibody binding titers. Although recent work has demonstrated that higher binding antibodies correlate to higher neutralizing antibodies [13], expansive, multi-center longitudinal studies are needed. An ideal analysis would consist of a multivariate analysis of reactogenicity, demographics, and quantitatively characterized antibody, B-cell and T-cell responses, as immune protection seems to be contingent on all three tiers of the immune response [50]. Further, some of the predictors used in our statistical analysis were found to be significant in one test but not in post-hoc tests. Large, longitudinal studies are required to confirm a significant group difference, but the predictors utilized herein should be included in future analyses. Our bivariate analysis of symptoms experienced following the 1st and 2nd doses failed to demonstrate that individual symptoms can influence peak antibody titers fol...
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.
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