Abstract

SARS-CoV-2 lipid nanoparticle mRNA vaccines continue to be administered as the predominant prophylactic measure to reduce COVID-19 disease pathogenesis. Quantifying the kinetics of the secondary immune response from subsequent doses beyond the primary series and understanding how dose-dependent immune waning kinetics vary as a function of age, sex, and various comorbidities remains an important question. We study anti-spike IgG waning kinetics in 152 individuals who received an mRNA-based primary series (first two doses) and a subset of 137 individuals who then received an mRNA-based booster dose. We find the booster dose elicits a 71–84% increase in the median Anti-S half life over that of the primary series. We find the Anti-S half life for both primary series and booster doses decreases with age. However, we stress that although chronological age continues to be a good proxy for vaccine-induced humoral waning, immunosenescence is likely not the mechanism, rather, more likely the mechanism is related to the presence of noncommunicable diseases, which also accumulate with age, that affect immune regulation. We are able to independently reproduce recent observations that those with pre-existing asthma exhibit a stronger primary series humoral response to vaccination than compared to those that do not, and further, we find this result is sustained for the booster dose. Finally, via a single-variate Kruskal-Wallis test we find no difference between male and female humoral decay kinetics, however, a multivariate approach utilizing  Least Absolute Shrinkage and Selection Operator (LASSO) regression for feature selection reveals a statistically significant (p<1×10-3), albeit small, bias in favour of longer-lasting humoral immunity amongst males.

Details

Title
SARS-CoV-2 booster vaccine dose significantly extends humoral immune response half-life beyond the primary series
Author
Korosec, Chapin S. 1 ; Dick, David W. 1 ; Moyles, Iain R. 1 ; Watmough, James 2 

 York University, Modelling Infection and Immunity Lab, Mathematics and Statistics, Toronto, Canada (GRID:grid.21100.32) (ISNI:0000 0004 1936 9430); York University, Centre for Disease Modelling, Mathematics and Statistics, Toronto, Canada (GRID:grid.21100.32) (ISNI:0000 0004 1936 9430) 
 University of New Brunswick, Department of Mathematics and Statistics, Fredericton, Canada (GRID:grid.266820.8) (ISNI:0000 0004 0402 6152) 
Pages
8426
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3041022775
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.