Abstract
The strength and breadth of an individual’s antibody repertoire is an important predictor of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), A/H3N2 priming inoculation and post-vaccination A/H1N1 inoculation. We fit models with various immunological mechanisms that have been empirically observed but have not previously been included in mathematical models of antibody landscapes, including: titre ceiling effects, antigenic seniority and exposure-type specific cross reactivity. Based on the parameter estimates of the best supported models, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Either antigenic seniority or a titre ceiling effect were included in the two best fitting models, suggesting a role for a mechanism describing diminishing antibody boosting with repeated exposures. Although there was considerable uncertainty in our estimates of antibody waning parameters, our results suggest that both short and long term waning were present and would be identifiable with a larger set of experiments. These results highlight the potential use of repeat exposure animal models in revealing short-term, strain-specific immune dynamics of influenza.
Highlights
Natural infection with influenza stimulates a complex and multifaceted immune response to neutralise and clear the infection [1]
Predicting how an individual’s antibody profile will change following exposure is useful for evaluating which populations are at greatest risk and how effective vaccination strategies might be
We developed a mathematical model to describe shortterm antibody kinetics that are important in building an individual’s immune profile but are difficult to observe in human populations
Summary
Natural infection with influenza stimulates a complex and multifaceted immune response to neutralise and clear the infection [1]. Influenza is an antigenically variable virus and undergoes continual antigenic drift, whereby mutations in immunodominant epitopes are selected by immunological pressure, allowing influenza lineages to escape population herd immunity [8,9,10]. This results in the continual loss of long-term immunity as antibodies effective against past strains fail to neutralise novel variants [11]. The current strategy for combating antigenic drift is to regularly update the seasonal influenza vaccine to better represent circulating strains, resulting in a competition between virus and vaccine formulation. There has been a recent push towards a universal influenza vaccination strategy, either through new vaccines or improved strength and breadth of immunity using existing technologies [14, 15]
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