Differential Influence of Age on the Relationship between Genetic Mismatch and A(H1N1)pdm09 Vaccine Effectiveness

Abstract

Assessment of influenza vaccine effectiveness (VE) and identification of relevant influencing factors are the current priorities for optimizing vaccines to reduce the impacts of influenza. To date, how the difference between epidemic strains and vaccine strains at genetic scale affects age-specific vaccine performance remains ambiguous. This study investigated the association between genetic mismatch on hemagglutinin and neuraminidase genes and A(H1N1)pdm09 VE in different age groups with a novel computational approach. We found significant linear relationships between VE and genetic mismatch in children, young adults, and middle-aged adults. In the children’s group, each 3-key amino acid mutation was associated with an average of 10% decrease in vaccine effectiveness in a given epidemic season, and genetic mismatch exerted no influence on VE for the elderly group. We demonstrated that present vaccines were most effective for children, while protection for the elderly was reduced and indifferent to vaccine component updates. Modeling such relationships is practical to inform timely evaluation of VE in different groups of populations during mass vaccination and may inform age-specific vaccination regimens.

Improving in silico prediction of influenza vaccine effectiveness by genome analysis incorporating epitope information

“…The HA and NA protein sequences in the United States were collected for model building and genetic data in the United Kingdom, Germany and Hong Kong were collected for validation. The vaccine effectiveness data were extracted from published epidemiological studies and described in the supplementary materials of Cao et al 2021 5,6 . The influenza vaccine strains recommended by WHO for use in the northern hemisphere were summarized in supplement materials Table S1 .…”

“…Previously, we developed a novel computational framework to predict VE for the influenza 5,6 and COVID-19 7 vaccine by virus sequencing data. We found that genetic distance (GD) between vaccine strains and circulating viruses is significantly correlated with vaccine effectiveness (VE).…”

Rapid evaluation of COVID-19 vaccine effectiveness against VOC/VOIs by genetic mismatch

“…In this study, we drew the connection between genetic mismatch of circulating SARS-CoV-2 viruses and reported COVID-19 VE from population studies. Based on previous bioinformatics approach established for the influenza viruses 16,17 , we further advanced the VE estimation framework for COVID-19 by controlling the clustered random variation of technology platforms using a mixed-effects model. Through extensive analysis of worldwide VE studies and genetic sequences, we showed that a significant proportion of the change in VE could be explained by the genetic factor and provided an efficient framework to evaluate vaccine protection.…”