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Integrating influenza antigenic dynamics with molecular evolution.

Trevor Bedford1, Marc A Suchard, Philippe Lemey

  • 1Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom.

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Summary
This summary is machine-generated.

Influenza viruses evolve antigenically, leading to immune evasion. This study models antigenic and genetic evolution together, revealing influenza A/H3N2 evolves faster and drives disease incidence.

Keywords:
Bayesian inferenceantigenic cartographyevolutioninfluenzamultidimensional scalingphylogenetics

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Area of Science:

  • Virology
  • Immunology
  • Computational Biology

Background:

  • Influenza viruses continuously evolve antigenically, enabling them to evade pre-existing host immunity.
  • The hemagglutination inhibition (HI) assay is commonly used to measure antigenic cross-reactivity between influenza strains.

Purpose of the Study:

  • To simultaneously characterize the antigenic and genetic evolution of influenza viruses.
  • To model the diffusion of antigenic phenotype across a shared viral phylogeny.
  • To investigate the relationship between antigenic drift and influenza incidence patterns.

Main Methods:

  • Extended antigenic cartography methods to integrate genetic and antigenic data.
  • Modeled antigenic phenotype diffusion over a virus phylogeny.
  • Utilized hemagglutination inhibition (HI) data from influenza lineages A/H3N2, A/H1N1, B/Victoria, and B/Yamagata.

Main Results:

  • Demonstrated that influenza A/H3N2 exhibits faster and more punctuated antigenic evolution compared to other lineages.
  • Showed a correlation between year-to-year antigenic drift and influenza incidence patterns within lineages.
  • Developed a novel model integrating molecular and antigenic evolution for influenza viruses.

Conclusions:

  • Antigenic drift in influenza viruses significantly impacts their evolutionary dynamics and disease spread.
  • Influenza A/H3N2 displays distinct evolutionary characteristics warranting specific attention.
  • The integrated model provides a powerful framework for studying antigenically variable pathogens.