How Heterogeneous Antibody Immunity Shapes Strain Evolution

A new study found that person-to-person heterogeneity in antibody immunity influences which influenza (flu) strains dominate in a population.

Published as a Reviewed Preprint in eLife, the study used a high-throughput sequencing method to examine antibody responses to circulating H₃N₂ flu strains in both children and adults. The editors note that the findings contribute to our understanding of population-level immunity and consider the data to be reliable.

This research may be of interest to immunologists, virologists, vaccine developers, and those involved in mathematical modeling of infectious diseases.

Flu viruses frequently evolve to escape antibodies formed after earlier infections or vaccinations. As a result, people can be infected with influenza multiple times over their lifetimes. Vaccines must also be regularly updated to remain effective. Many factors shape the immune response to flu, including an individual’s history of exposure to different strains.

Differences in infection and vaccination histories within a group of people mean that population immunity to a specific variant of the flu is highly varied. Understanding how this variety in antibodies across a population affects the evolutionary success of new flu strains has remained challenging, in part because conventional methods to quantify antibody levels are too slow and can only assess a handful of samples at a time.”

Caroline Kikawa, Study Co-Lead Author and MD/PhD Student, Department of Genome Sciences, University of Washington

Kikawa was the lead author of the study, alongside Andrea Loes, a staff scientist and lab manager in Jesse Bloom’s lab at the Fred Hutch Cancer Center, Division of Basic Sciences and Computational Biology Program. Bloom served as the senior author.

To address this issue, Kikawa, Loes, and their colleagues developed a high-throughput neutralization assay.

This method allowed them to test how well individual serum samples, which contain antibodies, could block infection by various influenza viruses. “High-throughput” refers to the assay’s ability to process large volumes of data efficiently.

The researchers engineered viruses that expressed 78 distinct hemagglutinin (HA) proteins. These proteins came from flu strains circulating in 2023 and from recent vaccine strains. Each virus included a unique genetic barcode for identification.

HA proteins are targeted by antibodies and are known to change frequently, allowing the virus to escape immune detection. The researchers mixed these viruses with serum samples and used Illumina sequencing to determine how effectively each virus was neutralized.

They measured neutralization titers—the amount of serum required to block infection—using 150 serum samples from children and adults in the United States. These samples were collected in 2023. In total, they obtained more than 11,000 individual titer measurements. This provided a detailed view of population immunity at the beginning of the 2023–2024 flu season.

The results showed significant variation in individual immune responses. Some serum samples from children neutralized nearly all tested flu strains, while others had much weaker responses. Adults tended to have more consistent immunity, but there was still noticeable variation between individuals.

The strongest neutralization responses were observed in a subset of children. This supports the idea that antibody responses are most robust to strains encountered earlier in life. It is also possible that children experience flu more frequently and therefore receive more immune stimulation. These findings highlight the highly individual nature of influenza immunity.

To understand how this variation affects viral evolution, the researchers compared neutralization titers with the growth rates of different flu strains during the 2023 season. They applied a statistical method called multinomial logistic regression to analyze how the frequency of each strain changed over time. This was compared to the proportion of serum samples with low neutralization titers for each strain.

The results showed that strains that spread more widely tended to be poorly neutralized by a large share of the samples. In other words, flu viruses were more likely to spread when fewer people had strong immunity to them. This suggests that large-scale, sequencing-based neutralization studies can help explain how flu viruses evolve.

This pattern was only visible when neutralization was measured using individual serum samples. It did not appear when samples were pooled. Since some surveillance programs use pooled sera to estimate population immunity, this finding suggests that pooled data may miss important individual-level differences in immune response.

Our findings show that individual-level immune variation, not just average immunity across the population, is a key factor in determining which flu strains are most successful.

Andrea Loes, Staff Scientist and Lab Manager, Fred Hutch Cancer Center

Although the study included a large number of titer measurements, the authors note that the samples came from a limited range of locations and age groups. Most of the child samples were collected at a hospital in Seattle, while adult samples were obtained from vaccinated cohorts in Philadelphia and Australia. Because of this, the dataset may not fully represent global patterns of influenza immunity.

This is, nevertheless, one of the largest datasets linking human antibody immunity to the success of flu virus strains in a population. It provides a framework for understanding how diverse immune histories can affect viral evolution. These methods could complement existing surveillance systems and support vaccine composition decisions by providing more detailed insights into population immunity.”

Jesse Bloom, Senior Author and Professor, Basic Sciences Division and Herbold Computational Biology Program, Fred Hutch Cancer Center

Bloom is also an Affiliate Professor of Genome Sciences at the University of Washington.