Antibody landscapes after influenza virus infection or vaccination

Vaccination against influenza viruses annually: Renewing or narrowing the protective shield?

Annual vaccines are recommended for the seasonal influenza virus. While yearly updates to the vaccine are necessary due to the constant evolution of influenza viruses, some studies have suggested repeat vaccination may result in a reduction in vaccine effectiveness in subsequent years. This review examines the available evidence that repeated annual influenza virus vaccination may have effects on future vaccine responses, and it synthesizes the available data with studies that may indicate potential immunological mechanisms underlying these effects. The goal is to examine the available literature to determine whether these mechanisms can be subverted to improve seasonal influenza virus vaccine efficacy.

Leveraging pre-vaccination antibody titres across multiple influenza H3N2 variants to forecast the post-vaccination response

BACKGROUND

Despite decades of research on the influenza virus, we still lack a predictive understanding of how vaccination reshapes each person's antibody response, which impedes efforts to design better vaccines. Models using pre-vaccination antibody haemagglutination inhibition (HAI) titres against the vaccine strain alone poorly predict post-vaccination responses.

METHODS

We combined fifteen prior H3N2 influenza vaccine studies from 1997 to 2021, collectively containing 20,000 data points, and develop of a machine learning model that uses pre-vaccination HAI titres against multiple influenza variants to predict post-vaccination responses. To further test the model, four new vaccine studies were conducted in 2022-2023 spanning two geographic locations and three influenza vaccine types.

FINDINGS

The most predictive pre-vaccination features were HAI titres against the vaccine strain and against historical influenza variants, with smaller predictive power derived from age, sex, vaccine dose, and geographic location. The resulting model predicted future responses even when the vaccine strain or vaccine formulation changed. A pre-vaccination feature-the time between peak HAI across recent variants-distinguished large versus small post-vaccination responses with 73% accuracy. Model predictions against prior vaccine studies had 2.4-fold error (95% CI: 2.34-2.40x, no large outliers with >4-fold error), yielding more accurate and robust predictions than a null model with 3.2-fold error (95% CI: 3.12-3.21x, 12% large outliers). The four new vaccine studies presented here were predicted with comparable accuracy to the intrinsic 2-fold error of the experimental assay.

INTERPRETATION

A person's pre-vaccination influenza HAI titres using multiple variants are highly predictive of their post-vaccination response. Many individuals exhibited little-to-no vaccine response, as exhibited by the null model's accuracy, yet the machine learning model identified and accurately predicted both weak and strong responses with statistical superiority. Taken together, this approach paves the way to better utilise current influenza vaccines, especially for individuals that exhibit the weakest responses.

FUNDING

NIAID, UCSD PREPARE Institute, LJI & Kyowa Kirin, Inc. (KKNA-Kyowa Kirin North America), UGA, Cleveland Clinic, the Georgia Research Alliance, and the Bodman family.

Predicting immune protection against outcomes of infectious disease from population-level effectiveness data with application to COVID-19

Quantifying the extent to which previous infections and vaccinations confer protection against future infection or disease outcomes is critical to managing the transmission and consequences of infectious diseases. We present a general statistical model for predicting the strength of protection conferred by different immunising exposures (numbers, types, and strains of both vaccines and infections), against multiple outcomes of interest, whilst accounting for immune waning. We predict immune protection against key clinical outcomes: developing symptoms, hospitalisation, and death. We also predict transmission-related outcomes: acquisition of infection and onward transmission in breakthrough infections. These enable quantification of the impact of immunity on population-level transmission dynamics. Our model calibrates the level of immune protection, drawing on both population-level data, such as vaccine effectiveness estimates, and neutralising antibody levels as a correlate of protection. This enables the model to learn realised immunity levels beyond those which can be predicted by antibody kinetics or other correlates alone. We demonstrate an application of the model for SARS-CoV-2, and predict the individual-level protective effectiveness conferred by natural infections with the Delta and the Omicron B.1.1.529 variants, and by the BioNTech-Pfizer (BNT162b2), Oxford-AstraZeneca (ChAdOx1), and 3rd-dose mRNA booster vaccines, against outcomes for both Delta and Omicron. We also demonstrate a use case of the model in late 2021 during the emergence of Omicron, showing how the model can be rapidly updated with emerging epidemiological data on multiple variants in the same population, to infer key immunogenicity and intrinsic transmissibility characteristics of the new variant, before the former can be more directly observed via vaccine effectiveness data. This model provided timely inference on rapidly evolving epidemic situations of significant concern during the early stages of the COVID-19 pandemic. The general nature of the model enables it to be used to support management of a range of infectious diseases.

Immunological drivers of zoonotic virus emergence, evolution, and endemicity

The disruption of natural ecosystems caused by climate change and human activity is amplifying the risk of zoonotic spillover, presenting a growing global health threat. In the past two decades, the emergence of multiple zoonotic viruses has exposed critical gaps in our ability to predict epidemic trajectories and implement effective interventions. RNA viruses, in particular, are challenging to control due to their high mutation rates and ability to adapt and evade immune defenses. To better prepare for future outbreaks, it is vital that we deepen our understanding of the factors driving viral emergence, transmission, and persistence in human populations. Specifically, deciphering the interactions between antibody-mediated immunity and viral evolution will be key. In this perspective, we explore these dynamic relationships and highlight research priorities that may guide the development of more effective strategies to mitigate the impact of emerging infectious diseases.

High-throughput neutralization measurements correlate strongly with evolutionary success of human influenza strains

Human influenza viruses rapidly acquire mutations in their hemagglutinin (HA) protein that erode neutralization by antibodies from prior exposures. Here, we use a sequencing-based assay to measure neutralization titers for 78 recent H3N2 HA strains against a large set of children and adult sera, measuring ~10,000 total titers. There is substantial person-to-person heterogeneity in the titers against different viral strains, both within and across age cohorts. The growth rates of H3N2 strains in the human population in 2023 are highly correlated with the fraction of sera with low titers against each strain. Notably, strain growth rates are less correlated with neutralization titers against pools of human sera, demonstrating the importance of population heterogeneity in shaping viral evolution. Overall, these results suggest that high-throughput neutralization measurements of human sera against many different viral strains can help explain the evolution of human influenza.

Antigenic drift expands influenza viral escape pathways from recalled humoral immunity

Initial exposure to a rapidly evolving virus establishes B cell memory that biases later responses to antigenically drifted strains. This "immune imprinting" implies that subsequent exposure to a drifted strain can induce affinity maturation of memory B cells toward cross-reactivity with the drifted strain and hence toward greater overall breadth. Here, we used deep mutational scanning of H1 influenza hemagglutinins (HAs) to investigate how viruses evolve in response to these broad antibody response. We identified escape mutations from clonal antibody lineages that targeted the receptor binding site and lateral patch. By adjusting the antigen-antibody contacts, antibody affinity maturation restricted the potential escape routes for the eliciting strain. However, escape occurred readily in drifted strains. We attribute this escape-prone property of the drifted strains to epistatic networks within HA. Our data explain how the influenza virus continues to evolve in the human population by escaping even broad antibody responses.

Characterizing the Short- and Long-Term Temporal Dynamics of Antibody Responses to Influenza Vaccination

Most influenza vaccine studies evaluate acute antibody responses 1 month post-vaccination, leaving long-term immunity poorly understood. Here, we performed a combined analysis of 14 large-scale vaccine studies and conducted two new studies mapping antibody responses in high resolution from their inception out to 1 year post-vaccination. Vaccine antibody responses were classified as weak (<4x fold-change at 1 month and 1 year), transient (≥4x at 1 month, <4x at 1 year), or durable (≥4x at 1 month and 1 year). Surprisingly, >50% of vaccine recipients were weak across seasons, age groups, sexes, pre-vaccination titers, and high or standard vaccine doses. Peak fold-change at 1 month post-vaccination was strongly associated with the long-term response, with most transient responders achieving a maximum fold-change of 4x, while most durable responders reached ≥16x, with both groups maintaining these titers for 2 months (10-75 days post-vaccination). Using the weak, transient, and durable trajectories, a single time point early in the response (days 7-8 or 21) predicted an individual's response out to 1 year post-vaccination. These results demonstrate that influenza vaccine responses range from little-to-no response to eliciting strong-and-durable immunity, highlighting the stark heterogeneity that is consistently seen across influenza seasons.

A Transgenic Mouse With a Humanized B-Cell Repertoire Mounts an Antibody Response to Influenza Infection and Vaccination

The development of a universal influenza vaccine likely requires an understanding of previous exposure to influenza virus (through vaccination or infection) and how that shapes the antibody repertoire to vaccination, sometimes called original antigenic sin or antigenic imprinting. While animal models can have a much more defined exposure history, they lack a human B-cell repertoire. Transgenic mice with the complete human immunoglobulin locus enable studies of controlled infection history leading to human-like antibody evolution. Here we evaluated responses to influenza in the Intelliselect transgenic mouse (the Kymouse). We show the Kymouse is susceptible to disease following infection with either H1N1, H3N2, or B/Yamagata influenza viruses and that it induces a robust binding and neutralizing antibody response to all 3 strains of influenza virus. This study demonstrates that human B-cell repertoire mice can be used for influenza virus studies, providing a tool for further interrogation of the antibody response.

Continuous Tracking for Effective Tackling: Ad5/35 Platform-Based JN1 Lineage Vaccines Development in Response to Evolving SARS-CoV-2 Variants

The SARS-CoV-2 virus is continuously evolving, such that JN.1 and its subvariants, including KP.2, KP.3, and LB.1, are now predominant variants globally. JN.1 is derived from BA.2.86, which harbors more than 30 mutations in the spike protein compared with those of XBB and BA.2, and it carries an additional L455S mutation. Given the rapid evolution of these variants, assessing the neutralization capacity of current JN.1 lineage vaccines against prevalent variants, such as KP.3, is critical. Phylogenetic trees using spike protein sequences and antigenic cartography based on neutralization results reveal that JN.1 lineage variants are antigenically distant from previously circulating variants. Moreover, JN.1 subvariants showed inadequate neutralization titers compared with other variants against XBB.1.5-containing vaccine in mice. Immunization with vaccines targeting the JN.1, KP.2, KP.3, and LB.1 variants demonstrated significant neutralizing activity against predominant variants in mice. These results highlight the importance of vaccine development to keep pace with the evolution of SARS-CoV-2 variants and the need for updated vaccines targeting the JN.1 variant.

Differential antigenic imprinting effects between influenza H1N1 hemagglutinin and neuraminidase in a mouse model

Understanding how immune history influences influenza immunity is essential for developing effective vaccines and therapeutic strategies. This study examines the antigenic imprinting of influenza hemagglutinin (HA) and neuraminidase (NA) using a mouse model with sequential infections by H1N1 virus strains exhibiting substantial antigenic differences in HA. In our pre-2009 influenza infection model, we observed that mice with more extensive infection histories produced higher levels of functional NA-inhibiting antibodies (NAI). However, following further infection with the 2009 pandemic H1N1 strain, these mice demonstrated a reduced NAI to the challenged virus. Interestingly, prior exposure to older strains resulted in a lower HA antibody response (neutralization and HAI) to the challenged virus in both pre- and post-2009 scenarios, potentially due to faster viral clearance facilitated by immune memory recall. Overall, our findings reveal distinct trajectories in HA and NA immune responses, suggesting that immune imprinting can differentially impact these proteins based on the extent of antigenic variation in influenza viruses.

IMPORTANCE

Influenza viruses continue to pose a significant threat to human health, with vaccine effectiveness remaining a persistent challenge. Individual immune history is a crucial factor that can influence antibody responses to subsequent influenza exposures. While many studies have explored how pre-existing antibodies shape the induction of anti-HA antibodies following influenza virus infections or vaccinations, the impact on anti-NA antibodies has been less extensively studied. Using a mouse model, our study demonstrates that within pre-2009 H1N1 strains, an extensive immune history negatively impacted anti-HA antibody responses but enhanced anti-NA antibody responses. However, in response to the 2009 pandemic H1N1 strain, which experienced an antigenic shift, both anti-HA and anti-NA antibody responses were hindered by antibodies from prior pre-2009 H1N1 virus infections. These findings provide important insights into how antigenic imprinting affects both anti-HA and anti-NA antibody responses and underscore the need to consider immune history in developing more effective influenza vaccination strategies.

Pre-pandemic cross-reactive antibody and cellular responses against SARS-CoV-2 among female sex workers in Dakar, Senegal

Background

The COVID-19 pandemic had a severe impact globally, yet African populations exhibited unexpectedly lower rates of severe disease and mortality. We investigated the potential role of pre-existing immunity in shaping the epidemiology of COVID-19 in Africa.

Methods

Plasma collected from Senegalese female sex workers prior to the COVID-19 pandemic was screened for SARS-CoV-2 and human coronavirus (hCoV) antibodies by virion immunoblots. For antibody-reactive plasma, paired peripheral blood mononuclear cells were stimulated by fusion proteins and IFN-γ cellular responses were assessed via ELISPOT.

Results

We observed substantial levels of pre-existing cross-reactive immunity to SARS-CoV-2, stemming from prior exposure to seasonal hCoVs. Our antibody analysis revealed a 23.5% (47/200) seroprevalence rate against SARS-CoV-2 nucleocapsid (N). These samples were then probed for antibodies against hCoV spike (S) and/or N antigens; 85.1% (40/47), 70.2% (33/47), and 95.7% (45/47) were antibody reactive against hCoV-229E, hCoV-OC43, or hCoV-HKU1, respectively. Our analysis of cellular responses also demonstrated cross-reactivity to SARS-CoV-2 with 80.0% (36/45) and 82.2% (37/45) showing IFN-γ responses against S and N, respectively. A unique pre-pandemic subject had cross-reactive SARS-CoV-2 S antibodies with detectable neutralization and cross-reactive cellular responses.

Conclusion

These findings suggest that prior hCoV exposure may induce cross-reactive adaptive immunity, potentially contributing to protection against COVID-19. Our study provides unique data on the dynamics of hCoV and SARS-CoV-2 immunity in Senegal and underscores the importance of understanding the role of pre-existing immunity in shaping COVID-19 outcomes globally.

Antibody responses against influenza A decline with successive years of annual influenza vaccination

Influenza vaccine effectiveness and immunogenicity can be compromised with repeated vaccination. We assessed immunological markers in a cohort of healthcare workers (HCW) from six public hospitals around Australia during 2020-2021. Sera were collected pre-vaccination and ~14 and ~180 days post-vaccination and assessed in haemagglutination inhibition assay against egg-grown vaccine and equivalent cell-grown viruses. Responses to vaccination were compared by the number of prior vaccinations. Baseline sera were available for 595 HCW in 2020 and 1031 in 2021. 5% had not been vaccinated during five years prior to enrolment and 55% had been vaccinated every year. Post-vaccination titres for all vaccine antigens were lowest among HCW vaccinated in all 5-prior years and highest among HCW with 0 or 1 prior vaccinations, even after adjustment. This was observed for both influenza A subtypes and was dependent on pre-vaccination titre. Expanded cohorts are needed to better understand how this translates to vaccine effectiveness.

Evolution of Omicron lineage towards increased fitness in the upper respiratory tract in the absence of severe lung pathology

The emergence of the Omicron lineage represented a major genetic drift in SARS-CoV-2 evolution. This was associated with phenotypic changes including evasion of pre-existing immunity and decreased disease severity. Continuous evolution within the Omicron lineage raised concerns of potential increased transmissibility and/or disease severity. To address this, we evaluate the fitness and pathogenesis of contemporary Omicron variants XBB.1.5, XBB.1.16, EG.5.1, and JN.1 in the upper (URT) and lower respiratory tract (LRT). We compare in vivo infection in Syrian hamsters with infection in primary human nasal and lung epithelium cells and assess differences in transmissibility, antigenicity, and innate immune activation. Omicron variants replicate efficiently in the URT but display limited pathology in the lungs compared to previous variants and fail to replicate in human lung organoids. JN.1 is attenuated in both URT and LRT compared to other Omicron variants and fails to transmit in the male hamster model. Our data demonstrate that Omicron lineage evolution has favored increased fitness in the URT.

Distinct evolution patterns of influenza viruses and implications for vaccine development

In conclusion, the distinct evolution patterns of panzootic influenza A(H5Nx) compared to A(H1N1) and A(H3N2) complicate vaccine development. Effective strategies must consider these unique patterns and the impact of pre-existing immunity. Leveraging AI-based methods for optimized antigen design is essential to mitigate the potential impact of emerging antigenically variable strains and will provide valuable insights for developing more effective vaccines to prepare for future pandemics.

Concepts and Methods for Predicting Viral Evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein hemagglutinin targeted by human antibodies. Here, we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to 1 year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available at https://previr.app .

Immune imprinting: The persisting influence of the first antigenic encounter with rapidly evolving viruses

Immune imprinting is a phenomenon that stems from the fundamentals of immunological memory. Upon recurrent exposures to an evolving pathogen, the immune system must weigh the benefits of rapidly recalling established antibody repertoires with greater affinity to the initial variant or invest additional time and energy in producing de novo responses specific to the emerging variant. In this review, we delve into the mechanistic complexities of immune imprinting and its role in shaping subsequent immune responses, both de novo and recall, against rapidly evolving respiratory viruses such as influenza and coronaviruses. By exploring the duality of immune imprinting, we examine its potential to both enhance or hinder immune protection against disease, while emphasizing the role of host and viral factors. Finally, we explore how different vaccine platforms may affect immune imprinting and comment on vaccine strategies that can favor de novo variant-specific antibody responses.

Eco-evolutionary dynamics of adapting pathogens and host immunity

As pathogens spread in a population of hosts, immunity is built up, and the pool of susceptible individuals are depleted. This generates selective pressure, to which many human RNA viruses, such as influenza virus or SARS-CoV-2, respond with rapid antigenic evolution and frequent emergence of immune evasive variants. However, the host's immune systems adapt, and older immune responses wane, such that escape variants only enjoy a growth advantage for a limited time. If variant growth dynamics and reshaping of host-immunity operate on comparable time scales, viral adaptation is determined by eco-evolutionary interactions that are not captured by models of rapid evolution in a fixed environment. Here, we use a Susceptible/Infected model to describe the interaction between an evolving viral population in a dynamic but immunologically diverse host population. We show that depending on strain cross-immunity, heterogeneity of the host population, and durability of immune responses, escape variants initially grow exponentially, but lose their growth advantage before reaching high frequencies. Their subsequent dynamics follows an anomalous random walk determined by future escape variants and results in variant trajectories that are unpredictable. This model can explain the apparent contradiction between the clearly adaptive nature of antigenic evolution and the quasi-neutral dynamics of high-frequency variants observed for influenza viruses.

Coupling antigens from multiple subtypes of influenza can broaden antibody and T cell responses

The seasonal influenza vaccine contains strains of viruses from distinct subtypes that are grown independently and then combined. However, most individuals exhibit a more robust response to one of these strains and thus are vulnerable to infection by others. By studying a monozygotic twin cohort, we found that although prior exposure is a factor, host genetics are a stronger driver of subtype bias to influenza viral strains. We found that covalent coupling of heterologous hemagglutinin (HA) from different viral strains could largely eliminate subtype bias in an animal model and in a human tonsil organoid system. We proposed that coupling of heterologous antigens improves antibody responses across influenza strains by broadening T cell help, and we found that using this approach substantially improved the antibody response to avian influenza HA.

A Global Collaborative Comparison of SARS-CoV-2 Antigenicity Across 15 Laboratories

Setting up a global SARS-CoV-2 surveillance system requires an understanding of how virus isolation and propagation practices, use of animal or human sera, and different neutralisation assay platforms influence assessment of SARS-CoV-2 antigenicity. In this study, with the contribution of 15 independent laboratories across all WHO regions, we carried out a controlled analysis of neutralisation assay platforms using the first WHO International Standard for antibodies to SARS-CoV-2 variants of concern (source: NIBSC). Live virus isolates (source: WHO BioHub or individual labs) or spike plasmids (individual labs) for pseudovirus production were used to perform neutralisation assays using the same serum panels. When comparing fold drops, excellent data consistency was observed across the labs using common reagents, including between pseudovirus and live virus neutralisation assays (RMSD of data from mean fold drop was 0.59). Utilising a Bayesian model, geometric mean titres and assay titre magnitudes (offsets) can describe the data efficiently. Titre magnitudes were seen to vary largely even for labs within the same assay group. We have observed that overall, live Microneutralisation assays tend to have the lowest titres, whereas Pseudovirus Neutralisation have the highest (with a mean difference of 3.2 log2 units between the two). These findings are relevant for laboratory networks, such as the WHO Coronavirus Laboratory Network (CoViNet), that seek to support a global surveillance system for evolution and antigenic characterisation of variants to support monitoring of population immunity and vaccine composition policy.

A platform for the rapid screening of equine immunoglobins F (ab)2 derived from single equine memory B cells able to cross-neutralize to influenza virus

Single B cells-based antibody platforms offer an effective approach for the discovery of useful antibodies for therapeutic or research purposes. Here we present a method for screening equine immunoglobins F(ab)2, which offers the potential advantage of reacting with multiple epitopes on the virus. Using equine influenza virus (EIV) as model, a hemagglutinin (HA) trimer was constructed to bait B cells in vaccinated horses. We screened 370 HA-specific B cells from 1 × 106 PBMCs and identified a diverse set of equine variable region gene sequences of heavy and light chains and then recombined with humanized Ig Fc. Recombinant equine Ig was then self-assembled in co-transfected 293 T cells, and subsequently optimized to obtain HA binding B-cell receptor (s). The recombinant antibodies exhibited a high binding affinity to the HA protein. Antibody H81 exhibited the highest cross neutralizing activities against EIV strains in vitro. Furthermore, it effectively protected EIV-challenged mice, resulting in significantly improved survival, reduced pulmonary inflammation and decreased viral titers. In silico predication identified a functional region of H81 comprising 27 key amino acids cross the main circulating EIV strains. The 12 amino acid residues in this region with the highest binding affinities were screened. Notably, the predicted epitopes of H81 encompassed the documented equine HA receptor binding site, validating its cross-neutralization. In summary, a rapid platform was successfully established to investigate the profiling of equine antigen-recognizing receptors (BCRs) following infection. This platform has the potential to optimize the screening of virus-neutralizing antibodies and aid in vaccine design.

Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data

We present a review and primer of methods to understand epidemiological dynamics and identify past exposures from serological data, referred to as serodynamics. We discuss processing and interpreting serological data prior to fitting serodynamical models, and review approaches for estimating epidemiological trends and past exposures, ranging from serocatalytic models applied to binary serostatus data, to more complex models incorporating quantitative antibody measurements and immunological understanding. Although these methods are seemingly disparate, we demonstrate how they are derived within a common mathematical framework. Finally, we discuss key areas for methodological development to improve scientific discovery and public health insights in seroepidemiology.

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app.

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app.

Human and hamster sera correlate well in identifying antigenic drift among SARS-CoV-2 variants, including JN.1

Antigenic assessments of SARS-CoV-2 variants inform decisions to update COVID-19 vaccines. Primary infection sera are often used for assessments, but such sera are rare due to population immunity from SARS-CoV-2 infections and COVID-19 vaccinations. Here, we show that neutralization titers and breadth of matched human and hamster pre-Omicron variant primary infection sera correlate well and generate similar antigenic maps. The hamster antigenic map shows modest antigenic drift among XBB sub-lineage variants, with JN.1 and BA.4/BA.5 variants within the XBB cluster, but with fivefold to sixfold antigenic differences between these variants and XBB.1.5. Compared to sera following only ancestral or bivalent COVID-19 vaccinations, or with post-vaccination infections, XBB.1.5 booster sera had the broadest neutralization against XBB sub-lineage variants, although a fivefold titer difference was still observed between JN.1 and XBB.1.5 variants. These findings suggest that antibody coverage of antigenically divergent JN.1 could be improved with a matched vaccine antigen.IMPORTANCEUpdates to COVID-19 vaccine antigens depend on assessing how much vaccine antigens differ antigenically from newer SARS-CoV-2 variants. Human sera from single variant infections are ideal for discriminating antigenic differences among variants, but such primary infection sera are now rare due to high population immunity. It remains unclear whether sera from experimentally infected animals could substitute for human sera for antigenic assessments. This report shows that neutralization titers of variant-matched human and hamster primary infection sera correlate well and recognize variants similarly, indicating that hamster sera can be a proxy for human sera for antigenic assessments. We further show that human sera following an XBB.1.5 booster vaccine broadly neutralized XBB sub-lineage variants but titers were fivefold lower against the more recent JN.1 variant. These findings support updating the current COVID-19 vaccine variant composition and developing a framework for assessing antigenic differences in future variants using hamster primary infection sera.

Multi-strain modeling of influenza vaccine effectiveness in older adults and its dependence on antigenic distance

Influenza vaccine effectiveness (VE) varies seasonally due to host, virus and vaccine characteristics. To investigate how antigenic matching and dosage impact VE, we developed a mechanistic knowledge-based mathematical model. Immunization with a split vaccine is modeled for exposure to A/H1N1 or A/H3N2 virus strains. The model accounts for cross-reactivity of immune cells elicited during previous immunizations with new antigens. We simulated vaccine effectiveness (sVE) of high dose (HD) versus standard dose (SD) vaccines in the older population, from 2011 to 2022. We find that sVE is highly dependent on antigenic matching and that higher dosage improves immunogenicity, activation and memory formation of immune cells. In alignment with clinical observations, the HD vaccine performs better than the SD vaccine in all simulations, supporting the use of the HD vaccine in the older population. This model could be adapted to predict the impact of alternative virus strain selection on clinical outcomes in future influenza seasons.

Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course

Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology in humans remains unclear. Here, we used a multilevel mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns in humans and to investigate how influenza incidence varies over time, space, and age in this population. We estimated median annual influenza infection rates to be approximately 19% from 1968 to 2015, but with substantial variation between years; 88% of individuals were estimated to have been infected at least once during the study period (2009 to 2015), and 20% were estimated to have 3 or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long-term epidemiological trends, within-host processes, and immunity when analysed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.

mRNA vaccines for infectious diseases - advances, challenges and opportunities

The concept of mRNA-based vaccines emerged more than three decades ago. Groundbreaking discoveries and technological advancements over the past 20 years have resolved the major roadblocks that initially delayed application of this new vaccine modality. The rapid development of nucleoside-modified COVID-19 mRNA vaccines demonstrated that this immunization platform is easy to develop, has an acceptable safety profile and can be produced at a large scale. The flexibility and ease of antigen design have enabled mRNA vaccines to enter development for a wide range of viruses as well as for various bacteria and parasites. However, gaps in our knowledge limit the development of next-generation mRNA vaccines with increased potency and safety. A deeper understanding of the mechanisms of action of mRNA vaccines, application of novel technologies enabling rational antigen design, and innovative vaccine delivery strategies and vaccination regimens will likely yield potent novel vaccines against a wide range of pathogens.

Vaccination against rapidly evolving pathogens and the entanglements of memory

Immune memory determines infection risk and responses to future infections and vaccinations over potentially decades of life. Despite its centrality, the dynamics of memory to antigenically variable pathogens remains poorly understood. This Review examines how past exposures shape B cell responses to vaccinations with influenza and SARS-CoV-2. An overriding feature of vaccinations with these pathogens is the recall of primary responses, often termed 'imprinting' or 'original antigenic sin'. These recalled responses can inhibit the generation of new responses unless some incompletely defined conditions are met. Depending on the context, immune memory can increase or decrease the total neutralizing antibody response to variant antigens, with apparent consequences for protection. These effects are easier to measure experimentally than epidemiologically, but there is evidence that both early and recent exposures influence vaccine effectiveness. A few immunological interactions between adaptive immune responses and antigens might explain the seemingly discrepant effects of memory. Overall, the complex observations point to a need for more quantitative approaches to integrate high-dimensional immune data from populations with diverse exposure histories. Such approaches could help identify optimal vaccination strategies against antigenically diverse pathogens.

Measures of population immunity can predict the dominant clade of influenza A (H3N2) in the 2017-2018 season and reveal age-associated differences in susceptibility and antibody-binding specificity

Background

For antigenically variable pathogens such as influenza, strain fitness is partly determined by the relative availability of hosts susceptible to infection with that strain compared to others. Antibodies to the hemagglutinin (HA) and neuraminidase (NA) confer substantial protection against influenza infection. We asked if a cross-sectional antibody-derived estimate of population susceptibility to different clades of influenza A (H3N2) could predict the success of clades in the following season.

Methods

We collected sera from 483 healthy individuals aged 1 to 90 years in the summer of 2017 and analyzed neutralizing responses to the HA and NA of representative strains using Focus Reduction Neutralization Tests (FNRT) and Enzyme-Linked Lectin Assays (ELLA). We estimated relative population-average and age-specific susceptibilities to circulating viral clades and compared those estimates to changes in clade frequencies in the following 2017-18 season.

Results

The clade to which neutralizing antibody titers were lowest, indicating greater population susceptibility, dominated the next season. Titer correlations between viral strains varied by age, suggesting age-associated differences in epitope targeting driven by shared past exposures. Yet substantial unexplained variation remains within age groups.

Conclusions

This study indicates how representative measures of population immunity might improve evolutionary forecasts and inform selective pressures on influenza.

Reverse zoonotic transmission of human seasonal influenza to a pig herd in Sweden

In January 2023, a Swedish piglet-producing farm with 2800 sows in production (SIP) was diagnosed with IAV (Influenza A virus) and the isolates were shown to cluster with the human seasonal influenza (2022/2023). In December 2022, employees with flu like symptoms tended to the pigs and a few weeks later, respiratory signs appeared in different age groups; sows in farrowing units were anorectic and pyrectic. Lung and nasal swabs were tested positive for IAV and other respiratory infectious agents. Blanket vaccination against H1N1pdm09 of sows and gilts was initiated but discontinued for sows after 2 treatments. Biosecurity measures aiming to reduce the spread of virus were implemented. However, the compliance to follow the protocol was moderate.Combining immunity and strict sanitary measures is crucial to control virus circulation. As the farmer discontinued sow vaccination and just partly increased biosecurity, this may have contributed to ongoing virus circulation and clinical signs in pigs, even 5 months post-diagnosis. Although H1N1pdm09 already had been found in the herd in 2017, there were no clinical signs or diagnostic results indicating continuous circulation of this or other IAV strains afterwards. However, this cannot be entirely excluded. Swine IAVs pose a risk of reintroduction into the human population, highlighting the importance of vaccination of farm workers against seasonal influenza.

B-cell characteristics define HCV reinfection outcome

BACKGROUND & AIMS

In individuals highly exposed to HCV, reinfection is common, suggesting that natural development of sterilising immunity is difficult. In those that are reinfected, some will develop a persistent infection, while a small proportion repeatedly clear the virus, suggesting natural protection is possible. The aim of this study was to characterise immune responses associated with rapid natural clearance of HCV reinfection.

METHODS

Broad neutralising antibodies (nAbs) and Envelope 2 (E2)-specific memory B cell (MBC) responses were examined longitudinally in 15 individuals with varied reinfection outcomes.

RESULTS

Broad nAb responses were associated with MBC recall, but not with clearance of reinfection. Strong evidence of antigen imprinting was found, and the B-cell receptor repertoire showed a high level of clonality with ongoing somatic hypermutation of many clones over subsequent reinfection events. Single-cell transcriptomic analyses showed that cleared reinfections featured an activated transcriptomic profile in HCV-specific B cells that rapidly expanded upon reinfection.

CONCLUSIONS

MBC quality, but not necessarily breadth of nAb responses, is important for protection against antigenically diverse variants, which is encouraging for HCV vaccine development.

IMPACT AND IMPLICATIONS

HCV continues to have a major health burden globally. Limitations in the health infrastructure for diagnosis and treatment, as well as high rates of reinfection, indicate that a vaccine that can protect against chronic HCV infection will greatly complement current efforts to eliminate HCV-related disease. With alternative approaches to testing vaccines, such as controlled human inoculation trials under consideration, we desperately need to identify the correlates of immune protection. In this study, in a small but rare cohort of high-risk injecting drug users who were reinfected multiple times, breadth of neutralisation was not associated with ultimate clearance of the reinfection event. Alternatively, characteristics of the HCV-specific B-cell response associated with B-cell proliferation were. This study indicates that humoral responses are important for protection and suggests that for genetically very diverse viruses, such as HCV, it may be beneficial to look beyond just antibodies as correlates of protection.

A broad-spectrum vaccine candidate against H5 viruses bearing different sub-clade 2.3.4.4 HA genes

The global spread of H5 clade 2.3.4.4 highly pathogenic avian influenza (HPAI) viruses threatens poultry and public health. The continuous circulation of these viruses has led to their considerable genetic and antigenic evolution, resulting in the formation of eight subclades (2.3.4.4a-h). Here, we examined the antigenic sites that determine the antigenic differences between two H5 vaccine strains, H5-Re8 (clade 2.3.4.4g) and H5-Re11 (clade 2.3.4.4h). Epitope mapping data revealed that all eight identified antigenic sites were located within two classical antigenic regions, with five sites in region A (positions 115, 120, 124, 126, and 140) and three in region B (positions 151, 156, and 185). Through antigenic cartography analysis of mutants with varying numbers of substitutions, we confirmed that a combination of mutations in these eight sites reverses the antigenicity of H5-Re11 to that of H5-Re8, and vice versa. More importantly, our analyses identified H5-Re11_Q115L/R120S/A156T (H5-Re11 + 3) as a promising candidate for a broad-spectrum vaccine, positioned centrally in the antigenic map, and offering potential universal protection against all variants within the clade 2.3.4.4. H5-Re11 + 3 serum has better cross-reactivity than sera generated with other 2.3.4.4 vaccines, and H5-Re11 + 3 vaccine provided 100% protection of chickens against antigenically drifted H5 viruses from various 2.3.4.4 antigenic groups. Our findings suggest that antigenic regions A and B are immunodominant in H5 viruses, and that antigenic cartography-guided vaccine design is a promising strategy for selecting a broad-spectrum vaccine.

Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin

Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population and how this heterogeneity affects virus evolution. Here, we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of two H3N2 strains, A/Hong Kong/45/2019 and A/Perth/16/2009, affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that were fixed in influenza variants after 2020 cause greater escape from sera from younger individuals compared with adults. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups and suggest approaches to understand how this heterogeneous selection shapes viral evolution.

Antigenic cartography using variant-specific hamster sera reveals substantial antigenic variation among Omicron subvariants

Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) has developed substantial antigenic variability. As the majority of the population now has pre-existing immunity due to infection or vaccination, the use of experimentally generated animal immune sera can be valuable for measuring antigenic differences between virus variants. Here, we immunized Syrian hamsters by two successive infections with one of nine SARS-CoV-2 variants. Their sera were titrated against 16 SARS-CoV-2 variants, and the resulting titers were visualized using antigenic cartography. The antigenic map shows a condensed cluster containing all pre-Omicron variants (D614G, Alpha, Delta, Beta, Mu, and an engineered B.1+E484K variant) and considerably more diversity among a selected panel of Omicron subvariants (BA.1, BA.2, BA.4/BA.5, the BA.5 descendants BF.7 and BQ.1.18, the BA.2.75 descendant BN.1.3.1, the BA.2-derived recombinants XBB.2 and EG.5.1, and the BA.2.86 descendant JN.1). Some Omicron subvariants were as antigenically distinct from each other as the wildtype is from the Omicron BA.1 variant. Compared to titers measured in human sera, titers in hamster sera are of higher magnitude, show less fold change, and result in a more compact antigenic map topology. The results highlight the potential of sera from hamsters for the continued antigenic characterization of SARS-CoV-2.

Evaluation of a novel intramuscular prime/intranasal boost vaccination strategy against influenza in the pig model

Live-attenuated influenza vaccines (LAIV) offer advantages over the commonly used inactivated split influenza vaccines. However, finding the optimal balance between sufficient attenuation and immunogenicity has remained a challenge. We recently developed an alternative LAIV based on the 2009 pandemic H1N1 virus with a truncated NS1 protein and lacking PA-X protein expression (NS1(1-126)-ΔPAX). This virus showed a blunted replication and elicited a strong innate immune response. In the present study, we evaluated the efficacy of this vaccine candidate in the porcine animal model as a pertinent in vivo system. Immunization of pigs via the nasal route with the novel NS1(1-126)-ΔPAX LAIV did not cause disease and elicited a strong mucosal immune response that completely blocked replication of the homologous challenge virus in the respiratory tract. However, we observed prolonged shedding of our vaccine candidate from the upper respiratory tract. To improve LAIV safety, we developed a novel prime/boost vaccination strategy combining primary intramuscular immunization with a haemagglutinin-encoding propagation-defective vesicular stomatitis virus (VSV) replicon, followed by a secondary immunization with the NS1(1-126)-ΔPAX LAIV via the nasal route. This two-step immunization procedure significantly reduced LAIV shedding, increased the production of specific serum IgG, neutralizing antibodies, and Th1 memory cells, and resulted in sterilizing immunity against homologous virus challenge. In conclusion, our novel intramuscular prime/intranasal boost regimen interferes with virus shedding and transmission, a feature that will help combat influenza epidemics and pandemics.

Repeated Omicron infection dampens immune imprinting from previous vaccination and induces broad neutralizing antibodies against Omicron sub-variants

OBJECTIVE

Similar with influenza virus, antigenic drift is highly relevant to SARS-CoV-2 evolution, and immune imprinting has been found to limit the performance of updated vaccines based on the emerging variants of SARS-CoV-2. We aimed to investigate whether repeated exposure to Omicron variant could reduce the immune imprinting from previous vaccination.

METHODS

A total of 194 participants with different status of vaccination (unvaccinated, regular vaccination and booster vaccination) confirmed for first infection and re-infection with BA.5, BF.7 and XBB variants were enrolled, and the neutralizing profiles against wild type (WT) SARS-CoV-2 and Omicron sub-variants were analyzed.

RESULTS

Neutralizing potency against the corresponding infected variant is significantly hampered along with the doses of vaccination during first infection. However, for the participants with first infection of BA.5/BF.7 variants and re-infection of XBB variant, immune imprinting was obviously alleviated, indicated as significantly increased ratio of the corresponding infected variant/WT ID50 titers and higher percentage of samples with high neutralizing activities (ID50 > 500) against BA.5, BF.7 and XBB variants. Moreover, repeated Omicron infection could induce strong neutralizing potency with broad neutralizing profiles against a series of other Omicron sub-variants, both in the vaccine naive and vaccine experienced individuals.

CONCLUSIONS

Our results demonstrate that repeated Omicron infection dampens immune imprinting from vaccination with WT SARS-CoV-2 and induces broad neutralizing profiles against Omicron sub-variants.

Immune imprinting in early life shapes cross-reactivity to influenza B virus haemagglutinin

Influenza exposures early in life are believed to shape future susceptibility to influenza infections by imprinting immunological biases that affect cross-reactivity to future influenza viruses. However, direct serological evidence linked to susceptibility is limited. Here we analysed haemagglutination-inhibition titres in 1,451 cross-sectional samples collected between 1992 and 2020, from individuals born between 1917 and 2008, against influenza B virus (IBV) isolates from 1940 to 2021. We included testing of 'future' isolates that circulated after sample collection. We show that immunological biases are conferred by early life IBV infection and result in lineage-specific cross-reactivity of a birth cohort towards future IBV isolates. This translates into differential estimates of susceptibility between birth cohorts towards the B/Yamagata and B/Victoria lineages, predicting lineage-specific birth-cohort distributions of observed medically attended IBV infections. Our data suggest that immunological measurements of imprinting could be important in modelling and predicting virus epidemiology.

Longitudinal assessment of human antibody binding to hemagglutinin elicited by split-inactivated influenza vaccination over six consecutive seasons

Participants between the ages of 10-86 years old were vaccinated with split-inactivated influenza vaccine (Fluzone®) in six consecutive influenza seasons from 2016-2017 to 2021-2022. Vaccine effectiveness varies from season to season as a result of both host immune responses as well as evolutionary changes in the influenza virus surface glycoproteins that provide challenges to vaccine manufacturers to produce more effective annual vaccines. Next generation influenza vaccines are in development and may provide protective immune responses against a broader number of influenza viruses and reduce the need for annual vaccination. An improved understanding how current influenza vaccines are influenced by human host immune responses in people of different ages and co-morbidities is necessary for designing the next-generation of 'universal' or broadly-protective influenza vaccines. Overall, pre-existing immune responses to previous influenza virus exposures, either by past infections or vaccinations, is a critical factor influencing host responses to seasonal influenza vaccination. Participants vaccinated in consecutive seasons had reduced serum hemagglutination-inhibition (HAI) activity against strains included in the vaccine compared to participants that had not been vaccinated in the preceding 1-2 years prior to entering this study. The magnitude and breadth of these antibody responses were also modulated by the age of the participant. Elderly participants over 65 years of age, in general, had lower pre-existing HAI titers each season prior to vaccination with lower post-vaccination titers compared to children or young adults under the age of 35. The administration of higher doses (HD) of the split-inactivated vaccine enhanced the antibody titers in the elderly. This report showcases 6 consecutive years of antibody HAI activity in human subjects receiving seasonal split-inactivated influenza vaccine.

A speed limit on serial strain replacement from original antigenic sin

Many pathogens evolve to escape immunity, yet it remains difficult to predict whether immune pressure will lead to diversification, serial replacement of one variant by another, or more complex patterns. Pathogen strain dynamics are mediated by cross-protective immunity, whereby exposure to one strain partially protects against infection by antigenically diverged strains. There is growing evidence that this protection is influenced by early exposures, a phenomenon referred to as original antigenic sin (OAS) or imprinting. In this paper, we derive constraints on the emergence of the pattern of successive strain replacements demonstrated by influenza, SARS-CoV-2, seasonal coronaviruses, and other pathogens. We find that OAS implies that the limited diversity found with successive strain replacement can only be maintained if [Formula: see text] is less than a threshold set by the characteristic antigenic distances for cross-protection and for the creation of new immune memory. This bound implies a "speed limit" on the evolution of new strains and a minimum variance of the distribution of infecting strains in antigenic space at any time. To carry out this analysis, we develop a theoretical model of pathogen evolution in antigenic space that implements OAS by decoupling the antigenic distances required for protection from infection and strain-specific memory creation. Our results demonstrate that OAS can play an integral role in the emergence of strain structure from host immune dynamics, preventing highly transmissible pathogens from maintaining serial strain replacement without diversification.

Biophysical principles predict fitness of SARS-CoV-2 variants

SARS-CoV-2 employs its spike protein's receptor binding domain (RBD) to enter host cells. The RBD is constantly subjected to immune responses, while requiring efficient binding to host cell receptors for successful infection. However, our understanding of how RBD's biophysical properties contribute to SARS-CoV-2's epidemiological fitness remains largely incomplete. Through a comprehensive approach, comprising large-scale sequence analysis of SARS-CoV-2 variants and the identification of a fitness function based on binding thermodynamics, we unravel the relationship between the biophysical properties of RBD variants and their contribution to viral fitness. We developed a biophysical model that uses statistical mechanics to map the molecular phenotype space, characterized by dissociation constants of RBD to ACE2, LY-CoV016, LY-CoV555, REGN10987, and S309, onto an epistatic fitness landscape. We validate our findings through experimentally measured and machine learning (ML) estimated binding affinities, coupled with infectivity data derived from population-level sequencing. Our analysis reveals that this model effectively predicts the fitness of novel RBD variants and can account for the epistatic interactions among mutations, including explaining the later reversal of Q493R. Our study sheds light on the impact of specific mutations on viral fitness and delivers a tool for predicting the future epidemiological trajectory of previously unseen or emerging low-frequency variants. These insights offer not only greater understanding of viral evolution but also potentially aid in guiding public health decisions in the battle against COVID-19 and future pandemics.

Comparative analysis of SARS-CoV-2 neutralization titers reveals consistency between human and animal model serum and across assays

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires ongoing monitoring to judge the ability of newly arising variants to escape the immune response. A surveillance system necessitates an understanding of differences in neutralization titers measured in different assays and using human and animal serum samples. We compared 18 datasets generated using human, hamster, and mouse serum and six different neutralization assays. Datasets using animal model serum samples showed higher titer magnitudes than datasets using human serum samples in this comparison. Fold change in neutralization of variants compared to ancestral SARS-CoV-2, immunodominance patterns, and antigenic maps were similar among serum samples and assays. Most assays yielded consistent results, except for differences in fold change in cytopathic effect assays. Hamster serum samples were a consistent surrogate for human first-infection serum samples. These results inform the transition of surveillance of SARS-CoV-2 antigenic variation from dependence on human first-infection serum samples to the utilization of serum samples from animal models.

Antigenic Cartography of SARS-CoV-2

Antigenic cartography is a tool for interpreting and visualizing antigenic differences between virus variants based on virus neutralization data. This approach has been successfully used in the selection of influenza vaccine seed strains. With the emergence of SARS-CoV-2 variants escaping vaccine-induced antibody response, adjusting COVID-19 vaccines has become essential. This review provides information on the antigenic differences between SARS-CoV-2 variants revealed by antigenic cartography and explores a potential of antigenic cartography-based methods (e.g., building antibody landscapes and neutralization breadth gain plots) for the quantitative assessment of the breadth of the antibody response. Understanding the antigenic differences of SARS-CoV-2 and the possibilities of the formed humoral immunity aids in the prompt modification of preventative vaccines against COVID-19.

Seroprevalence of Protective Antibodies Against Influenza and the Reduction of the Influenza Incidence Rate: An Annual Repeated Cross-Sectional Study From 2014 to 2019

BACKGROUND

Seroepidemiological studies provide estimates of population-level immunity, prevalence/incidence of infections, and evaluation of vaccination programs. We assessed the seroprevalence of protective antibodies against influenza and evaluated the correlation of seroprevalence with the cumulative annual influenza incidence rate.

METHODS

We conducted an annual repeated cross-sectional seroepidemiological survey, during June-August, from 2014 to 2019, in Portugal. A total of 4326 sera from all age groups, sex, and regions was tested by hemagglutination inhibition assay. Seroprevalence and geometric mean titers (GMT) of protective antibodies against influenza were assessed by age group, sex, and vaccine status (65+ years old). The association between summer annual seroprevalence and the difference of influenza incidence rates between one season and the previous one was measured by Pearson correlation coefficient (r).

RESULTS

Significant differences in seroprevalence of protective antibodies against influenza were observed in the population. Higher seroprevalence and GMT for A(H1N1)pdm09 and A(H3N2) were observed in children (5-14); influenza B seroprevalence in adults 65+ was 1.6-4.4 times than in children (0-4). Vaccinated participants (65+) showed significant higher seroprevalence/GMT for influenza. A strong negative and significant correlation was found between seroprevalence and ILI incidence rate for A(H1N1)pdm09 in children between 5 and 14 (r = -0.84; 95% CI, -0.98 to -0.07); a weak negative correlation was observed for A(H3N2) and B/Yamagata (r ≤ -0.1).

CONCLUSIONS

The study provides new insight into the anti-influenza antibodies seroprevalence measured in summer on the ILI incidence rate in the next season and the need for adjusted preventive health care measures to prevent influenza infection and transmission.

Antigenic distance between primary and secondary dengue infections correlates with disease risk

Many pathogens continuously change their protein structure in response to immune-driven selection, resulting in weakened protection even in previously exposed individuals. In addition, for some pathogens, such as dengue virus, poorly targeted immunity is associated with increased risk of severe disease through a mechanism known as antibody-dependent enhancement. However, it remains unclear whether the antigenic distances between an individual's first infection and subsequent exposures dictate disease risk, explaining the observed large-scale differences in dengue hospitalizations across years. Here, we develop a framework that combines detailed antigenic and genetic characterization of viruses with details on hospitalized cases from 21 years of dengue surveillance in Bangkok, Thailand, to identify the role of the antigenic profile of circulating viruses in determining disease risk. We found that the risk of hospitalization depended on both the specific order of infecting serotypes and the antigenic distance between an individual's primary and secondary infections, with risk maximized at intermediate antigenic distances. These findings suggest that immune imprinting helps determine dengue disease risk and provide a pathway to monitor the changing risk profile of populations and to quantifying risk profiles of candidate vaccines.

A speed limit on serial strain replacement from original antigenic sin

Many pathogens evolve to escape immunity, yet it remains difficult to predict whether immune pressure will lead to diversification, serial replacement of one variant by another, or more complex patterns. Pathogen strain dynamics are mediated by cross-protective immunity, whereby exposure to one strain partially protects against infection by antigenically diverged strains. There is growing evidence that this protection is influenced by early exposures, a phenomenon referred to as original antigenic sin (OAS) or imprinting. In this paper, we derive new constraints on the emergence of the pattern of successive strain replacements demonstrated by influenza, SARS-CoV-2, seasonal coronaviruses, and other pathogens. We find that OAS implies that the limited diversity found with successive strain replacement can only be maintained if R 0 is less than a threshold set by the characteristic antigenic distances for cross-protection and for the creation of new immune memory. This bound implies a "speed limit" on the evolution of new strains and a minimum variance of the distribution of infecting strains in antigenic space at any time. To carry out this analysis, we develop a theoretical model of pathogen evolution in antigenic space that implements OAS by decoupling the antigenic distances required for protection from infection and strain-specific memory creation. Our results demonstrate that OAS can play an integral role in the emergence of strain structure from host immune dynamics, preventing highly transmissible pathogens from maintaining serial strain replacement without diversification.

Cellular and Molecular Immunity to Influenza Viruses and Vaccines

Immune responses to influenza (flu) antigens reflect memory of prior infections or vaccinations, which might influence immunity to new flu antigens. Memory of past antigens has been termed "original antigenic sin" or, more recently, "immune imprinting" and "seniority". We have researched a comparison between the immune response to live flu infections and inactivated flu vaccinations. A brief history of antibody generation theories is presented, culminating in new findings about the immune-network theory and suggesting that a network of clones exists between anti-idiotypic antibodies and T cell receptors. Findings regarding the 2009 pandemic flu strain and immune responses to it are presented, including memory B cells and conserved regions within the hemagglutinin protein. The importance of CD4+ memory T cells and cytotoxic CD8+ T cells responding to both infections and vaccinations are discussed and compared. Innate immune cells, like natural killer (NK) cells and macrophages, are discussed regarding their roles in adaptive immune responses. Antigen presentation via macroautophagy processes is described. New vaccines in development are mentioned along with the results of some clinical trials. The manuscript concludes with how repeated vaccinations are impacting the immune system and a sketch of what might be behind the imprinting phenomenon, including future research directions.

Antigenic cartography using hamster sera identifies SARS-CoV-2 JN.1 evasion seen in human XBB.1.5 booster sera

Antigenic assessments of SARS-CoV-2 variants inform decisions to update COVID-19 vaccines. Primary infection sera are often used for assessments, but such sera are rare due to population immunity from SARS-CoV-2 infections and COVID-19 vaccinations. Here, we show that neutralization titers and breadth of matched human and hamster pre-Omicron variant primary infection sera correlate well and generate similar antigenic maps. The hamster antigenic map shows modest antigenic drift among XBB sub-lineage variants, with JN.1 and BA.4/BA.5 variants within the XBB cluster, but with five to six-fold antigenic differences between these variants and XBB.1.5. Compared to sera following only ancestral or bivalent COVID-19 vaccinations, or with post-vaccination infections, XBB.1.5 booster sera had the broadest neutralization against XBB sub-lineage variants, although a five-fold titer difference was still observed between JN.1 and XBB.1.5 variants. These findings suggest that antibody coverage of antigenically divergent JN.1 could be improved with a matched vaccine antigen.

How immune dynamics shape multi-season epidemics: a continuous-discrete model in one dimensional antigenic space

We extend a previously published model for the dynamics of a single strain of an influenza-like infection. The model incorporates a waning acquired immunity to infection and punctuated antigenic drift of the virus, employing a set of coupled integral equations within a season and a discrete map between seasons. The long term behaviour of the model is demonstrated by examples where immunity to infection depends on the time since a host was last infected, and where immunity depends on the number of times that a host has been infected. The first scenario leads to complicated dynamics in some regions of parameter space, and to regions of parameter space with more than one attractor. The second scenario leads to a stable fixed point, corresponding to an identical epidemic each season. We also examine the model with both paradigms in combination, almost always but not exclusively observing a stable fixed point or periodic solution. Adding stochastic perturbations to the between season map fails to destroy the model's qualitative dynamics. Our results suggest that if the level of host immunity depends on the elapsed time since the last infection then the epidemiological dynamics may be unpredictable.

Antigenic drift expands viral escape pathways from imprinted host humoral immunity

An initial virus exposure can imprint antibodies such that future responses to antigenically drifted strains are dependent on the identity of the imprinting strain. Subsequent exposure to antigenically distinct strains followed by affinity maturation can guide immune responses toward generation of cross-reactive antibodies. How viruses evolve in turn to escape these imprinted broad antibody responses is unclear. Here, we used clonal antibody lineages from two human donors recognizing conserved influenza virus hemagglutinin (HA) epitopes to assess viral escape potential using deep mutational scanning. We show that even though antibody affinity maturation does restrict the number of potential escape routes in the imprinting strain through repositioning the antibody variable domains, escape is still readily observed in drifted strains and attributed to epistatic networks within HA. These data explain how influenza virus continues to evolve in the human population by escaping even broad antibody responses.

Durability of Cross-Neutralizing Antibodies 5.5 Months After Bivalent Coronavirus Disease 2019 Vaccine Booster

We analyzed neutralizing antibodies in samples from ancestral + BA.1 and ancestral + BA.4/5 boosted individuals, collected around 5.5 months after booster. Titers of neutralizing antibodies generally decreased compared to a time point early after the bivalent booster immunization. This was more pronounced for individuals without infection history and for recently emerged Omicron variants.