Pan-vaccine analysis reveals innate immune endotypes predictive of antibody responses to vaccination

Lifestyle score is associated with cellular immune profiles in healthy Tanzanian adults

Immune system and vaccine responses vary across geographical locations worldwide, not only between high and low-middle income countries (LMICs), but also between rural and urban populations within the same country. Lifestyle factors such as housing conditions, exposure to microorganisms and parasites and diet are associated with rural-and urban-living. However, the relationships between these lifestyle factors and immune profiles have not been mapped in detail. Here, we profiled the immune system of 100 healthy Tanzanians living across four rural/urban areas using mass cytometry. We developed a lifestyle score based on an individual's household assets, housing condition and recent dietary history and studied the association with cellular immune profiles. Seventeen out of 80 immune cell clusters were associated with living location or lifestyle score, with eight identifiable only using lifestyle score. Individuals with low lifestyle score, most of whom live in rural settings, showed higher frequencies of NK cells, plasmablasts, atypical memory B cells, T helper 2 cells, regulatory T cells and activated CD4+ T effector memory cells expressing CD38, HLA-DR and CTLA-4. In contrast, those with high lifestyle score, most of whom live in urban areas, showed a less activated state of the immune system illustrated by higher frequencies of naïve CD8+ T cells. Using an elastic net machine learning model, we identified cellular immune signatures most associated with lifestyle score. Assuming a link between these immune profiles and vaccine responses, these signatures may inform us on the cellular mechanisms underlying poor responses to vaccines, but also reduced autoimmunity and allergies in low- and middle-income countries.

Pre-vaccination transcriptomic profiles of immune responders to the MUC1 peptide vaccine for colon cancer prevention

Introduction

Self-antigens abnormally expressed on tumors, such as MUC1, have been targeted by therapeutic cancer vaccines. We recently assessed in two clinical trials in a preventative setting whether immunity induced with a MUC1 peptide vaccine could reduce high colon cancer risk in individuals with a history of premalignant colon adenomas. In both trials, there were immune responders and non-responders to the vaccine.

Methods

Here we used PBMC pre-vaccination and 2 weeks after the first vaccine of responders and non-responders selected from both trials to identify early biomarkers of immune response involved in long-term memory generation and prevention of adenoma recurrence. We performed flow cytometry, phosflow, and differential gene expression analyses on PBMCs collected from MUC1 vaccine responders and non-responders pre-vaccination and two weeks after the first of three vaccine doses.

Results

MUC1 vaccine responders had higher frequencies of CD4 cells pre-vaccination, increased expression of CD40L on CD8 and CD4 T-cells, and a greater increase in ICOS expression on CD8 T-cells. Differential gene expression analysis revealed that iCOSL, PI3K AKT MTOR, and B-cell signaling pathways are activated early in response to the MUC1 vaccine. We identified six specific transcripts involved in elevated antigen presentation, B-cell activation, and NF-κB1 activation that were directly linked to finding antibody response at week 12. Finally, a model using these transcripts was able to predict non-responders with accuracy.

Discussion

These findings suggest that individuals who can be predicted to respond to the MUC1 vaccine, and potentially other vaccines, have greater readiness in all immune compartments to present and respond to antigens. Predictive biomarkers of MUC1 vaccine response may lead to more effective vaccines tailored to individuals with high risk for cancer but with varying immune fitness.

SARS-CoV-2 correlates of protection from infection against variants of concern

Serum neutralizing antibodies (nAbs) induced by vaccination have been linked to protection against symptomatic and severe coronavirus disease 2019. However, much less is known about the efficacy of nAbs in preventing the acquisition of infection, especially in the context of natural immunity and against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune-escape variants. Here we conducted mediation analysis to assess serum nAbs induced by prior SARS-CoV-2 infections as potential correlates of protection against Delta and Omicron infections, in rural and urban household cohorts in South Africa. We find that, in the Delta wave, D614G nAbs mediate 37% (95% confidence interval: 34-40%) of the total protection against infection conferred by prior exposure to SARS-CoV-2, and that protection decreases with waning immunity. In contrast, Omicron BA.1 nAbs mediate 11% (95% confidence interval: 9-12%) of the total protection against Omicron BA.1 or BA.2 infections, due to Omicron's neutralization escape. These findings underscore that correlates of protection mediated through nAbs are variant specific, and that boosting of nAbs against circulating variants might restore or confer immune protection lost due to nAb waning and/or immune escape. However, the majority of immune protection against SARS-CoV-2 conferred by natural infection cannot be fully explained by serum nAbs alone. Measuring these and other immune markers including T cell responses, both in the serum and in other compartments such as the nasal mucosa, may be required to comprehensively understand and predict immune protection against SARS-CoV-2.

Discovery of sparse, reliable omic biomarkers with Stabl

Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl .

Systemic dysregulation and molecular insights into poor influenza vaccine response in the aging population

Vaccination-induced protection against influenza is greatly diminished and increasingly heterogeneous with age. We investigated longitudinally (up to five time points) a cohort of 234 vaccinated >65-year-old vaccinees with adjuvanted vaccine FluAd across two independent seasons. System-level analyses of multiomics datasets measuring six modalities and serological data revealed that poor responders lacked time-dependent changes in response to vaccination as observed in responders, suggestive of systemic dysregulation in poor responders. Multiomics integration revealed key molecules and their likely role in vaccination response. High prevaccination plasma interleukin-15 (IL-15) concentrations negatively associated with antibody production, further supported by experimental validation in mice revealing an IL-15-driven natural killer cell axis explaining the suppressive role in vaccine-induced antibody production as observed in poor responders. We propose a subset of long-chain fatty acids as modulators of persistent inflammation in poor responders. Our findings provide a potential link between low-grade chronic inflammation and poor vaccination response and open avenues for possible pharmacological interventions to enhance vaccine responses.

Acute and persistent responses after H5N1 vaccination in humans

To gain insight into how an adjuvant impacts vaccination responses, we use systems immunology to study human H5N1 influenza vaccination with or without the adjuvant AS03, longitudinally assessing 14 time points including multiple time points within the first day after prime and boost. We develop an unsupervised computational framework to discover high-dimensional response patterns, which uncover adjuvant- and immunogenicity-associated early response dynamics, including some that differ post prime versus boost. With or without adjuvant, some vaccine-induced transcriptional patterns persist to at least 100 days after initial vaccination. Single-cell profiling of surface proteins, transcriptomes, and chromatin accessibility implicates transcription factors in the erythroblast-transformation-specific (ETS) family as shaping these long-lasting signatures, primarily in classical monocytes but also in CD8+ naive-like T cells. These cell-type-specific signatures are elevated at baseline in high-antibody responders in an independent vaccination cohort, suggesting that antigen-agnostic baseline immune states can be modulated by vaccine antigens alone to enhance future responses.

Longitudinal Multi-omic Immune Profiling Reveals Age-Related Immune Cell Dynamics in Healthy Adults

The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examined human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults' memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age.

Immune responses and transcription landscape of adults with the third dose of homologous and heterologous booster vaccines of COVID-19

Background

Heterologous booster vaccines are more effective than homologous booster vaccines in combating the coronavirus disease 2019 (COVID-19) outbreak. However, our understanding of homologous and heterologous booster vaccines for COVID-19 remains limited.

Methods

We recruited 34 healthy participants from two cohorts who were primed with two-dose inactivated COVID-19 vaccine before, vaccinated with COVID-19 inactivated vaccine and adenovirus-vectored vaccine (intramuscular and aerosol inhalation of Ad5-nCoV) as a third booster dose. We assessed the immune responses of participants before and 14 days after vaccination, including levels of neutralizing antibodies, IgG, and cytokines, and quantified the transcriptional profile of peripheral blood mononuclear cells (PBMCs).

Results

The Ad5-nCoV group showed a significantly higher neutralizing antibody geometric mean titer (GMT) compared to the ICV group after 14 days of heterologous boosting. The intramuscular Ad5-nCoV group had a GMT of 191.8 (95% CI 129.0, 285.1) compared to 38.1 (95% CI 23.1, 62.8) in the ICV1 group (p<0.0001). The aerosolized Ad5-nCoV group had a GMT of 738.4 (95% CI 250.9-2173.0) compared to 244.0 (95% CI 135.0, 441.2) in the ICV2 group (p=0.0434). Participants in the aerosolized Ad5-nCoV group had median IFN-γ+ spot counts of 36.5 (IQR 15.3-58.8) per 106 PBMCs, whereas, both intramuscular Ad5-nCoV and CoronaVac immunization as the third dose showed lower responses. This suggests that a third dose of booster Ad5-nCoV vaccine (especially aerosolized inhalation) as a heterologous vaccine booster induces stronger humoral and cellular immune responses, which may be more potent against VOCs than the use of inactivated vaccine homologs. In transcriptomic analyses, both aerosolized inhalation/intramuscular injection of the Ad5-nCoV vaccine and inactivated vaccine induced a large number of differentially expressed genes that were significantly associated with several important innate immune pathways including inflammatory responses, regulation of the defense response, and regulation of cytokine production. In addition, we identified crucial molecular modules of protective immunity that are significantly correlated with vaccine type and neutralizing antibodies level.

Conclusion

This study demonstrated that inhalation/intramuscular injection of the Ad5-nCoV vaccine-mediated stronger humoral and cellular immune responses compared with the inactivated vaccine, and correlated significantly with innate immune function modules, supporting a heterologous booster immunization strategy.

Putting computational models of immunity to the test - an invited challenge to predict B. pertussis vaccination outcomes

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting B. pertussis booster responses and generate experimental data for the explicit purpose of model evaluation. We here describe our second computational prediction challenge using this resource, where we benchmarked 49 algorithms from 53 scientists. We found that the most successful models stood out in their handling of nonlinearities, reducing large feature sets to representative subsets, and advanced data preprocessing. In contrast, we found that models adopted from literature that were developed to predict vaccine antibody responses in other settings performed poorly, reinforcing the need for purpose-built models. Overall, this demonstrates the value of purpose-generated datasets for rigorous and open model evaluations to identify features that improve the reliability and applicability of computational models in vaccine response prediction.

A unified metric of human immune health

Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.

Impact of Oil-in-Water Adjuvanted β-Glucan on Innate Immune Memory in Piglets

The non-specific protective effects offered by the concept of "innate immune memory" might represent a promising strategy to tackle early-life threatening infections. Here we tested the potential of an in vitro selected β-glucan in inducing trained immunity using an in vivo porcine model. We assessed the leukocyte transcriptome using blood transcriptomic module (BTM), proinflammatory cytokines, and clinical scoring after a first "training" and a second "stimulation" phase. The possible induction of innate immune memory was tested during a "stimulation" by an LPS-adjuvanted Mycoplasma hyopneumoniae vaccine (Hyogen®) one day after weaning. Following the "training", no major group differences were found, with the exception of a plasma TNF that was only induced by Adj and Adj_BG treatment. After vaccination, all groups developed similar antibody responses. A significant induction of plasma TNF and IL-1β was found in groups that received Adj and Adj_BG. However, following vaccination, the expected early innate BTMs were only induced by the PBS group. In conclusion, the adjuvant alone, adjuvant-formulated β-glucan, or orally applied β-glucan were unable to enhance innate immune reactivity but rather appeared to promote innate immune tolerance. Such an immune status could have both positive and negative implications during this phase of the piglet's life.

An innate immune signature induced by AS01- or AS03-adjuvanted vaccines predicts the antibody response magnitude and quality consistently over time

Background

Antibody-mediated protection can depend on mechanisms varying from neutralization to Fc-dependent innate immune-cell recruitment. Adjuvanted vaccine development relies on a holistic understanding of how adjuvants modulate the quantity/titer and quality of the antibody response.

Methods

A Phase 2 trial (ClinicalTrials.gov: NCT00805389) evaluated hepatitis B vaccines formulated with licensed adjuvants (AS01B, AS01E, AS03, AS04 or Alum) in antigen-naïve adults. The trial investigated the role of adjuvants in shaping antibody-effector functions, and identified an innate transcriptional response shared by AS01B, AS01E and AS03. We integrated previously reported data on the innate response (gene expression, cytokine/C-reactive protein levels) and on quantitative/qualitative features of the mature antibody response (Fc-related parameters, immunoglobulin titers, avidity). Associations between the innate and humoral parameters were explored using systems vaccinology and a machine-learning framework.

Results

A dichotomy in responses between AS01/AS03 and AS04/Alum (with the former two contributing most to the association with the humoral response) was observed across all timepoints of this longitudinal study. The consistent patterns over time suggested a similarity in the impacts of the two-dose immunization regimen, year-long interval, and non-adjuvanted antigenic challenge given one year later. An innate signature characterized by interferon pathway-related gene expression and secreted interferon-γ-induced protein 10 and C-reactive protein, which was shared by AS01 and AS03, consistently predicted both the qualitative antibody response features and the titers. The signature also predicted from the antibody response quality, the group of adjuvants from which the administered vaccine was derived.

Conclusion

An innate signature induced by AS01- or AS03-adjuvanted vaccines predicts the antibody response magnitude and quality consistently over time.

Deciphering Immune Responses to Immunization via Transcriptional Analysis: A Narrative Review of the Current Evidence towards Personalized Vaccination Strategies

The development of vaccines has drastically reduced the mortality and morbidity of several diseases. Despite the great success of vaccines, the immunological processes involved in protective immunity are not fully understood and several issues remain to be elucidated. Recently, the advent of high-throughput technologies has enabled a more in-depth investigation of the immune system as a whole and the characterization of the interactions of numerous components of immunity. In the field of vaccinology, these tools allow for the exploration of the molecular mechanisms by which vaccines can induce protective immune responses. In this review, we aim to describe current data on transcriptional responses to vaccination, focusing on similarities and differences of vaccine-induced transcriptional responses among vaccines mostly in healthy adults, but also in high-risk populations, such as the elderly and children. Moreover, the identification of potential predictive biomarkers of vaccine immunogenicity, the effect of age on transcriptional response and future perspectives for the utilization of transcriptomics in the field of vaccinology will be discussed.

Host Functional Response to a Prototypic Orally Delivered Self-Replicating Vaccine Platform

The development of mucosal vaccines has been limited and could be aided by a systems vaccinology approach to identify platforms and adjuvant strategies that induce protective immune responses. The induction of local immune responses by mucosal-delivered vaccines has been difficult to evaluate from peripheral samples, as systemic responses often do not correlate with the mucosal response. Here, we utilized transcriptomics in combination with Gene Set Enrichment Analysis (GSEA) to assess innate immune activation by an oral probiotic Lactobacillus acidophilus-based vaccine platform in mice. The goal was to explore the earliest immune responses elicited after oral immunization at the Peyer's patch. Twenty-four hours after oral delivery of the L. acidophilus vaccine platform, we found an abundance of L. acidophilus at Peyer's patches and detected expression of the vaccine viral proteins and adjuvants, confirming in vivo vaccine delivery. Compared to mice orally dosed with buffer or wild-type L. acidophilus, we identified enhanced responses in immune pathways related to cytokine and gene signaling, T and B cell activation, phagocytosis, and humoral responses. While more work is needed to correlate these pathways with protection from infection and/or disease, they indicate this method's potential to evaluate and aid in the iterative development of next-generation mucosal vaccines.

Proteomic analysis of plasma in healthy adults receiving recombinant vaccinia virus provides novel insights into HIV-1 neutralizing antibodies

Human immunodeficiency virus (HIV) infection is still a global public health issue, and the development of an effective prophylactic vaccine inducing potent neutralizing antibodies remains a significant challenge. This study aims to explore the inflammation-related proteins associated with the neutralizing antibodies induced by the DNA/rTV vaccine. In this study, we employed the Olink chip to analyze the inflammation-related proteins in plasma in healthy individuals receiving HIV candidate vaccine (DNA priming and recombinant vaccinia virus rTV boosting) and compared the differences between neutralizing antibody-positive (nab + ) and -negative(nab-) groups. We identified 25 differentially expressed factors and conducted enrichment and correlation analysis on them. Our results revealed that significant expression differences in artemin (ARTN) and C-C motif chemokine ligand 23 (CCL23) between nab+ and -nab- groups. Notably, the expression of CCL23 was negatively corelated to the ID50 of neutralizing antibodies and the intensity of the CD4+ T cell responses. This study enriches our understanding of the immune picture induced by the DNA/rTV vaccine, and provides insights for future HIV vaccine development.

Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

Pre-vaccination transcriptomic profiles of immune responders to the MUC1 peptide vaccine for colon cancer prevention

Self-antigens abnormally expressed on tumors, such as MUC1, have been targeted by therapeutic cancer vaccines. We recently assessed in two clinical trials in a preventative setting whether immunity induced with a MUC1 peptide vaccine could reduce high colon cancer risk in individuals with a history of premalignant colon adenomas. In both trials, there were immune responders and non-responders to the vaccine. Here we used PBMC pre-vaccination and 2 weeks after the first vaccine of responders and non-responders selected from both trials to identify early biomarkers of immune response involved in long-term memory generation and prevention of adenoma recurrence. We performed flow cytometry, phosflow, and differential gene expression analyses on PBMCs collected from MUC1 vaccine responders and non-responders pre-vaccination and two weeks after the first of three vaccine doses. MUC1 vaccine responders had higher frequencies of CD4 cells pre-vaccination, increased expression of CD40L on CD8 and CD4 T-cells, and a greater increase in ICOS expression on CD8 T-cells. Differential gene expression analysis revealed that iCOSL, PI3K AKT MTOR, and B-cell signaling pathways are activated early in response to the MUC1 vaccine. We identified six specific transcripts involved in elevated antigen presentation, B-cell activation, and NF-kB1 activation that were directly linked to finding antibody response at week 12. Finally, a model using these transcripts was able to predict non-responders with accuracy. These findings suggest that individuals who can be predicted to respond to the MUC1 vaccine, and potentially other vaccines, have greater readiness in all immune compartments to present and respond to antigens. Predictive biomarkers of MUC1 vaccine response may lead to more effective vaccines tailored to individuals with high risk for cancer but with varying immune fitness.

A supervised Bayesian factor model for the identification of multi-omics signatures

MOTIVATION

Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are identified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive modeling. However, multi-omics integration and predictive modeling are generally performed independently in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful.

RESULTS

We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the reconstruction of underlying factors in synthetic examples and prediction accuracy of coronavirus disease 2019 severity and breast cancer tumor subtypes.

AVAILABILITY AND IMPLEMENTATION

SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.

Systems and Computational Screening identifies SRC and NKIRAS2 as Baseline Correlates of Risk (CoR) for Live Attenuated Oral Typhoid Vaccine (TY21a) associated Protection

AIM

We investigated the molecular underpinnings of variation in immune responses to the live attenuated typhoid vaccine (Ty21a) by analyzing the baseline immunological profile. We utilized gene expression datasets obtained from the Gene Expression Omnibus (GEO) database (accession number: GSE100665) before and after immunization. We then employed two distinct computational approaches to identify potential baseline biomarkers associated with responsiveness to the Ty21a vaccine.

MAIN METHODS

The first pipeline (knowledge-based) involved the retrieval of differentially expressed genes (DEGs), functional enrichment analysis, protein-protein interaction network construction, and topological network analysis of post-immunization datasets before gauging their pre-vaccination expression levels. The second pipeline utilized an unsupervised machine learning algorithm for data-driven feature selection on pre-immunization datasets. Supervised machine-learning classifiers were employed to computationally validate the identified biomarkers.

KEY FINDINGS

Baseline activation of NKIRAS2 (a negative regulator of NF-kB signalling) and SRC (an adaptor for immune receptor activation) was negatively associated with Ty21a vaccine responsiveness, whereas LOC100134365 exhibited a positive association. The Stochastic Gradient Descent (SGD) algorithm accurately distinguished vaccine responders and non-responders, with 88.8%, 70.3%, and 85.1% accuracy for the three identified genes, respectively.

SIGNIFICANCE

This dual-pronged novel analytical approach provides a comprehensive comparison between knowledge-based and data-driven methods for the prediction of baseline biomarkers associated with Ty21a vaccine responsiveness. The identified genes shed light on the intricate molecular mechanisms that influence vaccine efficacy from the host perspective while pushing the needle further towards the need for development of precise enteric vaccines and on the importance of pre-immunization screening.

Innate immune activation restricts priming and protective efficacy of the radiation-attenuated PfSPZ malaria vaccine

A systems analysis was conducted to determine the potential molecular mechanisms underlying differential immunogenicity and protective efficacy results of a clinical trial of the radiation-attenuated whole-sporozoite PfSPZ vaccine in African infants. Innate immune activation and myeloid signatures at prevaccination baseline correlated with protection from P. falciparum parasitemia in placebo controls. These same signatures were associated with susceptibility to parasitemia among infants who received the highest and most protective PfSPZ vaccine dose. Machine learning identified spliceosome, proteosome, and resting DC signatures as prevaccination features predictive of protection after highest-dose PfSPZ vaccination, whereas baseline circumsporozoite protein-specific (CSP-specific) IgG predicted nonprotection. Prevaccination innate inflammatory and myeloid signatures were associated with higher sporozoite-specific IgG Ab response but undetectable PfSPZ-specific CD8+ T cell responses after vaccination. Consistent with these human data, innate stimulation in vivo conferred protection against infection by sporozoite injection in malaria-naive mice while diminishing the CD8+ T cell response to radiation-attenuated sporozoites. These data suggest a dichotomous role of innate stimulation for malaria protection and induction of protective immunity by whole-sporozoite malaria vaccines. The uncoupling of vaccine-induced protective immunity achieved by Abs from more protective CD8+ T cell responses suggests that PfSPZ vaccine efficacy in malaria-endemic settings may be constrained by opposing antigen presentation pathways.

Vaccines Induce Homeostatic Immunity, Generating Several Secondary Benefits

The optimal immune response eliminates invading pathogens, restoring immune equilibrium without inflicting undue harm to the host. However, when a cascade of immunological reactions is triggered, the immune response can sometimes go into overdrive, potentially leading to harmful long-term effects or even death. The immune system is triggered mostly by infections, allergens, or medical interventions such as vaccination. This review examines how these immune triggers differ and why certain infections may dysregulate immune homeostasis, leading to inflammatory or allergic pathology and exacerbation of pre-existing conditions. However, many vaccines generate an optimal immune response and protect against the consequences of pathogen-induced immunological aggressiveness, and from a small number of unrelated pathogens and autoimmune diseases. Here, we propose an "immuno-wave" model describing a vaccine-induced "Goldilocks immunity", which leaves fine imprints of both pro-inflammatory and anti-inflammatory milieus, derived from both the innate and the adaptive arms of the immune system, in the body. The resulting balanced, 'quiet alert' state of the immune system may provide a jump-start in the defense against pathogens and any associated pathological inflammatory or allergic responses, allowing vaccines to go above and beyond their call of duty. In closing, we recommend formally investigating and reaping many of the secondary benefits of vaccines with appropriate clinical studies.

Immunological factors linked to geographical variation in vaccine responses

Vaccination is one of medicine's greatest achievements; however, its full potential is hampered by considerable variation in efficacy across populations and geographical regions. For example, attenuated malaria vaccines in high-income countries confer almost 100% protection, whereas in low-income regions these same vaccines achieve only 20-50% protection. This trend is also observed for other vaccines, such as bacillus Calmette-Guérin (BCG), rotavirus and yellow fever vaccines, in terms of either immunogenicity or efficacy. Multiple environmental factors affect vaccine responses, including pathogen exposure, microbiota composition and dietary nutrients. However, there has been variable success with interventions that target these individual factors, highlighting the need for a better understanding of their downstream immunological mechanisms to develop new ways of modulating vaccine responses. Here, we review the immunological factors that underlie geographical variation in vaccine responses. Through the identification of causal pathways that link environmental influences to vaccine responsiveness, it might become possible to devise modulatory compounds that can complement vaccines for better outcomes in regions where they are needed most.

A multi-omics systems vaccinology resource to develop and test computational models of immunity

Systems vaccinology studies have identified factors affecting individual vaccine responses, but comparing these findings is challenging due to varying study designs. To address this lack of reproducibility, we established a community resource for comparing Bordetella pertussis booster responses and to host annual contests for predicting patients' vaccination outcomes. We report here on our experiences with the "dry-run" prediction contest. We found that, among 20+ models adopted from the literature, the most successful model predicting vaccination outcome was based on age alone. This confirms our concerns about the reproducibility of conclusions between different vaccinology studies. Further, we found that, for newly trained models, handling of baseline information on the target variables was crucial. Overall, multiple co-inertia analysis gave the best results of the tested modeling approaches. Our goal is to engage community in these prediction challenges by making data and models available and opening a public contest in August 2024.

NIAID/SMB Workshop on Multiscale Modeling of Infectious and Immune-Mediated Diseases

On July 19th, 2023, the National Institute of Allergy and Infectious Diseases co-organized a workshop with the Society of Mathematical Biology, with the authors of this paper as the organizing committee. The workshop, "Bridging multiscale modeling and practical clinical applications in infectious diseases" sought to create an environment for mathematical modelers, statisticians, and infectious disease researchers and clinicians to exchange ideas and perspectives.

Whole blood RNA signatures in tuberculosis patients receiving H56:IC31 vaccine as adjunctive therapy

Introduction

Therapeutic vaccination in tuberculosis (TB) represents a Host Directed Therapy strategy which enhances immune responses in order to improve clinical outcomes and shorten TB treatment. Previously, we have shown that the subunit H56:IC31 vaccine induced both humoral and cellular immune responses when administered to TB patients adjunctive to standard TB treatment (TBCOX2 study, NCT02503839). Here we present the longitudinal whole blood gene expression patterns in H56:IC31 vaccinated TB patients compared to controls receiving standard TB treatment only.

Methods

The H56:IC31 group (N=11) and Control group (N=7) underwent first-line TB treatment for 182 days. The H56:IC31 group received 5 micrograms of the H56:IC31 vaccine (Statens Serum Institut; SSI, Valneva Austria GmbH) intramuscularly at day 84 and day 140. Total RNA was extracted from whole blood samples collected in PAXgene tubes on days 0, 84, 98, 140, 154, 182 and 238. The expression level of 183 immune-related genes was measured by high-throughput microfluidic qPCR (Biomark HD system, Standard BioTools).

Results

The targeted gene expression profiling unveiled the upregulation of modules such as interferon (IFN) signalling genes, pattern recognition receptors and small nucleotide guanosine triphosphate (GTP)-ases in the vaccinated group compared to controls two weeks after administration of the first H56:IC31 vaccine. Additionally, the longitudinal analysis of the Adolescent Cohort Study-Correlation of Risk (ACS-COR) signature showed a progressive downregulation in both study arms towards the end of TB treatment, in congruence with reported treatment responses and clinical improvements. Still, two months after the end of TB treatment, vaccinated patients, and especially those developing both cellular and humoral vaccine responses, showed a lower expression of the ACS-COR genes compared to controls.

Discussion

Our data report gene expression patterns following H56:IC31 vaccination which might be interpreted as a lower risk of relapse in therapeutically vaccinated patients. Further studies are needed to conclude if these gene expression patterns could be used as prognostic biosignatures for therapeutic TB vaccine responses.

Leveraging baseline transcriptional features and information from single-cell data to power the prediction of influenza vaccine response

Introduction

Vaccination is still the primary means for preventing influenza virus infection, but the protective effects vary greatly among individuals. Identifying individuals at risk of low response to influenza vaccination is important. This study aimed to explore improved strategies for constructing predictive models of influenza vaccine response using gene expression data.

Methods

We first used gene expression and immune response data from the Immune Signatures Data Resource (IS2) to define influenza vaccine response-related transcriptional expression and alteration features at different time points across vaccination via differential expression analysis. Then, we mapped these features to single-cell resolution using additional published single-cell data to investigate the possible mechanism. Finally, we explored the potential of these identified transcriptional features in predicting influenza vaccine response. We used several modeling strategies and also attempted to leverage the information from single-cell RNA sequencing (scRNA-seq) data to optimize the predictive models.

Results

The results showed that models based on genes showing differential expression (DEGs) or fold change (DFGs) at day 7 post-vaccination performed the best in internal validation, while models based on DFGs had a better performance in external validation than those based on DEGs. In addition, incorporating baseline predictors could improve the performance of models based on days 1-3, while the model based on the expression profile of plasma cells deconvoluted from the model that used DEGs at day 7 as predictors showed an improved performance in external validation.

Conclusion

Our study emphasizes the value of using combination modeling strategy and leveraging information from single-cell levels in constructing influenza vaccine response predictive models.

A Quantitative Clinical Pharmacology-Based Framework For Model-Informed Vaccine Development

Historically, vaccine development and dose optimization have followed mostly empirical approaches without clinical pharmacology and model-informed approaches playing a major role, in contrast to conventional drug development. This is attributed to the complex cascade of immunobiological mechanisms associated with vaccines and a lack of quantitative frameworks for extracting dose-exposure-efficacy-toxicity relationships. However, the Covid-19 pandemic highlighted the lack of sufficient immunogenicity due to suboptimal vaccine dosing regimens and the need for well-designed, model-informed clinical trials which enhance the probability of selection of optimal vaccine dosing regimens. In this perspective, we attempt to develop a quantitative clinical pharmacology-based approach that integrates vaccine dose-efficacy-toxicity across various stages of vaccine development into a unified framework that we term as model-informed vaccine dose-optimization and development (MIVD). We highlight scenarios where the adoption of MIVD approaches may have a strategic advantage compared to conventional practices for vaccines.

Systems biology analysis reveals distinct molecular signatures associated with immune responsiveness to the BNT162b COVID-19 vaccine

BACKGROUND

Human immune responses to COVID-19 vaccines display a large heterogeneity of induced immunity and the underlying immune mechanisms for this remain largely unknown.

METHODS

Using a systems biology approach, we longitudinally profiled a unique cohort of female high and low responders to the BNT162b vaccine, who were known from previous COVID-19 vaccinations to develop maximum and minimum immune responses to the vaccine. We utilized high dimensional flow cytometry, bulk and single cell mRNA sequencing and 48-plex serum cytokine analyses.

FINDINGS

We revealed early, transient immunological and molecular signatures that distinguished high from low responders and correlated with B and T cell responses measured 14 days later. High responders featured a distinct transcriptional activity of interferon-driven genes and genes connected to enhanced antigen presentation. This was accompanied by a robust cytokine response related to Th1 differentiation. Both transcriptome and serum cytokine signatures were confirmed in two independent confirmatory cohorts.

INTERPRETATION

Collectively, our data contribute to a better understanding of the immunogenicity of mRNA-based COVID-19 vaccines, which might lead to the optimization of vaccine designs for individuals with poor vaccine responses.

FUNDING

German Center for Infection Research, German Center for Lung Research, German Research Foundation, Excellence Strategy EXC 2155 "RESIST" and European Regional Development Fund.

Global blood miRNA profiling unravels early signatures of immunogenicity of Ebola vaccine rVSVΔG-ZEBOV-GP

The vectored Ebola vaccine rVSVΔG-ZEBOV-GP elicits protection against Ebola Virus Disease (EVD). In a study of forty-eight healthy adult volunteers who received either the rVSVΔG-ZEBOV-GP vaccine or placebo, we profiled intracellular microRNAs (miRNAs) from whole blood cells (WB) and circulating miRNAs from serum-derived extracellular vesicles (EV) at baseline and longitudinally following vaccination. Further, we identified early miRNA signatures associated with ZEBOV-specific IgG antibody responses at baseline and up to one year post-vaccination, and pinpointed target mRNA transcripts and pathways correlated to miRNAs whose expression was altered after vaccination by using systems biology approaches. Several miRNAs were differentially expressed (DE) and miRNA signatures predicted high or low IgG ZEBOV-specific antibody levels with high classification performance. The top miRNA discriminators were WB-miR-6810, EV-miR-7151-3p, and EV-miR-4426. An eight-miRNA antibody predictive signature was associated with immune-related target mRNAs and pathways. These findings provide valuable insights into early blood biomarkers associated with rVSVΔG-ZEBOV-GP vaccine-induced IgG antibody responses.

Using the power of innate immunoprofiling to understand vaccine design, infection, and immunity

In the field of immunology, a systems biology approach is crucial to understanding the immune response to infection and vaccination considering the complex interplay between genetic, epigenetic, and environmental factors. Significant progress has been made in understanding the innate immune response, including cell players and critical signaling pathways, but many questions remain unanswered, including how the innate immune response dictates host/pathogen responses and responses to vaccines. To complicate things further, it is becoming increasingly clear that the innate immune response is not a linear pathway but is formed from complex networks and interactions. To further our understanding of the crosstalk and complexities, systems-level analyses and expanded experimental technologies are now needed. In this review, we discuss the most recent immunoprofiling techniques and discuss systems approaches to studying the global innate immune landscape which will inform on the development of personalized medicine and innovative vaccine strategies.

From bench to bedside via bytes: Multi-omic immunoprofiling and integration using machine learning and network approaches

A significant surge in research endeavors leverages the vast potential of high-throughput omic technology platforms for broad profiling of biological responses to vaccines and cutting-edge immunotherapies and stem-cell therapies under development. These profiles capture different aspects of core regulatory and functional processes at different scales of resolution from molecular and cellular to organismal. Systems approaches capture the complex and intricate interplay between these layers and scales. Here, we summarize experimental data modalities, for characterizing the genome, epigenome, transcriptome, proteome, metabolome, and antibody-ome, that enable us to generate large-scale immune profiles. We also discuss machine learning and network approaches that are commonly used to analyze and integrate these modalities, to gain insights into correlates and mechanisms of natural and vaccine-mediated immunity as well as therapy-induced immunomodulation.

Interaction dynamics between innate and adaptive immune cells responding to SARS-CoV-2 vaccination in non-human primates

As SARS-CoV-2 variants continue evolving, testing updated vaccines in non-human primates remains important for guiding human clinical practice. To date, such studies have focused on antibody titers and antigen-specific B and T cell frequencies. Here, we extend our understanding by integrating innate and adaptive immune responses to mRNA-1273 vaccination in rhesus macaques. We sorted innate immune cells from a pre-vaccine time point, as well as innate immune cells and antigen-specific peripheral B and T cells two weeks after each of two vaccine doses and used single-cell sequencing to assess the transcriptomes and adaptive immune receptors of each cell. We show that a subset of S-specific T cells expresses cytokines critical for activating innate responses, with a concomitant increase in CCR5-expressing intermediate monocytes and a shift of natural killer cells to a more cytotoxic phenotype. The second vaccine dose, administered 4 weeks after the first, elicits an increase in circulating germinal center-like B cells 2 weeks later, which are more clonally expanded and enriched for epitopes in the receptor binding domain. Both doses stimulate inflammatory response genes associated with elevated antibody production. Overall, we provide a comprehensive picture of bidirectional signaling between innate and adaptive components of the immune system and suggest potential mechanisms for the enhanced response to secondary exposure.

Leveraging human immune organoids for rational vaccine design

Current influenza A and B virus (IABV) vaccines provide suboptimal protection and efforts are underway to develop a universal IABV vaccine. Blood neutralizing antibodies are the current gold standard for protection, but many processes that regulate human IABV-specific immunity occur in mucosal and lymphoid tissues. We need an improved mechanistic understanding of how immune cells respond within these tissues to advance our current (slow and expensive) vaccine testing model. We posit that advanced in vitro models of human adaptive immunity can bridge some of the gaps between vaccine design, animal models, and human clinical trials. Here, we highlight how they can be integrated into current practices and play a role in reverse translating the defined features of protective vaccines to rationally design new candidates.

Rapid transient and longer-lasting innate cytokine changes associated with adaptive immunity after repeated SARS-CoV-2 BNT162b2 mRNA vaccinations

Introduction

Cytokines and chemokines play an important role in shaping innate and adaptive immunity in response to infection and vaccination. Systems serology identified immunological parameters predictive of beneficial response to the BNT162b2 mRNA vaccine in COVID-19 infection-naïve volunteers, COVID-19 convalescent patients and transplant patients with hematological malignancies. Here, we examined the dynamics of the serum cytokine/chemokine responses after the 3rd BNT162b2 mRNA vaccination in a cohort of COVID-19 infection-naïve volunteers.

Methods

We measured serum cytokine and chemokine responses after the 3rd dose of the BNT162b2 mRNA (Pfizer/BioNtech) vaccine in COVID-19 infection-naïve individuals by a chemiluminescent assay and ELISA. Anti-Spike binding antibodies were measured by ELISA. Anti-Spike neutralizing antibodies were measured by a pseudotype assay.

Results

Comparison to responses found after the 1st and 2nd vaccinations showed persistence of the coordinated responses of several cytokine/chemokines including the previously identified rapid and transient IL-15, IFN-γ, CXCL10/IP-10, TNF-α, IL-6 signature. In contrast to the transient (24hrs) effect of the IL-15 signature, an inflammatory/anti-inflammatory cytokine signature (CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CXCL8/IL-8, IL-1Ra) remained at higher levels up to one month after the 2nd and 3rd booster vaccinations, indicative of a state of longer-lasting innate immune change. We also identified a systemic transient increase of CXCL13 only after the 3rd vaccination, supporting stronger germinal center activity and the higher anti-Spike antibody responses. Changes of the IL-15 signature, and the inflammatory/anti-inflammatory cytokine profile correlated with neutralizing antibody levels also after the 3rd vaccination supporting their role as immune biomarkers for effective development of vaccine-induced humoral responses.

Conclusion

These data revealed that repeated SARS-Cov-2 BNT162b2 mRNA vaccination induces both rapid transient as well as longer-lasting systemic serum cytokine changes associated with innate and adaptive immune responses.

Clinical trial registration

Clinicaltrials.gov, identifier NCT04743388.

Baseline immune states (BIS) associated with vaccine responsiveness and factors that shape the BIS

Vaccines are among the greatest inventions in medicine, leading to the elimination or control of numerous diseases, including smallpox, polio, measles, rubella, and, most recently, COVID-19. Yet, the effectiveness of vaccines varies among individuals. In fact, while some recipients mount a robust response to vaccination that protects them from the disease, others fail to respond. Multiple clinical and epidemiological factors contribute to this heterogeneity in responsiveness. Systems immunology studies fueled by advances in single-cell biology have been instrumental in uncovering pre-vaccination immune cell types and genomic features (i.e., the baseline immune state, BIS) that have been associated with vaccine responsiveness. Here, we review clinical factors that shape the BIS, and the characteristics of the BIS associated with responsiveness to frequently studied vaccines (i.e., influenza, COVID-19, bacterial pneumonia, malaria). Finally, we discuss potential strategies to enhance vaccine responsiveness in high-risk groups, focusing specifically on older adults.

Reduced Serological Response to COVID-19 Booster Vaccine is Associated with Reduced B Cell Memory in Patients With Inflammatory Bowel Disease; VARIATION [VAriability in Response in IBD AgainsT SARS-COV-2 ImmunisatiON]

BACKGROUND AND AIMS

Patients with inflammatory bowel disease [IBD] have an attenuated response to initial COVID-19 vaccination. We sought to characterize the impact of IBD and its treatment on responses after the third vaccine against SARS-CoV-2.

METHODS

This was a prospective multicentre observational study of patients with IBD [n = 202] and healthy controls [HC, n = 92]. Serological response to vaccination was assessed by quantification of anti-spike protein [SP] immunoglobulin [Ig]G levels [anti-SPIgG] and in vitro neutralization of binding to angiotensin-converting enzyme 2 [ACE2]. Peripheral blood B-cell phenotype populations were assessed by flow cytometry. SARS-CoV-2 antigen-specific B-cell responses were assessed in ex vivo culture.

RESULTS

Median anti-SP IgG post-third vaccination in our IBD cohort was significantly lower than HCs [7862 vs 19 622 AU/mL, p < 0.001] as was ACE2 binding inhibition [p < 0.001]. IBD patients previously infected with COVID-19 [30%] had similar quantitative antibody response as HCs previously infected with COVID-19 [p = 0.12]. Lowest anti-SP IgG titres and neutralization were seen in IBD patients on anti-tumour necrosis factor [anti-TNF] agents, without prior COVID-19 infection, but all IBD patients show an attenuated vaccine response compared to HCs. Patients with IBD have reduced memory B-cell populations and attenuated B-cell responses to SARS-CoV-2 antigens if not previously infected with COVID-19 [p = 0.01]. Higher anti-TNF drug levels and zinc levels <65 ng/ml were associated with significantly lower serological responses.

CONCLUSIONS

Patients with IBD have an attenuated response to three doses of SARS-CoV-2 vaccine. Physicians should consider patients with higher anti-TNF drug levels and/or zinc deficiency as potentially at higher risk of attenuated response to vaccination.

Identification of early gene expression profiles associated with long-lasting antibody responses to the Ebola vaccine Ad26.ZEBOV/MVA-BN-Filo

Ebola virus disease is a severe hemorrhagic fever with a high fatality rate. We investigate transcriptome profiles at 3 h, 1 day, and 7 days after vaccination with Ad26.ZEBOV and MVA-BN-Filo. 3 h after Ad26.ZEBOV injection, we observe an increase in genes related to antigen presentation, sensing, and T and B cell receptors. The highest response occurs 1 day after Ad26.ZEBOV injection, with an increase of the gene expression of interferon-induced antiviral molecules, monocyte activation, and sensing receptors. This response is regulated by the HESX1, ATF3, ANKRD22, and ETV7 transcription factors. A plasma cell signature is observed on day 7 post-Ad26.ZEBOV vaccination, with an increase of CD138, MZB1, CD38, CD79A, and immunoglobulin genes. We have identified early expressed genes correlated with the magnitude of the antibody response 21 days after the MVA-BN-Filo and 364 days after Ad26.ZEBOV vaccinations. Our results provide early gene signatures that correlate with vaccine-induced Ebola virus glycoprotein-specific antibodies.

Baseline innate and T cell populations are correlates of protection against symptomatic influenza virus infection independent of serology

Evidence suggests that innate and adaptive cellular responses mediate resistance to the influenza virus and confer protection after vaccination. However, few studies have resolved the contribution of cellular responses within the context of preexisting antibody titers. Here, we measured the peripheral immune profiles of 206 vaccinated or unvaccinated adults to determine how baseline variations in the cellular and humoral immune compartments contribute independently or synergistically to the risk of developing symptomatic influenza. Protection correlated with diverse and polyfunctional CD4+ and CD8+ T, circulating T follicular helper, T helper type 17, myeloid dendritic and CD16+ natural killer (NK) cell subsets. Conversely, increased susceptibility was predominantly attributed to nonspecific inflammatory populations, including γδ T cells and activated CD16- NK cells, as well as TNFα+ single-cytokine-producing CD8+ T cells. Multivariate and predictive modeling indicated that cellular subsets (1) work synergistically with humoral immunity to confer protection, (2) improve model performance over demographic and serologic factors alone and (3) comprise the most important predictive covariates. Together, these results demonstrate that preinfection peripheral cell composition improves the prediction of symptomatic influenza susceptibility over vaccination, demographics or serology alone.

A systems vaccinology resource to develop and test computational models of immunity

Computational models that predict an individual's response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine. The ability to assess the performance of the resulting models would be improved by comparing their performance on independent datasets, as has been done with great success in other areas of biology such as protein structure predictions. To transfer this approach to system vaccinology studies, we established a prototype platform that focuses on the evaluation of Computational Models of Immunity to Pertussis Booster vaccinations (CMI-PB). A community resource, CMI-PB generates experimental data for the explicit purpose of model evaluation, which is performed through a series of annual data releases and associated contests. We here report on our experience with the first such 'dry run' for a contest where the goal was to predict individual immune responses based on pre-vaccination multi-omic profiles. Over 30 models adopted from the literature were tested, but only one was predictive, and was based on age alone. The performance of new models built using CMI-PB training data was much better, but varied significantly based on the choice of pre-vaccination features used and the model building strategy. This suggests that previously published models developed for other vaccines do not generalize well to Pertussis Booster vaccination. Overall, these results reinforced the need for comparative analysis across models and datasets that CMI-PB aims to achieve. We are seeking wider community engagement for our first public prediction contest, which will open in early 2024.

Immunological Monitoring in Hepatitis C Virus Controlled Human Infection Model

Controlled human infection model trials for hepatitis C virus represent an important opportunity to identify correlates of protective immunity against a well-characterized inoculum of hepatitis C virus and how such responses are modified by vaccination. In this article, we discuss the approach to immunological monitoring during such trials, including a set of recommendations for optimal sampling schedule and preferred immunological assays to examine the different arms of the immune response. We recommend that this approach be adapted to different trial designs. Finally, we discuss how these studies can provide surrogate predictors of the success of candidate vaccines.

Restoring Trust: The Need for Precision Medicine in Infectious Diseases, Public Health and Vaccines

There are limited data on precision medicine in infectious diseases and vaccines; however, precise management of infectious diseases plays a critical role in trust for government, health-care organizations, science, and pharma. The improvement in biomedical technologies, availability of large clinical and -omic data and appropriate application of artificial intelligence may allow precision in vaccines and public health and restore trust. This is an invited editorial on the role of precision medicine in infectious diseases and vaccines.

Predictive overfitting in immunological applications: Pitfalls and solutions

Overfitting describes the phenomenon where a highly predictive model on the training data generalizes poorly to future observations. It is a common concern when applying machine learning techniques to contemporary medical applications, such as predicting vaccination response and disease status in infectious disease or cancer studies. This review examines the causes of overfitting and offers strategies to counteract it, focusing on model complexity reduction, reliable model evaluation, and harnessing data diversity. Through discussion of the underlying mathematical models and illustrative examples using both synthetic data and published real datasets, our objective is to equip analysts and bioinformaticians with the knowledge and tools necessary to detect and mitigate overfitting in their research.

Baseline Gut Microbiome Signatures Correlate with Immunogenicity of SARS-CoV-2 mRNA Vaccines

The powerful immune responses elicited by the mRNA vaccines targeting the SARS-CoV-2 Spike protein contribute to their high efficacy. Yet, their efficacy can vary greatly between individuals. For vaccines not based on mRNA, cumulative evidence suggests that differences in the composition of the gut microbiome, which impact vaccine immunogenicity, are some of the factors that contribute to variations in efficacy. However, it is unclear if the microbiome impacts the novel mode of immunogenicity of the SARS-CoV-2 mRNA vaccines. We conducted a prospective longitudinal cohort study of individuals receiving SARS-CoV-2 mRNA vaccines where we measured levels of anti-Spike IgG and characterized microbiome composition, at pre-vaccination (baseline), and one week following the first and second immunizations. While we found that microbial diversity at all timepoints correlated with final IgG levels, only at baseline did microbial composition and predicted function correlate with vaccine immunogenicity. Specifically, the phylum Desulfobacterota and genus Bilophila, producers of immunostimulatory LPS, positively correlated with IgG, while Bacteroides was negatively correlated. KEGG predicted pathways relating to SCFA metabolism and sulfur metabolism, as well as structural components such as flagellin and capsular polysaccharides, also positively correlated with IgG levels. Consistent with these findings, depleting the microbiome with antibiotics reduced the immunogenicity of the BNT162b2 vaccine in mice. These findings suggest that gut microbiome composition impacts the immunogenicity of the SARS-CoV-2 mRNA vaccines.

Memory-like innate response to booster vaccination with MF-59 adjuvanted influenza vaccine in children

The pediatric population receives the majority of vaccines globally, yet there is a paucity of studies on the transcriptional response induced by immunization in this special population. In this study, we performed a systems-level analysis of immune responses to the trivalent inactivated influenza vaccine adjuvanted with MF-59 in children (15-24 months old) and in young, healthy adults. We analyzed transcriptional responses elicited by vaccination in peripheral blood, as well as cellular and antibody responses following primary and booster vaccinations. Our analysis revealed that primary vaccination induced a persistent transcriptional signature of innate immunity; booster vaccination induced a transcriptional signature of an enhanced memory-like innate response, which was consistent with enhanced activation of myeloid cells assessed by flow cytometry. Furthermore, we identified a transcriptional signature of type 1 interferon response post-booster vaccination and at baseline that was correlated with the local reactogenicity to vaccination and defined an early signature that correlated with the hemagglutinin antibody titers. These results highlight an adaptive behavior of the innate immune system in evoking a memory-like response to secondary vaccination and define molecular correlates of reactogenicity and immunogenicity in infants.

Making human immune systems more interpretable through systems immunology

The human immune system is a distributed system of specialized cell populations with unique functions that collectively give rise to immune responses to infections and during immune-mediated diseases. Cell composition, plasma proteins, and functional responses vary among individuals, making the system difficult to interpret, but this variation is nonrandom. With careful analyses using novel experimental and computational tools, human immune system composition and function carry interpretable information. Here, we propose that systems-level analyses offer an opportunity to make human immune responses more interpretable in the future, and we discuss herein important considerations and lessons learned to this end. Predictable human immunology holds implications for better diagnostic and curative precision in patients with infectious and immune-associated diseases.

Schistosoma mansoni infection alters the host pre-vaccination environment resulting in blunted Hepatitis B vaccination immune responses

Schistosomiasis is a disease caused by parasitic flatworms of the Schistosoma spp., and is increasingly recognized to alter the immune system, and the potential to respond to vaccines. The impact of endemic infections on protective immunity is critical to inform vaccination strategies globally. We assessed the influence of Schistosoma mansoni worm burden on multiple host vaccine-related immune parameters in a Ugandan fishing cohort (n = 75) given three doses of a Hepatitis B (HepB) vaccine at baseline and multiple timepoints post-vaccination. We observed distinct differences in immune responses in instances of higher worm burden, compared to low worm burden or non-infected. Concentrations of pre-vaccination serum schistosome-specific circulating anodic antigen (CAA), linked to worm burden, showed a significant bimodal distribution associated with HepB titers, which was lower in individuals with higher CAA values at month 7 post-vaccination (M7). Comparative chemokine/cytokine responses revealed significant upregulation of CCL19, CXCL9 and CCL17 known to be involved in T cell activation and recruitment, in higher CAA individuals, and CCL17 correlated negatively with HepB titers at month 12 post-vaccination. We show that HepB-specific CD4+ T cell memory responses correlated positively with HepB titers at M7. We further established that those participants with high CAA had significantly lower frequencies of circulating T follicular helper (cTfh) subpopulations pre- and post-vaccination, but higher regulatory T cells (Tregs) post-vaccination, suggesting changes in the immune microenvironment in high CAA could favor Treg recruitment and activation. Additionally, we found that changes in the levels of innate-related cytokines/chemokines CXCL10, IL-1β, and CCL26, involved in driving T helper responses, were associated with increasing CAA concentration. This study provides further insight on pre-vaccination host responses to Schistosoma worm burden which will support our understanding of vaccine responses altered by pathogenic host immune mechanisms and memory function and explain abrogated vaccine responses in communities with endemic infections.

Polyfunctional antibodies: a path towards precision vaccines for vulnerable populations

Vaccine efficacy determined within the controlled environment of a clinical trial is usually substantially greater than real-world vaccine effectiveness. Typically, this results from reduced protection of immunologically vulnerable populations, such as children, elderly individuals and people with chronic comorbidities. Consequently, these high-risk groups are frequently recommended tailored immunisation schedules to boost responses. In addition, diverse groups of healthy adults may also be variably protected by the same vaccine regimen. Current population-based vaccination strategies that consider basic clinical parameters offer a glimpse into what may be achievable if more nuanced aspects of the immune response are considered in vaccine design. To date, vaccine development has been largely empirical. However, next-generation approaches require more rational strategies. We foresee a generation of precision vaccines that consider the mechanistic basis of vaccine response variations associated with both immunogenetic and baseline health differences. Recent efforts have highlighted the importance of balanced and diverse extra-neutralising antibody functions for vaccine-induced protection. However, in immunologically vulnerable populations, significant modulation of polyfunctional antibody responses that mediate both neutralisation and effector functions has been observed. Here, we review the current understanding of key genetic and inflammatory modulators of antibody polyfunctionality that affect vaccination outcomes and consider how this knowledge may be harnessed to tailor vaccine design for improved public health.

Broad-spectrum pan-genus and pan-family virus vaccines

Although the development and clinical application of SARS-CoV-2 vaccines during the COVID-19 pandemic demonstrated unprecedented vaccine success in a short time frame, it also revealed a limitation of current vaccines in their inability to provide broad-spectrum or universal protection against emerging variants. Broad-spectrum vaccines, therefore, remain a dream and challenge for vaccinology. This review will focus on current and future efforts in developing universal vaccines targeting different viruses at the genus and/or family levels, with a special focus on henipaviruses, influenza viruses, and coronaviruses. It is evident that strategies for developing broad-spectrum vaccines will be virus-genus or family specific, and it is almost impossible to adopt a universal approach for different viruses. On the other hand, efforts in developing broad-spectrum neutralizing monoclonal antibodies have been more successful and it is worth considering broad-spectrum antibody-mediated immunization, or "universal antibody vaccine," as an alternative approach for early intervention for future disease X outbreaks.

Predictors of long-term neutralizing antibody titers following COVID-19 vaccination by three vaccine types: the BOOST study

As concerns related to the COVID-19 pandemic continue, it is critical to understand the impact of vaccination type on neutralizing antibody response durability as well as to identify individual difference factors related to decline in neutralization. This was a head-to-head comparison study following 498 healthy, community volunteers who received the BNT162b2 (n = 287), mRNA-1273 (n = 149), and Ad26.COV2.S (n = 62). Participants completed questionnaires and underwent blood draws prior to vaccination, 1 month, and 6 months after the vaccination series, and neutralizing antibody (nAB) titers at 1- and 6-months post vaccination were quantified using a high-throughput pseudovirus assay. Over 6 months of follow-up, nABs declined in recipients of BNT162b2 and mRNA-1273, while nABs in recipients of Ad26.COV2.S showed a significant increase. At the 6-month time point, nABs to Ad26.COV2.S were significantly higher than nABs to BNT162b2 and equivalent to mRNA-1273. Irrespective of follow-up timing, being older was associated with lower nAB for participants who received BNT162b2 and Ad26.COV2.S but not for those who received mRNA-1273. A higher baseline BMI was associated with a lower nAB for Ad26.COV2.S recipients but not for recipients of other vaccines. Women and non-smokers showed higher nAB compared to men and current smokers, respectively. The durability of neutralizing antibody responses differed by vaccine type and several sociodemographic factors that predicted response. These findings may inform booster recommendations in the future.

Sex chromosome complement and sex steroid signaling underlie sex differences in immunity to respiratory virus infection

Epidemiological studies have revealed sex differences in the incidence and morbidity of respiratory virus infection in the human population, and often these observations are correlated with sex differences in the quality or magnitude of the immune response. Sex differences in immunity and morbidity also are observed in animal models of respiratory virus infection, suggesting differential dominance of specific immune mechanisms. Emerging research shows intrinsic sex differences in immune cell transcriptomes, epigenomes, and proteomes that may regulate human immunity when challenged by viral infection. Here, we highlight recent research into the role(s) of sex steroids and X chromosome complement in immune cells and describe how these findings provide insight into immunity during respiratory virus infection. We focus on the regulation of innate and adaptive immune cells by receptors for androgen and estrogens, as well as genes with a propensity to escape X chromosome inactivation. A deeper mechanistic knowledge of these pathways will help us to understand the often significant sex differences in immunity to endemic or pandemic respiratory pathogens such as influenza viruses, respiratory syncytial viruses and pathogenic coronaviruses.