Transcriptional signatures of influenza A/H1N1-specific IgG memory-like B cell response in older individuals

Similar humoral responses but distinct CD4+ T cell transcriptomic profiles in older adults elicited by MF59 adjuvanted and high dose influenza vaccines

Older age (≥ 65 years) is associated with impaired responses to influenza vaccination, leading to the preferential recommendation of MF59-adjuvanted (MF59Flu) or high-dose (HDFlu) influenza vaccines for this age group in the United States. Herein, we characterized transcriptomic profiles of CD4+ T cells isolated from 234 recipients (≥ 65 years) of either MF59Flu or HDFlu vaccine, prior to vaccination and 28 days thereafter. We identified 412 and 645 differentially expressed genes (DEGs) in CD4+ T cells of older adults after receiving MF59Flu and HDFlu, respectively. DEGs in CD4+ T cells of MF59Flu recipients were enriched in 14 KEGG pathways, all of which were downregulated. DEGs in CD4+ T cells of HDFlu recipients were enriched in 11 upregulated pathways and 20 downregulated pathways. CD4+ T cells in both vaccine groups shared 50 upregulated genes and 75 downregulated genes, all of which were enriched in 7 KEGG pathways. The remaining 287 and 520 DEGs were specifically associated with MF59Flu and HDFlu, respectively. Unexpectedly, none of these DEGs was significantly correlated with influenza A/H3N2-specific HAI titers, suggesting these DEGs at the individual level may have a limited role in protection against influenza. Our findings emphasize the need for further investigation into other factors influencing immunity against influenza in older adults.

Virus-specific and shared gene expression signatures in immune cells after vaccination in response to influenza and vaccinia stimulation

Background

In the vaccine era, individuals receive multiple vaccines in their lifetime. Host gene expression in response to antigenic stimulation is usually virus-specific; however, identifying shared pathways of host response across a wide spectrum of vaccine pathogens can shed light on the molecular mechanisms/components which can be targeted for the development of broad/universal therapeutics and vaccines.

Method

We isolated PBMCs, monocytes, B cells, and CD8+ T cells from the peripheral blood of healthy donors, who received both seasonal influenza vaccine (within <1 year) and smallpox vaccine (within 1 - 4 years). Each of the purified cell populations was stimulated with either influenza virus or vaccinia virus. Differentially expressed genes (DEGs) relative to unstimulated controls were identified for each in vitro viral infection, as well as for both viral infections (shared DEGs). Pathway enrichment analysis was performed to associate identified DEGs with KEGG/biological pathways.

Results

We identified 2,906, 3,888, 681, and 446 DEGs in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, in response to influenza stimulation. Meanwhile, 97, 120, 20, and 10 DEGs were identified as gene signatures in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, upon vaccinia stimulation. The majority of DEGs identified in PBMCs were also found in monocytes after either viral stimulation. Of the virus-specific DEGs, 55, 63, and 9 DEGs occurred in common in PBMCs, monocytes, and B cells, respectively, while no DEGs were shared in infected CD8+ T cells after influenza and vaccinia. Gene set enrichment analysis demonstrated that these shared DEGs were over-represented in innate signaling pathways, including cytokine-cytokine receptor interaction, viral protein interaction with cytokine and cytokine receptor, Toll-like receptor signaling, RIG-I-like receptor signaling pathways, cytosolic DNA-sensing pathways, and natural killer cell mediated cytotoxicity.

Conclusion

Our results provide insights into virus-host interactions in different immune cells, as well as host defense mechanisms against viral stimulation. Our data also highlights the role of monocytes as a major cell population driving gene expression in ex vivo PBMCs in response to viral stimulation. The immune response signaling pathways identified in this study may provide specific targets for the development of novel virus-specific therapeutics and improved vaccines for vaccinia and influenza. Although influenza and vaccinia viruses have been selected in this study as pathogen models, this approach could be applicable to other pathogens.

T Cell Transcriptional Signatures of Influenza A/H3N2 Antibody Response to High Dose Influenza and Adjuvanted Influenza Vaccine in Older Adults

Older adults experience declining influenza vaccine-induced immunity and are at higher risk of influenza and its complications. For this reason, high dose (e.g., Fluzone) and adjuvanted (e.g., Fluad) vaccines are preferentially recommended for people age 65 years and older. However, T cell transcriptional activity shaping the humoral immune responses to Fluzone and Fluad vaccines in older adults is still poorly understood. We designed a study of 234 older adults (≥65 years old) who were randomly allocated to receive Fluzone or Fluad vaccine and provided blood samples at baseline and at Day 28 after immunization. We measured the humoral immune responses (hemagglutination inhibition/HAI antibody titer) to influenza A/H3N2 and performed mRNA-Seq transcriptional profiling in purified CD4+ T cells, in order to identify T cell signatures that might explain differences in humoral immune response by vaccine type. Given the large differences in formulation (higher antigen dose vs adjuvant), our hypothesis was that each vaccine elicited a distinct transcriptomic response after vaccination. Thus, the main focus of our study was to identify the differential gene expression influencing the antibody titer in the two vaccine groups. Our analyses identified three differentially expressed, functionally linked genes/proteins in CD4+ T cells: the calcium/calmodulin dependent serine/threonine kinase IV (CaMKIV); its regulator the TMEM38B/transmembrane protein 38B, involved in maintenance of intracellular Ca2+ release; and the transcriptional coactivator CBP/CREB binding protein, as regulators of transcriptional activity/function in CD4+ T cells that impact differences in immune response by vaccine type. Significantly enriched T cell-specific pathways/biological processes were also identified that point to the importance of genes/proteins involved in Th1/Th2 cell differentiation, IL-17 signaling, calcium signaling, Notch signaling, MAPK signaling, and regulation of TRP cation Ca2+ channels in humoral immunity after influenza vaccination. In summary, we identified the genes/proteins and pathways essential for cell activation and function in CD4+ T cells that are associated with differences in influenza vaccine-induced humoral immunity by vaccine type. These findings provide an additional mechanistic perspective for achieving protective immunity in older adults.

Transcriptional signatures associated with rubella virus-specific humoral immunity after a third dose of MMR vaccine in women of childbearing age

Multiple factors linked to host genetics/inherent biology play a role in interindividual variability in immune response outcomes after rubella vaccination. In order to identify these factors, we conducted a study of rubella-specific humoral immunity before (Baseline) and after (Day 28) a third dose of MMR-II vaccine in a cohort of 109 women of childbearing age. We performed mRNA-Seq profiling of PBMCs after rubella virus in vitro stimulation to delineate genes associated with post-vaccination rubella humoral immunity and to define genes mediating the association between prior immune response status (high or low antibody) and subsequent immune response outcome. Our study identified novel genes that mediated the association between prior immune response and neutralizing antibody titer after a third MMR vaccine dose. These genes included the following: CDC34; CSNK1D; APOBEC3F; RAD18; AAAS; SLC37A1; FAS; and JAK2. The encoded proteins are involved in innate antiviral response, IFN/cytokine signaling, B cell repertoire generation, the clonal selection of B lymphocytes in germinal centers, and somatic hypermutation/antibody affinity maturation to promote optimal antigen-specific B cell immune function. These data advance our understanding of how subjects' prior immune status and/or genetic propensity to respond to rubella/MMR vaccination ultimately affects innate immunity and humoral immune outcomes after vaccination.

Sex-specific differences of humoral immunity and transcriptome diversification in older adults vaccinated with inactivated quadrivalent influenza vaccines

Clinical data showed sex variability in the immune response to influenza vaccination, this study aimed to investigate differentially expressed genes (DEGs) that contribute to sex-bias immunity to quadrivalent inactivated influenza vaccines (QIVs) in the elderly. 60 healthy adults aged 60-80 yrs were vaccinated with QIVs, and gene expression was analyzed before and after vaccination. The humoral immunity was analyzed by HAI assay, and the correlation of gene expression patterns of two sex groups with humoral immunity was analyzed. The DEGs involved in type I interferon signaling pathway and complement activation of classical pathway were upregulated within 3 days in females. At Day 28, the immune response showed a male-bias pattern associated with the regulation of protein processing and complement activation of classical pathway. A list of DEGs associated with variant responses to influenza vaccination between females and males were identified by biology-driven clustering. Old females have a greater immune response to QIVs but a rapid antibody decline, while old males have the advantages to sustain a durable response. In addition, we identified genes that may contribute to the sex variations toward influenza vaccination in the aged. Our findings highlight the importance of developing personalized seasonal influenza vaccines.

Identifying Potential Candidate Hub Genes and Functionally Enriched Pathways in the Immune Responses to Quadrivalent Inactivated Influenza Vaccines in the Elderly Through Co-Expression Network Analysis

Insights into the potential candidate hub genes may facilitate the generation of safe and effective immunity against seasonal influenza as well as the development of personalized influenza vaccines for the elderly at high risk of influenza virus infection. This study aimed to identify the potential hub genes related to the immune induction process of the 2018/19 seasonal quadrivalent inactivated influenza vaccines (QIVs) in the elderly ≥60 years by using weighted gene co-expression network analysis (WGCNA). From 63 whole blood samples from16 elderly individuals, a total of 13,345 genes were obtained and divided into eight co-expression modules, with two modules being significantly correlated with vaccine-induced immune responses. After functional enrichment analysis, genes under GO terms of vaccine-associated immunity were used to construct the sub-network for identification and functional validation of hub genes. MCEMP1 and SPARC were confirmed as the hub genes with an obvious effect on QIVs-induced immunity. The MCEMP1 expression was shown to be negatively correlated with the QIVs-associated reactogenicity within 7 days after vaccination, which could be suppressed by the CXCL 8/IL-8 and exacerbated by the Granzyme-B cytotoxic mediator. Meanwhile, the SPARC expression was found to increase the immune responses to the QIVs and contribute to the persistence of protective humoral antibody titers. These two genes can be used to predict QIVs-induced adverse reaction, the intensity of immune responses, and the persistence of humoral antibody against influenza. This work has shed light on further research on the development of personalized QIVs with appropriate immune responses and long-lasting immunity against the forthcoming seasonal influenza.

The impact of physical frailty on the response to inactivated influenza vaccine in older adults

Physical frailty's impact on hemagglutination inhibition antibody titers (HAI) and peripheral blood mononuclear cell (PBMC) transcriptional responses after influenza vaccination is unclear. Physical frailty was assessed using the 5-item Fried frailty phenotype in 168 community- and assisted-living adults ≥55 years of age during an observational study. Blood was drawn before, 3, 7, and 28 days post-vaccination with the 2017-2018 inactivated influenza vaccine. HAI response to the A/H1N1 strain was measured at Days 0 and 28 using seropositivity, seroconversion, log2 HAI titers, and fold-rise in log2 HAI titers. RNA sequencing of PBMCs from Days 0, 3 and 7 was measured in 28 participants and compared using pathway analyses. Frailty was not significantly associated with any HAI outcome in multivariable models. Compared with non-frail participants, frail participants expressed decreased cell proliferation, metabolism, antibody production, and interferon signaling genes. Conversely, frail participants showed elevated gene expression in IL-8 signaling, T-cell exhaustion, and oxidative stress pathways compared with non-frail participants. These results suggest that reduced effectiveness of influenza vaccine among older, frail individuals may be attributed to immunosenescence-related changes in PBMCs that are not reflected in antibody levels.

The Role of Systems Vaccinology in Understanding the Immune Defects to Vaccination in Solid Organ Transplant Recipients

Solid organ transplant recipients (SOTRs) are at increased risk for many infections, whether viral, bacterial, or fungal, due to immunosuppressive therapy to prevent organ rejection. The same immune defects that render transplanted patients susceptible to infection dampen their immune response to vaccination. Therefore, it is vital to identify immune defects to vaccination in transplant recipients and methods to obviate them. These methods can include alternative vaccine composition, dosage, adjuvants, route of administration, timing, and re-vaccination strategies. Systems biology is a relatively new field of study, which utilizes high throughput means to better understand biological systems and predict outcomes. Systems biology approaches have been used to help obtain a global picture of immune responses to infections and vaccination (i.e. systems vaccinology), but little work has been done to use systems biology to improve vaccine efficacy in immunocompromised patients, particularly SOTRs, thus far. Systems vaccinology approaches may hold key insights to vaccination in this vulnerable population.

Durability of humoral immune responses to rubella following MMR vaccination

BACKGROUND

While administration of the measles-mumps-rubella (MMR-II®) vaccine has been effective at preventing rubella infection in the United States, the durability of humoral immunity to the rubella component of MMR vaccine has not been widely studied among older adolescents and adults.

METHODS

In this longitudinal study, we sought to assess the durability of rubella virus (RV)-specific humoral immunity in a healthy population (n = 98) of adolescents and young adults at two timepoints: ~7 and ~17 years after two doses of MMR-II® vaccination. Levels of circulating antibodies specific to RV were measured by ELISA and an immune-colorimetric neutralization assay. RV-specific memory B cell responses were also measured by ELISpot.

RESULTS

Rubella-specific IgG antibody titers, neutralizing antibody titers, and memory B cell responses declined with increasing time since vaccination; however, these decreases were relatively moderate. Memory B cell responses exhibited a greater decline in men compared to women.

CONCLUSIONS

Collectively, rubella-specific humoral immunity declines following vaccination, although subjects' antibody titers remain well above the currently recognized threshold for protective immunity. Clinical correlates of protection based on neutralizing antibody titer and memory B cell ELISpot response should be defined.

Rubella virus-specific humoral immune responses and their interrelationships before and after a third dose of measles-mumps-rubella vaccine in women of childbearing age

In the U.S., measles, mumps, and rubella vaccination is recommended as two vaccine doses. A third dose of measles-mumps-rubella (MMR) vaccine is being administered in certain situations (e.g., identified seronegativity and during outbreaks). We studied rubella-specific humoral immunity (neutralizing antibody, enzyme-linked immunosorbent assay/ELISA IgG titer and antibody avidity) and the frequencies of antigen-specific memory B cells before and after a third dose of MMR-II in 109 female participants of childbearing age (median age, 34.5 years old) from Olmsted County, MN, with two documented prior MMR vaccine doses. The participants were selected from a cohort of 1117 individuals if they represented the high and the low ends of the rubella-specific antibody response spectrum. Of the 109 participants, we identified four individuals (3.67% of all study participants; 7.14% of the low-responder group) that were seronegative at Baseline (rubella-specific ELISA IgG titers <10 IU/mL), suggesting a lack of protection against rubella before receipt of a third MMR vaccine dose. The peak geometric mean neutralizing antibody titer one month following the third dose of MMR vaccine for the cohort was 243 NT₅₀ (CI; 241, 245), which is expected for a cohort with two doses of MMR, and the peak geometric mean IgG titer was 150 IU/mL (CI; 148, 152) with no seronegative individuals at Day 28. One-third of all subjects (31.8% for the neutralizing antibody; 30.8% for the IgG titer) experienced a significant boost (≥4-fold) of antibody titers one month following vaccination. Antibody titers and other tested immune-response variables were significantly higher in the high-responder group compared to the low-responder group. The frequencies of rubella-specific memory B cells were modestly associated with the antibody titers. Our study suggests the importance of yet unknown inherent biologic and immune factors for the generation and maintenance of rubella-vaccine-induced humoral immune responses.

Microarray Gene Expression Dataset Re-analysis Reveals Variability in Influenza Infection and Vaccination

Influenza, a communicable disease, affects thousands of people worldwide. Young children, elderly, immunocompromised individuals and pregnant women are at higher risk for being infected by the influenza virus. Our study aims to highlight differentially expressed genes in influenza disease compared to influenza vaccination, including variability due to age and sex. To accomplish our goals, we conducted a meta-analysis using publicly available microarray expression data. Our inclusion criteria included subjects with influenza, subjects who received the influenza vaccine and healthy controls. We curated 18 microarray datasets for a total of 3,481 samples (1,277 controls, 297 influenza infection, 1,907 influenza vaccination). We pre-processed the raw microarray expression data in R using packages available to pre-process Affymetrix and Illumina microarray platforms. We used a Box-Cox power transformation of the data prior to our down-stream analysis to identify differentially expressed genes. Statistical analyses were based on linear mixed effects model with all study factors and successive likelihood ratio tests (LRT) to identify differentially-expressed genes. We filtered LRT results by disease (Bonferroni adjusted p < 0.05) and used a two-tailed 10% quantile cutoff to identify biologically significant genes. Furthermore, we assessed age and sex effects on the disease genes by filtering for genes with a statistically significant (Bonferroni adjusted p < 0.05) interaction between disease and age, and disease and sex. We identified 4,889 statistically significant genes when we filtered the LRT results by disease factor, and gene enrichment analysis (gene ontology and pathways) included innate immune response, viral process, defense response to virus, Hematopoietic cell lineage and NF-kappa B signaling pathway. Our quantile filtered gene lists comprised of 978 genes each associated with influenza infection and vaccination. We also identified 907 and 48 genes with statistically significant (Bonferroni adjusted p < 0.05) disease-age and disease-sex interactions, respectively. Our meta-analysis approach highlights key gene signatures and their associated pathways for both influenza infection and vaccination. We also were able to identify genes with an age and sex effect. This gives potential for improving current vaccines and exploring genes that are expressed equally across ages when considering universal vaccinations for influenza.

Aging and influenza vaccine-induced immunity

Immunosenescence is defined as the progressive deterioration of the immune system with aging. Immunosenescence stifles the generation of protective B and T cell-mediated adaptive immunity in response to various pathogens, resulting in increased disease susceptibility and severity in the elderly population. In particular, immunosenescence has major impacts on the phenotype, function, and receptor repertoire of B and T cells in the elderly, hindering protective responses induced by seasonal influenza virus vaccination. In order to overcome the detrimental impacts of immunosenescence on protective immunity to influenza viruses, we review our current understanding of the effects of aging on adaptive immune responses to influenza and discuss current and future avenues of vaccine research for eliciting more potent anti-influenza immunity in the elderly.

Immunosenescence and human vaccine immune responses

The age-related dysregulation and decline of the immune system-collectively termed "immunosenescence"-has been generally associated with an increased susceptibility to infectious pathogens and poor vaccine responses in older adults. While numerous studies have reported on the clinical outcomes of infected or vaccinated individuals, our understanding of the mechanisms governing the onset of immunosenescence and its effects on adaptive immunity remains incomplete. Age-dependent differences in T and B lymphocyte populations and functions have been well-defined, yet studies that demonstrate direct associations between immune cell function and clinical outcomes in older individuals are lacking. Despite these knowledge gaps, research has progressed in the development of vaccine and adjuvant formulations tailored for older adults in order to boost protective immunity and overcome immunosenescence. In this review, we will discuss the development of vaccines for older adults in light of our current understanding-or lack thereof-of the aging immune system. We highlight the functional changes that are known to occur in the adaptive immune system with age, followed by a discussion of current, clinically relevant pathogens that disproportionately affect older adults and are the central focus of vaccine research efforts for the aging population. We conclude with an outlook on personalized vaccine development for older adults and areas in need of further study in order to improve our fundamental understanding of adaptive immunosenescence.

Systems Immunology: Learning the Rules of the Immune System

Given the many cell types and molecular components of the human immune system, along with vast variations across individuals, how should we go about developing causal and predictive explanations of immunity? A central strategy in human studies is to leverage natural variation to find relationships among variables, including DNA variants, epigenetic states, immune phenotypes, clinical descriptors, and others. Here, we focus on how natural variation is used to find patterns, infer principles, and develop predictive models for two areas: (a) immune cell activation-how single-cell profiling boosts our ability to discover immune cell types and states-and (b) antigen presentation and recognition-how models can be generated to predict presentation of antigens on MHC molecules and their detection by T cell receptors. These are two examples of a shift in how we find the drivers and targets of immunity, especially in the human system in the context of health and disease.

RITAN: rapid integration of term annotation and network resources

Background

Identifying the biologic functions of groups of genes identified in high-throughput studies currently requires considerable time and/or bioinformatics experience. This is due in part to each resource housed within separate databases, requiring users to know about them, and integrate across them. Time consuming and often repeated for each study, integrating across resources and merging with data under study is an increasingly common bioinformatics task.

Methods

We developed an open-source R software package for assisting researchers in annotating their genesets with functions, pathways, and their interconnectivity across a diversity of network resources.

Results

We present rapid integration of term annotation and network resources (RITAN) for the rapid and comprehensive annotation of a list of genes using functional term and pathway resources and their relationships among each other using multiple network biology resources. Currently, and to comply with data redistribution policies, RITAN allows rapid access to 16 term annotations spanning gene ontology, biologic pathways, and immunologic modules, and nine network biology resources, with support for user-supplied resources; we provide recommendations for additional resources and scripts to facilitate their addition to RITAN. Having the resources together in the same system allows users to derive novel combinations. RITAN has a growing set of tools to explore the relationships within resources themselves. These tools allow users to merge resources together such that the merged annotations have a minimal overlap with one another. Because we index both function annotation and network interactions, the combination allows users to expand small groups of genes using links from biologic networks—either by adding all neighboring genes or by identifying genes that efficiently connect among input genes—followed by term enrichment to identify functions. That is, users can start from a core set of genes, identify interacting genes from biologic networks, and then identify the functions to which the expanded list of genes contribute.

Conclusion

We believe RITAN fills the important niche of bridging the results of high-throughput experiments with the ever-growing corpus of functional annotations and network biology resources.

Availability

Rapid integration of term annotation and network resources is available as an R package at github.com/MTZimmer/RITAN and BioConductor.org.

Immunosenescence: A systems-level overview of immune cell biology and strategies for improving vaccine responses

Immunosenescence contributes to a decreased capacity of the immune system to respond effectively to infections or vaccines in the elderly. The full extent of the biological changes that lead to immunosenescence are unknown, but numerous cell types involved in innate and adaptive immunity exhibit altered phenotypes and function as a result of aging. These manifestations of immunosenescence at the cellular level are mediated by dysregulation at the genetic level, and changes throughout the immune system are, in turn, propagated by numerous cellular interactions. Environmental factors, such as nutrition, also exert significant influence on the immune system during aging. While the mechanisms that govern the onset of immunosenescence are complex, systems biology approaches allow for the identification of individual contributions from each component within the system as a whole. Although there is still much to learn regarding immunosenescence, systems-level studies of vaccine responses have been highly informative and will guide the development of new vaccine candidates, novel adjuvant formulations, and immunotherapeutic drugs to improve vaccine responses among the aging population.

Sex Differences in Older Adults' Immune Responses to Seasonal Influenza Vaccination

Background: Sex differences in immune responses to influenza vaccine may impact efficacy across populations. Methods: In a cohort of 138 older adults (50-74 years old), we measured influenza A/H1N1 antibody titers, B-cell ELISPOT response, PBMC transcriptomics, and PBMC cell compositions at 0, 3, and 28 days post-immunization with the 2010/11 seasonal inactivated influenza vaccine. Results: We identified higher B-cell ELISPOT responses in females than males. Potential mechanisms for sex effects were identified in four gene clusters related to T, NK, and B cells. Mediation analysis indicated that sex-dependent expression in T and NK cell genes can be partially attributed to higher CD4+ T cell and lower NK cell fractions in females. We identified strong sex effects in 135 B cell genes whose expression correlates with ELISPOT measures, and found that cell subset differences did not explain the effect of sex on these genes' expression. Post-vaccination expression of these genes, however, mediated 41% of the sex effect on ELISPOT responses. Conclusions: These results improve our understanding of sexual dimorphism in immunity and influenza vaccine response.

Older Human B Cells and Antibodies

B cells have a number of different roles in the immune response. Their excellent antigen presentation potential can contribute to the activation of other cells of the immune system, and evidence is emerging that specialized subsets of these cells, that may be increased with age, can influence the cell-mediated immune system in antitumor responses. They can also regulate immune responses, to avoid autoreactivity and excessive inflammation. Deficiencies in regulatory B cells may be beneficial in cancer but will only exacerbate the inflammatory environment that is a hallmark of aging. The B cell role as antibody producers is particularly important, since antibodies perform numerous different functions in different environments. Although studying tissue responses in humans is not as easy as in mice, we do know that certain classes of antibodies are more suited to protecting the mucosal tissues (IgA) or responding to T-independent bacterial polysaccharide antigens (IgG₂) so we can make some inference with respect to tissue-specific immunity from a study of peripheral blood. We can also make inferences about changes in B cell development with age by looking at the repertoire of different B cell populations to see how age affects the selection events that would normally occur to avoid autoreactivity, or increase specificity, to antigen.

Gene expression profiling toward the next generation safety control of influenza vaccines and adjuvants in Japan

Influenza becomes epidemic worldwide every year, and many individuals receive vaccination annually. Quality control relating to safety and potency of influenza vaccines is important to maintain public confidence. The safety of influenza vaccines has been assessed by clinical trials, and animal safety tests are performed to monitor the consistent quality between vaccines used for clinical trials and marketing; the biological responses in vaccinated animals are evaluated, including changes in body weight and white blood cell count. Animal safety tests have been contributing to the quality relating to the safety of influenza vaccines for decades, but improvements are needed. Although precise mechanisms involving biological changes in animal safety tests have not been fully elucidated, the application of cDNA microarray technology make it possible to reliably identify genes related to biological responses in vaccinated animals. From analysis of the expression profile of >10,000 genes of lung in animals treated with an inactivated whole virion influenza vaccine, we identified 17 marker genes whose expression patterns correlated well to changes in body weight and leukocyte count in vaccinated animals. In influenza HA vaccine-treated animals exhibiting subtle changes in biological responses, a robust expression pattern of marker genes was found. Furthermore, these marker genes could also be used in the evaluation of adjuvanted influenza vaccines. The expression profile of marker genes is expected to be an alternative indicator for safety control of various influenza vaccines conferring high sensitivity and short turnaround time. Thus, gene expression profiling may be a powerful tool for safety control of vaccines in the future.

Cytokine production in whole-blood cultures following immunization with an influenza vaccine

A clinical trial of a quadrivalent split influenza vaccine was performed in the 2014/15 season. Sixty-four subjects aged 6 months to 18 years were enrolled in order to investigate the relationship between cellular and humoral immune responses. Subjects were categorized into two groups by measuring neutralizing antibodies: non-primed naïve/primed or seroconverted/non-seroconverted groups. Whole-blood cultures were stimulated with the H1N1 split antigen before immunization and one month after the first and second immunizations for subjects < 13 years and before and one month after the first dose for those ≥ 13 years in order to investigate cytokine production. Significant amounts of IL-2, IL-12, IL-13, MCP-1, MIP-1β, and TNF-α were detected from one month after the first dose in the naïve group. In addition to these cytokines, the production of IL-1β, IL-4, IL-6, IL-8, IL-10, IL-17, G-CSF, and IFN-γ was enhanced one month after the second dose. No significant increase was noted in the primed group, except in the production of IL-10. In seroconverted subjects, the production of IL-2, IL-4, IL-8, IL-10, G-CSF, MCP-1, TNF-α, and IFN-γ increased one month after the first dose, which was earlier than in the naïve group, whereas no significant cytokine response was noted in subjects without seroconversion. Subjects ≥ 13 years were primed and the production of G-CSF, IL-4, and IL-1β increased in subjects with seroconversion. Whole-blood cultures were also stimulated with the H3N2 split antigen and similar cytokine profiles were obtained. Many cytokines and chemokines, including inflammatory cytokines, were produced in seroconverted, but not non-seroconverted subjects.

Transcriptomic signatures of cellular and humoral immune responses in older adults after seasonal influenza vaccination identified by data-driven clustering

PBMC transcriptomes after influenza vaccination contain valuable information about factors affecting vaccine responses. However, distilling meaningful knowledge out of these complex datasets is often difficult and requires advanced data mining algorithms. We investigated the use of the data-driven Weighted Gene Correlation Network Analysis (WGCNA) gene clustering method to identify vaccine response-related genes in PBMC transcriptomic datasets collected from 138 healthy older adults (ages 50-74) before and after 2010-2011 seasonal trivalent influenza vaccination. WGCNA separated the 14,197 gene dataset into 15 gene clusters based on observed gene expression patterns across subjects. Eight clusters were strongly enriched for genes involved in specific immune cell types and processes, including B cells, T cells, monocytes, platelets, NK cells, cytotoxic T cells, and antiviral signaling. Examination of gene cluster membership identified signatures of cellular and humoral responses to seasonal influenza vaccination, as well as pre-existing cellular immunity. The results of this study illustrate the utility of this publically available analysis methodology and highlight genes previously associated with influenza vaccine responses (e.g., CAMK4, CD19), genes with functions not previously identified in vaccine responses (e.g., SPON2, MATK, CST7), and previously uncharacterized genes (e.g. CORO1C, C8orf83) likely related to influenza vaccine-induced immunity due to their expression patterns.

Detection and Quantification of Influenza A/H1N1 Virus-Specific Memory B Cells in Human PBMCs Using ELISpot Assay

Immune response following subsequent encounter of viruses (and vaccines) relies largely on the pool and frequencies of antigen-specific memory B cells. In addition to antibody titers, the reliable measurement of these cells in human blood (peripheral blood mononuclear cells/PBMCs or purified B cells) provides valuable information on the preparedness of the adaptive immune system to respond to infection or vaccines, and potentially supports the discovery of new quantitative correlates of protection. The Mayo Clinic Vaccine Research Group has developed and optimized a high-throughput ELISPOT-based assay for the quantification of influenza A/H1N1 virus-specific memory B cells in human PBMCs. Here, we present the materials and detailed methodology for using this assay on cryopreserved cells for the measurement of recall humoral immunity readiness (antigen-specific memory B cell frequencies) after influenza vaccination. This assay could be readily adapted to other influenza virus strains and other respiratory viruses and vaccines for use in systems biology and larger population-based studies.

Differential gene expression elicited by children in response to the 2015-16 live attenuated versus inactivated influenza vaccine

BACKGROUND

In recent influenza seasons, the live attenuated influenza vaccine (LAIV) has not demonstrated the same level of vaccine effectiveness as that observed among children who received the inactivated influenza vaccine (IIV). To better understand this difference, this study compared the mRNA sequencing transcription profile (RNA seq) in children who received either IIV or LAIV.

METHODS

Children 3-17years of age receiving quadrivalent influenza vaccine were enrolled. Blood samples were collected on Day 0 prior to vaccination and again on Day 7 (range 6-10days) following vaccination. Total RNA was isolated from PAXgene tubes and sequenced for a custom panel of 89 transcripts using the TruSeq Targeted RNA Expression method. Fold differences in normalized RNA seq counts from Day 0 to Day 7 were calculated, log₂ transformed and compared between the two vaccine groups.

RESULTS

Of 72 children, 46 received IIV and 26 received LAIV. Following IIV vaccination, 7 genes demonstrated significant differential expression at Day 7 (down-regulated). In contrast, following LAIV vaccination, 8 genes demonstrated significant differential expression at Day 7 (5 up-regulated and 3 down-regulated). Only two genes demonstrated similar patterns of regulation in both groups.

CONCLUSIONS

Differential regulation of genes was observed between 2015-16 LAIV and IIV recipients. These results help to elucidate the immune response to influenza vaccines and may be related to the difference in vaccine effectiveness observed in recent years between LAIV and IIV.

Systems immunology: just getting started

Systems-biology approaches in immunology take various forms, but here we review strategies for measuring a broad swath of immunological functions as a means of discovering previously unknown relationships and phenomena and as a powerful way of understanding the immune system as a whole. This approach has rejuvenated the field of vaccine development and has fostered hope that new ways will be found to combat infectious diseases that have proven refractory to classical approaches. Systems immunology also presents an important new strategy for understanding human immunity directly, taking advantage of the many ways the immune system of humans can be manipulated.

Integration of Immune Cell Populations, mRNA-Seq, and CpG Methylation to Better Predict Humoral Immunity to Influenza Vaccination: Dependence of mRNA-Seq/CpG Methylation on Immune Cell Populations

The development of a humoral immune response to influenza vaccines occurs on a multisystems level. Due to the orchestration required for robust immune responses when multiple genes and their regulatory components across multiple cell types are involved, we examined an influenza vaccination cohort using multiple high-throughput technologies. In this study, we sought a more thorough understanding of how immune cell composition and gene expression relate to each other and contribute to interindividual variation in response to influenza vaccination. We first hypothesized that many of the differentially expressed (DE) genes observed after influenza vaccination result from changes in the composition of participants' peripheral blood mononuclear cells (PBMCs), which were assessed using flow cytometry. We demonstrated that DE genes in our study are correlated with changes in PBMC composition. We gathered DE genes from 128 other publically available PBMC-based vaccine studies and identified that an average of 57% correlated with specific cell subset levels in our study (permutation used to control false discovery), suggesting that the associations we have identified are likely general features of PBMC-based transcriptomics. Second, we hypothesized that more robust models of vaccine response could be generated by accounting for the interplay between PBMC composition, gene expression, and gene regulation. We employed machine learning to generate predictive models of B-cell ELISPOT response outcomes and hemagglutination inhibition (HAI) antibody titers. The top HAI and B-cell ELISPOT model achieved an area under the receiver operating curve (AUC) of 0.64 and 0.79, respectively, with linear model coefficients of determination of 0.08 and 0.28. For the B-cell ELISPOT outcomes, CpG methylation had the greatest predictive ability, highlighting potentially novel regulatory features important for immune response. B-cell ELISOT models using only PBMC composition had lower performance (AUC = 0.67), but highlighted well-known mechanisms. Our analysis demonstrated that each of the three data sets (cell composition, mRNA-Seq, and DNA methylation) may provide distinct information for the prediction of humoral immune response outcomes. We believe that these findings are important for the interpretation of current omics-based studies and set the stage for a more thorough understanding of interindividual immune responses to influenza vaccination.

Immunosenescence-Related Transcriptomic and Immunologic Changes in Older Individuals Following Influenza Vaccination

The goal of annual influenza vaccination is to reduce mortality and morbidity associated with this disease through the generation of protective immune responses. The objective of the current study was to examine markers of immunosenescence and identify immunosenescence-related differences in gene expression, gene regulation, cytokine secretion, and immunologic changes in an older study population receiving seasonal influenza A/H1N1 vaccination. Surprisingly, prior studies in this cohort revealed weak correlations between immunosenescence markers and humoral immune response to vaccination. In this report, we further examined the relationship of each immunosenescence marker (age, T cell receptor excision circle frequency, telomerase expression, percentage of CD28⁻ CD4⁺ T cells, percentage of CD28⁻ CD8⁺ T cells, and the CD4/CD8 T cell ratio) with additional markers of immune response (serum cytokine and chemokine expression) and measures of gene expression and/or regulation. Many of the immunosenescence markers indeed correlated with distinct sets of individual DNA methylation sites, miRNA expression levels, mRNA expression levels, serum cytokines, and leukocyte subsets. However, when the individual immunosenescence markers were grouped by pathways or functional terms, several shared biological functions were identified: antigen processing and presentation pathways, MAPK, mTOR, TCR, BCR, and calcium signaling pathways, as well as key cellular metabolic, proliferation and survival activities. Furthermore, the percent of CD4⁺ and/or CD8⁺ T cells lacking CD28 expression also correlated with miRNAs regulating clusters of genes known to be involved in viral infection. Integrated (DNA methylation, mRNA, miRNA, and protein levels) network biology analysis of immunosenescence-related pathways and genesets identified both known pathways (e.g., chemokine signaling, CTL, and NK cell activity), as well as a gene expression module not previously annotated with a known function. These results may improve our ability to predict immune responses to influenza and aid in new vaccine development, and highlight the need for additional studies to better define and characterize immunosenescence.

B Cell-Specific Biomarkers for Optimal Antibody Responses to Influenza Vaccination and Molecular Pathways That Reduce B Cell Function with Aging

This review highlights recent findings on the effects of aging on influenza vaccine responses, with major emphasis on T and B cells, which are significantly impaired by aging. We discuss changes in T cell production and thymic output; T cell subsets; and TCR repertoire, function, and response to latent persistent infection. We also discuss changes in B cell subsets, repertoire, and function, and how function is impaired by increased intrinsic B cell inflammation and reduced signal transduction. This review presents age-related effects on antigen-presenting cells, summarizes recent studies, including our own, aimed at the identification of biomarkers of protective vaccine responses, and provides examples of recent technical advances and insights into human vaccine responses that are helping to define the features associated with successful vaccination and that may enable a more predictive vaccinology in the future.