Genome-wide characterization of transcriptional patterns in high and low antibody responders to rubella vaccination. PLoS One. 2013;8:e62149. [PMID: 23658707 PMCID: PMC3641062 DOI: 10.1371/journal.pone.0062149]

Advancing the Science of Vaccine Safety During the Coronavirus Disease 2019 (COVID-19) Pandemic and Beyond: Launching an International Network of Special Immunization Services

Within 2 years after the start of the coronavirus disease 2019 (COVID-19) pandemic, novel severe acute respiratory syndrome coronavirus 2 vaccines were developed, rigorously evaluated in large phase 3 trials, and administered to more than 5 billion individuals globally. However, adverse events of special interest (AESIs) have been described post-implementation, including myocarditis after receipt of messenger RNA (mRNA) vaccines and thrombosis with thrombocytopenia syndrome after receipt of adenoviral vector vaccines. AESIs are rare (<1 to 10/100 000 vaccinees) and less frequent than COVID-19 complications, though they have associated morbidity and mortality. The diversity of COVID-19 vaccine platforms (eg, mRNA, viral vector, protein) and rates of AESIs both between and within platforms (eg, higher rate of myocarditis after mRNA-1273 vs BNT162b2 vaccines) present an important opportunity to advance vaccine safety science. The International Network of Special Immunization Services has been formed with experts in vaccine safety, systems biology, and other relevant disciplines to study cases of AESIs and matched controls to uncover the pathogenesis of rare AESIs and inform vaccine development.

Predictors associated with a better response to the Japanese aluminum-free hepatitis A vaccine, Aimmugen® , for people living with HIV

AIM

After the hepatitis A virus (HAV) outbreak among men who have sex with men (MSM) around 2018, the importance of HAV vaccination was emphasized, especially for MSM-living with human immunodeficiency virus (MSM-LWHIV). Aimmugen^® is licensed and distributed exclusively in Japan. While administration of three doses is recommended, 85% of recipients in the general population were reported to acquire seroprotection after the second dose. In this study, we evaluated the efficacy of two or three vaccine doses along with predictors associated with the response to Aimmugen^® in MSM-LWHIV.

METHODS

We retrospectively examined anti-HA-IgG titers of MSM-LWHIV vaccinated with Aimmugen^® in our hospital. Patients' data were collected from medical records.

RESULTS

Between January 2018 and October 2019, 141 subjects whose median age was 46 years old, were examined. All the subjects were on antiretroviral therapy (ART) and the median CD4 count was 615/μL. The acquisition rate of protectable anti-HA-IgG titers after the second and third dose was 71.1% and 98.6%, respectively. In 114 subjects whose anti-HA-IgG titers were tested after the second-dose, factors significantly associated with better response were prolonged ART duration and higher CD4 count. The titers of anti-HA-IgG after the third dose were higher in those who became seropositive after the second-dose than those who did not.

CONCLUSIONS

Three-dose of Aimmugen^® for MSM-LWHIV was effective while two-dose was less effective compared to non-HIV-infected people. People-LWHIV with shorter duration of ART and lesser CD4 cell count achieved lower titers of anti-HA-IgG and might require an additional vaccination.

Transcriptome Analysis of Peripheral Blood Mononuclear Cells in SARS-CoV-2 Naïve and Recovered Individuals Vaccinated With Inactivated Vaccine

The urgent approval of the use of the inactivated COVID-19 vaccine is essential to reduce the threat and burden of the epidemic on global public health, however, our current understanding of the host immune response to inactivated vaccine remains limited. Herein, we performed serum IgG antibody detection and transcriptomics analysis on 20 SARS-CoV-2 naïve individuals who received multiple doses of inactivated vaccine and 5 SARS-CoV-2 recovered individuals who received single dose of inactivated vaccine. Our research revealed the important role of many innate immune pathways after vaccination, identified a significant correlation with the third dose of booster vaccine and proteasome-related genes, and found that SARS-CoV-2 recovered individuals can produces a strong immune response to a single dose of inactivated vaccine. These results help us understand the reaction mechanism of the host's molecular immune system to the inactivated vaccine, and provide a basis for the choice of vaccination strategy.

Transcriptomic signatures induced by the Ebola virus vaccine rVSVΔG-ZEBOV-GP in adult cohorts in Europe, Africa, and North America: a molecular biomarker study

BACKGROUND

A recombinant vesicular stomatitis virus vector expressing the Zaire Ebola virus glycoprotein (rVSVΔG-ZEBOV-GP) vaccine has been reported as safe, immunogenic, and highly protective in a ring vaccination trial. We aimed to identify transcriptomic immune response biomarker signatures induced by vaccination and associated signatures with its immunogenicity and reactogenicity to better understand the potential mechanisms of action of the vaccine.

METHODS

354 healthy adult volunteers were vaccinated in randomised, double-blind, placebo-controlled trials in Europe (Geneva, Switzerland [November, 2014, to January, 2015]) and North America (USA [Dec 5, 2014, to June 23, 2015]), and dose-escalation trials in Africa (Lambaréné, Gabon [November, 2014, to January, 2015], and Kilifi, Kenya [December, 2014, to January, 2015]) using different doses of the recombinant vesicular stomatitis virus vector expressing the Zaire Ebola virus glycoprotein (rVSVΔG-ZEBOV-GP; 3 × 10⁵ to 1 × 10⁸ plaque-forming units [pfu]). Longitudinal transcriptomic responses (days 0, 1, 2, 3, 7, 14, and 28) were measured in whole blood using a targeted gene expression profiling platform (dual-colour reverse-transcriptase multiplex ligation-dependent probe amplification) focusing on 144 immune-related genes. The effect of time and dose on transcriptomic response was also assessed. Logistic regression with lasso regularisation was applied to identify host signatures with optimal discriminatory capability of vaccination at day 1 or day 7 versus baseline, whereas random-effects models and recursive feature elimination combined with regularised logistic regression were used to associate signatures with immunogenicity and reactogenicity.

FINDINGS

Our results indicated that perturbation of gene expression peaked on day 1 and returned to baseline levels between day 7 and day 28. The magnitude of the response was dose-dependent, with vaccinees receiving a high dose (≥9 × 10⁶ pfu) of rVSVΔG-ZEBOV-GP exhibiting the largest amplitude. The most differentially expressed genes that were significantly upregulated following vaccination consisted of type I and II interferon-related genes and myeloid cell-associated markers, whereas T cell, natural killer cell, and cytotoxicity-associated genes were downregulated. A gene signature associated with immunogenicity (common to all four cohorts) was identified correlating gene expression profiles with ZEBOV-GP antibody titres and a gene signatures associated with reactogenicity (Geneva cohort) was identified correlating gene expression profiles with an adverse event (ie, arthritis).

INTERPRETATION

Collectively, our results identify and cross-validate immune-related transcriptomic signatures induced by rVSVΔG-ZEBOV-GP vaccination in four cohorts of adult participants from different genetic and geographical backgrounds. These signatures will aid in the rational development, testing, and evaluation of novel vaccines and will allow evaluation of the effect of host factors such as age, co-infection, and comorbidity on responses to vaccines.

FUNDING

Innovative Medicines Initiative 2 Joint Undertaking.

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.

Expansion of Single Cell Transcriptomics Data of SARS-CoV Infection in Human Bronchial Epithelial Cells to COVID-19

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 19 (COVID-19) that was emerged as a new member of coronaviruses since December 2019 in Wuhan, China and then after was spread in all continentals. Since SARS-CoV-2 has shown about 77.5% similarity to SARS-CoV, the transcriptome and immunological regulations of SARS-CoV-2 was expected to have high percentage of overlap with SARS-CoV.

Results

In this study, we applied the single cell transcriptomics data of human bronchial epithelial cells (2B4 cell line) infected with SARS-CoV, which was annotated in the Expression Atlas database to expand this data to COVID-19. In addition, we employed system biology methods including gene ontology (GO) and Reactome pathway analyses to define functional genes and pathways in the infected cells with SARS-CoV. The transcriptomics analysis on the Expression Atlas database revealed that most genes from infected 2B4 cell line with SARS-CoV were downregulated leading to immune system hyperactivation, induction of signaling pathways, and consequently a cytokine storm. In addition, GO:0016192 (vesicle-mediated transport), GO:0006886 (intracellular protein transport), and GO:0006888 (ER to Golgi vesicle-mediated transport) were shown as top three GOs in the ontology network of infected cells with SARS-CoV. Meanwhile, R-HAS-6807070 (phosphatase and tensin homolog or PTEN regulation) showed the highest association with other Reactome pathways in the network of infected cells with SARS-CoV. PTEN plays a critical role in the activation of dendritic cells, B- and T-cells, and secretion of proinflammatory cytokines, which cooperates with downregulated genes in the promotion of cytokine storm in the COVID-19 patients.

Conclusions

Based on the high similarity percentage of the transcriptome of SARS-CoV with SARS-CoV-2, the data of immunological regulations, signaling pathways, and proinflammatory cytokines in SARS-CoV infection can be expanded to COVID-19 to have a valid platform for future pharmaceutical and vaccine studies.

Transcriptomic profiling of different responder types in adults after a Priorix® vaccination

Thanks to the recommendation of a combined Measles/Mumps/Rubella (MMR) vaccine, like Priorix®, these childhood diseases are less common now. This is beneficial to limit the spread of these diseases and work towards their elimination. However, the measles, mumps and rubella antibody titers show a large variability in short- and long-term immunity. The recent outbreaks worldwide of measles and mumps and previous studies, which mostly focused on only one of the three virus responses, illustrate that there is a clear need for better understanding the immune responses after vaccination. Our healthy cohort was already primed with the MMR antigens in their childhood. In this study, the adult volunteers received one Priorix® vaccine dose at day 0. First, we defined 4 different groups of responders, based on their antibody titers' evolution over 4 time points (Day 0, 21, 150 and 365). This showed a high variability within and between individuals. Second, we determined transcriptome profiles using 3'mRNA sequencing at day 0, 3 and 7. Using two analytical approaches, "one response group per time point" and "a time comparison per response group", we correlated the short-term gene expression profiles to the different response groups. In general, the list of differentially expressed genes is limited, however, most of them are clearly immune-related and upregulated at day 3 and 7, compared to the baseline day 0. Depending on the specific response group there are overlapping signatures for two of the three viruses. Antibody titers and transcriptomics data showed that an additional Priorix vaccination does not facilitate an equal immune response against the 3 viruses or among different vaccine recipients.

Factors That Influence the Immune Response to Vaccination

There is substantial variation between individuals in the immune response to vaccination. In this review, we provide an overview of the plethora of studies that have investigated factors that influence humoral and cellular vaccine responses in humans. These include intrinsic host factors (such as age, sex, genetics, and comorbidities), perinatal factors (such as gestational age, birth weight, feeding method, and maternal factors), and extrinsic factors (such as preexisting immunity, microbiota, infections, and antibiotics). Further, environmental factors (such as geographic location, season, family size, and toxins), behavioral factors (such as smoking, alcohol consumption, exercise, and sleep), and nutritional factors (such as body mass index, micronutrients, and enteropathy) also influence how individuals respond to vaccines. Moreover, vaccine factors (such as vaccine type, product, adjuvant, and dose) and administration factors (schedule, site, route, time of vaccination, and coadministered vaccines and other drugs) are also important. An understanding of all these factors and their impacts in the design of vaccine studies and decisions on vaccination schedules offers ways to improve vaccine immunogenicity and efficacy.

Adjuvant-Associated Peripheral Blood mRNA Profiles and Kinetics Induced by the Adjuvanted Recombinant Protein Candidate Tuberculosis Vaccine M72/AS01 in Bacillus Calmette-Guérin-Vaccinated Adults

Systems biology has the potential to identify gene signatures associated with vaccine immunogenicity and protective efficacy. The main objective of this study was to identify optimal postvaccination time points for evaluating peripheral blood RNA expression profiles in relation to vaccine immunogenicity and potential efficacy in recipients of the candidate tuberculosis vaccine M72/AS01. In this phase II open-label study (NCT01669096; https://clinicaltrials.gov/), healthy Bacillus Calmette–Guérin-primed, HIV-negative adults were administered two doses (30 days apart) of M72/AS01. Twenty subjects completed the study and 18 subjects received two doses. Blood samples were collected pre-dose 1, pre-dose 2, and 1, 7, 10, 14, 17, and 30 days post-dose 2. RNA expression in whole blood (WB) and peripheral blood mononuclear cells (PBMCs) was quantified using microarray technology. Serum interferon-gamma responses and M72-specific CD4⁺ T cell responses to vaccination, and the observed safety profile were similar to previous trials. Two different approaches were utilized to analyze the RNA expression data. First, a kinetic analysis of RNA expression changes using blood transcription modules revealed early (1 day post-dose 2) activation of several pathways related to innate immune activation, both in WB and PBMC. Second, using a previously identified gene signature as a classifier, optimal postvaccination time points were identified. Since M72/AS01 efficacy remains to be established, a PBMC-derived gene signature associated with the protective efficacy of a similarly adjuvanted candidate malaria vaccine was used as a proxy for this purpose. This approach was based on the assumption that the AS01 adjuvant used in both studies could induce shared innate immune pathways. Subjects were classified as gene signature positive (GS⁺) or gene signature negative (GS⁻). Assignments of subjects to GS⁺ or GS⁻ groups were confirmed by significant differences in RNA expression of the gene signature genes in PBMCs at 14 days post-dose 2 relative to prevaccination and in WB samples at 7, 10, 14, and 17 days post-dose 2 relative to prevaccination. Hence, in comparison with a prevaccination, 7, 10, 14, and 17 days postvaccination appeared to be suitable time points for identifying potentially clinically relevant transcriptome responses to M72/AS01 in WB samples.

Genome-wide associations of CD46 and IFI44L genetic variants with neutralizing antibody response to measles vaccine

Population-based studies have revealed 2-10% measles vaccine failure rate even after two vaccine doses. While the mechanisms behind this remain unknown, we hypothesized that host genetic factors are likely to be involved. We performed a genome-wide association study of measles specific neutralizing antibody and IFNγ ELISPOT response in a combined sample of 2872 subjects. We identified two distinct chromosome 1 regions (previously associated with MMR-related febrile seizures), associated with vaccine-induced measles neutralizing antibody titers. The 1q32 region contained 20 significant SNPs in/around the measles virus receptor-encoding CD46 gene, including the intronic rs2724384 (p value = 2.64 × 10^-09) and rs2724374 (p value = 3.16 × 10^-09) SNPs. The 1q31.1 region contained nine significant SNPs in/around IFI44L, including the intronic rs1333973 (p value = 1.41 × 10^-10) and the missense rs273259 (His73Arg, p value = 2.87 × 10^-10) SNPs. Analysis of differential exon usage with mRNA-Seq data and RT-PCR suggests the involvement of rs2724374 minor G allele in the CD46 STP region exon B skipping, resulting in shorter CD46 isoforms. Our study reveals common CD46 and IFI44L SNPs associated with measles-specific humoral immunity, and highlights the importance of alternative splicing/virus cellular receptor isoform usage as a mechanism explaining inter-individual variation in immune response after live measles vaccine.

Comparative Systems Analyses Reveal Molecular Signatures of Clinically tested Vaccine Adjuvants

A better understanding of the mechanisms of action of human adjuvants could inform a rational development of next generation vaccines for human use. Here, we exploited a genome wide transcriptomics analysis combined with a systems biology approach to determine the molecular signatures induced by four clinically tested vaccine adjuvants, namely CAF01, IC31, GLA-SE and Alum in mice. We report signature molecules, pathways, gene modules and networks, which are shared by or otherwise exclusive to these clinical-grade adjuvants in whole blood and draining lymph nodes of mice. Intriguingly, co-expression analysis revealed blood gene modules highly enriched for molecules with documented roles in T follicular helper (TFH) and germinal center (GC) responses. We could show that all adjuvants enhanced, although with different magnitude and kinetics, TFH and GC B cell responses in draining lymph nodes. These results represent, to our knowledge, the first comparative systems analysis of clinically tested vaccine adjuvants that may provide new insights into the mechanisms of action of human adjuvants.

Potential role of killer immunoglobulin receptor genes among individuals vaccinated against hepatitis B virus in Lebanon

AIM

To explore the role of killer immunoglobulin receptor (KIR) genes in responsiveness or non-responsiveness to vaccination against hepatitis B virus.

METHODS

We recruited 101 voluntary participants between March 2010 and December 2011. Sera samples from vaccinated and non-vaccinated participants were tested for the presence of anti-HBs antibodies as a measure of protection against hepatitis B, hepatitis B surface antigen and hepatitis B core antibody as indicators of infection by enzyme-linked immunosorbent assay. KIR gene frequencies were determined by polymerase chain reaction.

RESULTS

Sera samples from 99 participants were tested for the levels of anti-HBs as an indicator of protection (≥ 10 mIU/mL) following vaccination as defined by the World Health Organization international reference standard. Among the vaccinated participants, 47% (35/74) had anti-HBs titers above 100 mIU/mL, 22% (16/74) had anti-HBs ranging between 10-100 mIU/mL, and 20% (15/74) had values of less than 10 mIU/mL. We report the lack of significant association between the number of vaccine dosages and the titer of antibodies among our vaccinated participants. The inhibitory KIR2DL1, KIR2DL4, KIR3DL1, KIR3DL2, and KIR3DL were detected in more than 95%, whereas KIR2DL2, KIR2DL3, KIR2DL5 (KR2DL5A and KIR2DL5B) were expressed in 56%, 84% and 42% (25% and 29%) of participants, respectively. The observed frequency of the activating KIR genes ranged between 35% and 55% except for KIR2DS4, detected in 95% of the study participants (40.6% 2DS4*001/002; 82.2% 2DS4*003/007). KIR2DP1 pseudogene was detected in 99% of our participants, whereas KIR3DP*001/02/04 and KIR3DP1*003 had frequencies of 17% and 100%, respectively. No association between the frequency of KIR genes and anti-HBs antibodies was detected. When we compared the frequency of KIR genes between vaccinated individuals with protective antibodies titers and those who lost their protective antibody levels, we did not detect a significant difference. KIR2DL5B was significantly different among different groups of vaccinated participants (group I > 100 mIU/mL, group II 10-100 mIU/mL, group III < 10 mIU/mL and group IV with undetectable levels of protective antibodies).

CONCLUSION

To our knowledge, this is the first study screening for the possible role of KIR genes among individuals vaccinated against hepatitis B virus (HBV). Our results can be used to design larger studies to better understand the role of KIR genes in protection against or susceptibility to HBV post vaccination.

Gene signatures associated with adaptive humoral immunity following seasonal influenza A/H1N1 vaccination

This study aimed to identify gene expression markers shared between both influenza hemagglutination-inhibition (HAI) and virus-neutralization antibody (VNA) responses. We enrolled 158 older subjects who received the 2010–2011 trivalent inactivated influenza vaccine (TIV). Influenza-specific HAI and VNA titers, and mRNA-sequencing were performed using blood samples obtained at Days 0, 3 and 28 post-vaccination. For antibody response at Day 28 vs Day 0, several genesets were identified as significant in predictive models for HAI (n=7) and VNA (n=35) responses. Five genesets (comprising the genes MAZ, TTF, GSTM, RABGGTA, SMS, CA, IFNG, and DOPEY) were in common for both HAI and VNA. For response at Day 28 vs Day 3, many genesets were identified in predictive models for HAI (n=13) and VNA (n=41). Ten genesets (comprising biologically related genes, such as MAN1B1, POLL, CEBPG, FOXP3, IL12A, TLR3, TLR7, and others) were shared between HAI and VNA. These identified genesets demonstrated a high degree of network interactions and likelihood for functional relationships. Influenza-specific HAI and VNA responses demonstrated a remarkable degree of similarity. Although unique geneset signatures were identified for each humoral outcome, several genesets were determined to be in common with both HAI and VNA response to influenza vaccine.

Whole Transcriptome Profiling Identifies CD93 and Other Plasma Cell Survival Factor Genes Associated with Measles-Specific Antibody Response after Vaccination

Background

There are insufficient system-wide transcriptomic (or other) data that help explain the observed inter-individual variability in antibody titers after measles vaccination in otherwise healthy individuals.

Methods

We performed a transcriptome(mRNA-Seq)-profiling study after in vitro viral stimulation of PBMCs from 30 measles vaccine recipients, selected from a cohort of 764 schoolchildren, based on the highest and lowest antibody titers. We used regression and network biology modeling to define markers associated with neutralizing antibody response.

Results

We identified 39 differentially expressed genes that demonstrate significant differences between the high and low antibody responder groups (p-value≤0.0002, q-value≤0.092), including the top gene CD93 (p<1.0E^-13, q<1.0E^-09), encoding a receptor required for antigen-driven B-cell differentiation, maintenance of immunoglobulin production and preservation of plasma cells in the bone marrow. Network biology modeling highlighted plasma cell survival (CD93, IL6, CXCL12), chemokine/cytokine activity and cell-cell communication/adhesion/migration as biological processes associated with the observed differential response in the two responder groups.

Conclusion

We identified genes and pathways that explain in part, and are associated with, neutralizing antibody titers after measles vaccination. This new knowledge could assist in the identification of biomarkers and predictive signatures of protective immunity that may be useful in the design of new vaccine candidates and in clinical studies.

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

BACKGROUND

Studies suggest that the recall-based humoral immune responses to influenza A/H1N1 originates from activated memory B cells. The aim of this study was to identify baseline, early and late blood transcriptional signatures (in peripheral blood mononuclear cells/PBMCs) associated with memory B cell response following influenza vaccination.

METHODS

We used pre- and post-vaccination mRNA-Seq transcriptional profiling on samples from 159 subjects (50-74years old) following receipt of seasonal trivalent influenza vaccine containing the A/California/7/2009/H1N1-like virus, and penalized regression modeling to identify associations with influenza A/H1N1-specific memory B cell ELISPOT response after vaccination.

RESULTS

Genesets and genes (p-value range 7.92E(-08) to 0.00018, q-value range 0.00019-0.039) demonstrating significant associations (of gene expression levels) with memory B cell response suggest the importance of metabolic (cholesterol and lipid metabolism-related), cell migration/adhesion, MAP kinase, NF-kB cell signaling (chemokine/cytokine signaling) and transcriptional regulation gene signatures in the development of memory B cell response after influenza vaccination.

CONCLUSION

Through an unbiased transcriptome-wide profiling approach, our study identified signatures of memory B cell response following influenza vaccination, highlighting the underappreciated role of metabolic changes (among the other immune function-related events) in the regulation of influenza vaccine-induced immune memory.

Gene signatures related to HAI response following influenza A/H1N1 vaccine in older individuals

To assess gene signatures related to humoral response among healthy older subjects following seasonal influenza vaccination, we studied 94 healthy adults (50–74 years old) who received one documented dose of licensed trivalent influenza vaccine containing the A/California/7/2009 (H1N1)-like virus strain. Influenza-specific antibody (HAI) titer in serum samples and next-generation sequencing on PBMCs were performed using blood samples collected prior to (Day 0) and at two timepoints after (Days 3 and 28) vaccination. We identified a number of uncharacterized genes (ZNF300, NUP1333, KLK1 and others) and confirmed previous studies demonstrating specific genes/genesets that are important mediators of host immune responses and that displayed associations with antibody response to influenza A/H1N1 vaccine. These included interferon-regulatory transcription factors (IRF1/IRF2/IRF6/IRF7/IRF9), chemokine/chemokine receptors (CCR5/CCR9/CCL5), cytokine/cytokine receptors (IFNG/IL10RA/TNFRSF1A), protein kinases (MAP2K4/MAPK3), growth factor receptor (TGFBR1). The identification of gene signatures associated with antibody response represents an early stage in the science for which further research is needed. Such research may assist in the design of better vaccines to facilitate improved defenses against new influenza virus strains, as well as better understanding the genetic drivers of immune responses.

System-Wide Associations between DNA-Methylation, Gene Expression, and Humoral Immune Response to Influenza Vaccination

Failure to achieve a protected state after influenza vaccination is poorly understood but occurs commonly among aged populations experiencing greater immunosenescence. In order to better understand immune response in the elderly, we studied epigenetic and transcriptomic profiles and humoral immune response outcomes in 50-74 year old healthy participants. Associations between DNA methylation and gene expression reveal a system-wide regulation of immune-relevant functions, likely playing a role in regulating a participant's propensity to respond to vaccination. Our findings show that sites of methylation regulation associated with humoral response to vaccination impact known cellular differentiation signaling and antigen presentation pathways. We performed our analysis using per-site and regionally average methylation levels, in addition to continuous or dichotomized outcome measures. The genes and molecular functions implicated by each analysis were compared, highlighting different aspects of the biologic mechanisms of immune response affected by differential methylation. Both cis-acting (within the gene or promoter) and trans-acting (enhancers and transcription factor binding sites) sites show significant associations with measures of humoral immunity. Specifically, we identified a group of CpGs that, when coordinately hypo-methylated, are associated with lower humoral immune response, and methylated with higher response. Additionally, CpGs that individually predict humoral immune responses are enriched for polycomb-group and FOXP2 transcription factor binding sites. The most robust associations implicate differential methylation affecting gene expression levels of genes with known roles in immunity (e.g. HLA-B and HLA-DQB2) and immunosenescence. We believe our data and analysis strategy highlight new and interesting epigenetic trends affecting humoral response to vaccination against influenza; one of the most common and impactful viral pathogens.

Single nucleotide polymorphisms/haplotypes associated with multiple rubella-specific immune response outcomes post-MMR immunization in healthy children

The observed heterogeneity in rubella-specific immune response phenotypes post-MMR vaccination is thought to be explained, in part, by inter-individual genetic variation. In this study, single nucleotide polymorphisms (SNPs) and multiple haplotypes in several candidate genes were analyzed for associations with more than one rubella-specific immune response outcome, including secreted IFN-γ, secreted IL-6, and neutralizing antibody titers. Overall, we identified 23 SNPs in 10 different genes that were significantly associated with at least two rubella-specific immune responses. Of these SNPs, we detected eight in the PVRL3 gene, five in the PVRL1 gene, one in the TRIM22 gene, two in the IL10RB gene, two in the TLR4 gene, and five in other genes (PVR, ADAR, ZFP57, MX1, and BTN2A1/BTN3A3). The PVRL3 gene haplotype GACGGGGGCAGCAAAAAGAAGAGGAAAGAACAA was significantly associated with both higher IFN-γ secretion (t-statistic 4.43, p < 0.0001) and higher neutralizing antibody titers (t-statistic 3.14, p = 0.002). Our results suggest that there is evidence of multigenic associations among identified gene SNPs and that polymorphisms in these candidate genes contribute to the overall observed differences between individuals in response to live rubella virus vaccine. These results will aid our understanding of mechanisms behind rubella-specific immune response to MMR vaccine and influence the development of vaccines in the future.

Rubella

Rubella remains an important pathogen worldwide, with roughly 100,000 cases of congenital rubella syndrome estimated to occur every year. Rubella-containing vaccine is highly effective and safe and, as a result, endemic rubella transmission has been interrupted in the Americas since 2009. Incomplete rubella vaccination programmes result in continued disease transmission, as evidenced by recent large outbreaks in Japan and elsewhere. In this Seminar, we provide present results regarding rubella control, elimination, and eradication policies, and a brief review of new laboratory diagnostics. Additionally, we provide novel information about rubella-containing vaccine immunogenetics and review the emerging evidence of interindividual variability in humoral and cell-mediated innate and adaptive immune responses to rubella-containing vaccine and their association with haplotypes and single-nucleotide polymorphisms across the human genome.

Polymorphisms in HLA-DPB1 are associated with differences in rubella virus-specific humoral immunity after vaccination

Vaccination with live attenuated rubella virus induces a strong immune response in most individuals. However, small numbers of subjects never reach or maintain protective antibody levels, and there is a high degree of variability in immune response. We have previously described genetic polymorphisms in HLA and other candidate genes that are associated with interindividual differences in humoral immunity to rubella virus. To expand our previous work, we performed a genome-wide association study (GWAS) to discover single-nucleotide polymorphisms (SNPs) associated with rubella virus-specific neutralizing antibodies. We identified rs2064479 in the HLA-DPB1 genetic region as being significantly associated with humoral immune response variations after rubella vaccination (P = 8.62 × 10(-8)). All other significant SNPs in this GWAS were located near the HLA-DPB1 gene (P ≤ 1 × 10(-7)). These findings demonstrate that polymorphisms in HLA-DPB1 are strongly associated with interindividual differences in neutralizing antibody levels to rubella vaccination and represent a validation of our previous HLA work.

Changing face of vaccination in immunocompromised hosts

Infection prevention is a key component of care and an important determinant of clinical outcomes in a diverse population of immunocompromised hosts. Vaccination remains a fundamental preventative strategy, and clear guidelines exist for the vaccination of immunocompromised individuals and close contacts. Unfortunately, adherence to such guidelines is frequently suboptimal, with consequent missed opportunities to prevent infection. Additionally, vaccination of immunocompromised individuals is known to produce responses inferior to those observed in immunocompetent hosts. Multiple factors contribute to this finding, and developing improved vaccination strategies for those at high risk of infectious complications remains a priority of care providers. Herein, we review potential factors contributing to vaccine outcomes, focusing on host immune responses, and propose a means for applying modern, innovative systems biology technology to model critical determinants of vaccination success. With influenza vaccine in solid organ transplants used as a case in point, novel means for stratifying individuals using a host "immunophenotype" are explored, and strategies for individualizing vaccine approaches tailored to safely optimize vaccine responses in those most at risk are discussed.

Associations between single nucleotide polymorphisms in cellular viral receptors and attachment factor-related genes and humoral immunity to rubella vaccination

Background

Viral attachment and cell entry host factors are important for viral replication, pathogenesis, and the generation and sustenance of immune responses after infection and/or vaccination, and are plausible genetic regulators of vaccine-induced immunity.

Methods

Using a tag-SNP approach in candidate gene study, we assessed the role of selected cell surface receptor genes, attachment factor-related genes, along with other immune genes in the genetic control of immune response variations after live rubella vaccination in two independent study cohorts.

Results

Our analysis revealed evidence for multiple associations between genetic variants in the PVR, PVRL2, CD209/DC-SIGN, RARB, MOG, IL6 and other immune function-related genes and rubella-specific neutralizing antibodies after vaccination (meta p-value <0.05).

Conclusion

Our results indicate that multiple SNPs from genes involved in cell adhesion, viral attachment, and viral entry, as well as others in genes involved in signaling and/or immune response regulation, play a role in modulating humoral immune responses following live rubella vaccination.

Kinomic exploration of temozolomide and radiation resistance in Glioblastoma multiforme xenolines

BACKGROUND AND PURPOSE

Glioblastoma multiforme (GBM) represents the most common and deadly primary brain malignancy, particularly due to temozolomide (TMZ) and radiation (RT) resistance. To better understand resistance mechanisms, we examined global kinase activity (kinomic profiling) in both treatment sensitive and resistant human GBM patient-derived xenografts (PDX or "xenolines").

MATERIALS AND METHODS

Thirteen orthotopically-implanted xenolines were examined including 8 with known RT sensitivity/resistance, while 5 TMZ resistant xenolines were generated through serial TMZ treatment in vivo. Tumors were harvested, prepared as total protein lysates, and kinomically analyzed on a PamStation®12 high-throughput microarray platform with subsequent upstream kinase prediction and network modeling.

RESULTS

Kinomic profiles indicated elevated tyrosine kinase activity associated with the radiation resistance phenotype, including FAK and FGFR1. Furthermore, network modeling showed VEGFR1/2 and c-Raf hubs could be involved. Analysis of acquired TMZ resistance revealed more kinomic variability among TMZ resistant tumors. Two of the five tumors displayed significantly altered kinase activity in the TMZ resistant xenolines and network modeling indicated PKC, JAK1, PI3K, CDK2, and VEGFR as potential mediators of this resistance.

CONCLUSION

GBM xenolines provide a phenotypic model for GBM drug response and resistance that when paired with kinomic profiling identified targetable pathways to inherent (radiation) or acquired (TMZ) resistance.

Characterization of humoral and cellular immunity to rubella vaccine in four distinct cohorts

Although vaccination campaigns have significantly reduced the global burden of rubella disease, there are still regional outbreaks and cases of congenital rubella syndrome. Rubella vaccination elicits a strong humoral as well as cellular response. The relationship between these two measures in response to rubella vaccine is poorly understood. We have previously reported no correlation between rubella-virus-specific cytokine secretion and IgG antibody levels after rubella vaccination. In the current study, we extend our previous work to report correlations between secreted cytokines and functional neutralizing antibodies after rubella vaccination in four distinct cohorts. There was evidence of significant differences (p < 0.05) in rubella-virus-specific humoral and cellular responses between cohorts. When investigating relationships between rubella-vaccine-specific humoral and cellular immunity, we observed a significant correlation between neutralizing antibodies and IFN-γ (r(s) = 0.21, p = 0.0004). We also observed correlations in subjects with extreme humoral immune phenotypes and IFN-γ levels in two of the four cohorts (r(s) = 0.32, p = 0.01; r(s) = 0.36, p = 0.01, respectively). These findings indicate that there is a high level of heterogeneity in rubella-specific immune responses between study populations. We believe that the novel correlation discovered between IFN-γ and neutralizing antibody titers will give future insight into the functional mechanisms of immunity induced by rubella virus and other live viral vaccines.

ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php.

Variability in the immune system: of vaccine responses and immune states

System-wide approaches are now being applied to study vaccine responses, whose mechanisms of action, and failure, are not well understood. These works have repeatedly shown vaccine response to be an orchestrated process involving multiple arms of immunity most noticeable sensing and innate components. Prediction of vaccine responses based on system-wide measures is achievable, but challenges remain for robust population wide predictions based only on pre-vaccination measures, especially in partially efficacious vaccines such as influenza. This is especially true in older adults, who are often less responsive to vaccination and exhibit high level of variation compared to young in many components of immunity. Despite this increase in variation, most of the studies on aging use group averages of immune phenotypes to model immune system behavior. Using systems approaches, it is possible to exploit this variation to form distinguishable clusters of phenotypes within and across individuals to discover underlying immune states.