Gene expression profiling reveals insights into infant immunological and febrile responses to group B meningococcal vaccine

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.

Baseline gene signatures of reactogenicity to Ebola vaccination: a machine learning approach across multiple cohorts

Introduction

The rVSVDG-ZEBOV-GP (Ervebo®) vaccine is both immunogenic and protective against Ebola. However, the vaccine can cause a broad range of transient adverse reactions, from headache to arthritis. Identifying baseline reactogenicity signatures can advance personalized vaccinology and increase our understanding of the molecular factors associated with such adverse events.

Methods

In this study, we developed a machine learning approach to integrate prevaccination gene expression data with adverse events that occurred within 14 days post-vaccination.

Results and Discussion

We analyzed the expression of 144 genes across 343 blood samples collected from participants of 4 phase I clinical trial cohorts: Switzerland, USA, Gabon, and Kenya. Our machine learning approach revealed 22 key genes associated with adverse events such as local reactions, fatigue, headache, myalgia, fever, chills, arthralgia, nausea, and arthritis, providing insights into potential biological mechanisms linked to vaccine reactogenicity.

Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature

BACKGROUND

Appropriate treatment and management of children presenting with fever depend on accurate and timely diagnosis, but current diagnostic tests lack sensitivity and specificity and are frequently too slow to inform initial treatment. As an alternative to pathogen detection, host gene expression signatures in blood have shown promise in discriminating several infectious and inflammatory diseases in a dichotomous manner. However, differential diagnosis requires simultaneous consideration of multiple diseases. Here, we show that diverse infectious and inflammatory diseases can be discriminated by the expression levels of a single panel of genes in blood.

METHODS

A multi-class supervised machine-learning approach, incorporating clinical consequence of misdiagnosis as a "cost" weighting, was applied to a whole-blood transcriptomic microarray dataset, incorporating 12 publicly available datasets, including 1,212 children with 18 infectious or inflammatory diseases. The transcriptional panel identified was further validated in a new RNA sequencing dataset comprising 411 febrile children.

FINDINGS

We identified 161 transcripts that classified patients into 18 disease categories, reflecting individual causative pathogen and specific disease, as well as reliable prediction of broad classes comprising bacterial infection, viral infection, malaria, tuberculosis, or inflammatory disease. The transcriptional panel was validated in an independent cohort and benchmarked against existing dichotomous RNA signatures.

CONCLUSIONS

Our data suggest that classification of febrile illness can be achieved with a single blood sample and opens the way for a new approach for clinical diagnosis.

FUNDING

European Union's Seventh Framework no. 279185; Horizon2020 no. 668303 PERFORM; Wellcome Trust (206508/Z/17/Z); Medical Research Foundation (MRF-160-0008-ELP-KAFO-C0801); NIHR Imperial BRC.

Molecular correlates of vaccine-induced protection against typhoid fever

BACKGROUNDTyphoid fever is caused by the Gram-negative bacterium Salmonella enterica serovar Typhi and poses a substantial public health burden worldwide. Vaccines have been developed based on the surface Vi-capsular polysaccharide of S. Typhi; these include a plain-polysaccharide-based vaccine, ViPS, and a glycoconjugate vaccine, ViTT. To understand immune responses to these vaccines and their vaccine-induced immunological protection, molecular signatures were analyzed using bioinformatic approaches.METHODSBulk RNA-Seq data were generated from blood samples obtained from adult human volunteers enrolled in a vaccine trial, who were then challenged with S. Typhi in a controlled human infection model (CHIM). These data were used to conduct differential gene expression analyses, gene set and modular analyses, B cell repertoire analyses, and time-course analyses at various post-vaccination and post-challenge time points between participants receiving ViTT, ViPS, or a control meningococcal vaccine.RESULTSTranscriptomic responses revealed strong differential molecular signatures between the 2 typhoid vaccines, mostly driven by the upregulation in humoral immune signatures, including selective usage of immunoglobulin heavy chain variable region (IGHV) genes and more polarized clonal expansions. We describe several molecular correlates of protection against S. Typhi infection, including clusters of B cell receptor (BCR) clonotypes associated with protection, with known binders of Vi-polysaccharide among these.CONCLUSIONThe study reports a series of contemporary analyses that reveal the transcriptomic signatures after vaccination and infectious challenge, while identifying molecular correlates of protection that may inform future vaccine design and assessment.TRIAL REGISTRATIONClinicalTrials.gov NCT02324751.

The omics strategy: the use of systems vaccinology to characterise immune responses to childhood immunisation

INTRODUCTION

Vaccines have had a transformative impact on child health. Despite this impact the immunological processes involved in protective responses are not entirely understood and vaccine development has been largely empirical. Recent technological advances offer the opportunity to reveal the immunology underlying vaccine response at an unprecedented resolution. These data could revolutionise the way vaccines are developed and tested and further augment their role in securing the health of children around the world.

AREAS COVERED

Systems level information and the tools are now being deployed by vaccinologists at all stages of the vaccine development pathway; however, this review will specifically describe some of the key findings that have be gleaned from multi-omics datasets collected in the context of childhood immunisation.

EXPERT OPINION

Despite the success of vaccines there remains hard-to-target pathogens, refractory to current vaccination strategies. Moreover, zoonotic diseases with pandemic potential are a threat to global health, as recently illustrated by COVID-19. Systems vaccinology holds a great deal of promise in revealing a greater understanding of vaccine responses and consequently modernising vaccinology. However, there is a need for future studies -particularly in vulnerable populations that are targets for vaccination programmes - if this potential is to be fulfilled.

Distinct patterns of whole blood transcriptional responses are induced in mice following immunisation with adenoviral and poxviral vector vaccines encoding the same antigen

BACKGROUND

Viral vectors, including adenovirus (Ad) and modified vaccinia Ankara (MVA), have gained increasing attention as vaccine platforms in recent years due to their capacity to express antigens from a wide array of pathogens, their rapid induction of humoral and cellular protective immune responses, and their relatively low production costs. In particular, the chimpanzee Ad vector, ChAdOx1, has taken centre stage as a leading COVID-19 vaccine candidate. However, despite mounting data, both clinical and pre-clinical, demonstrating effective induction of adaptive immune responses, the innate immune signals that precede the protective responses that make these vectors attractive vaccine platforms remain poorly understood.

RESULTS

In this study, a mouse immunisation model was used to evaluate whole blood gene expression changes 24 h after either a single dose or heterologous prime-boost regimen of an Ad and/or MVA vaccine. We demonstrate through comparative analysis of Ad vectors encoding different antigens that a transgene product-specific gene signature can be discerned from the vector-induced transcriptional response. Expression of genes involved in TLR2 stimulation and γδ T cell and natural killer cell activation were induced after a single dose of Ad, while MVA led to greater expression of type I interferon genes. The order of prime-boost combinations was found to influence the magnitude of the gene expression changes, with MVA/Ad eliciting greater transcriptional perturbation than Ad/MVA. Contrasting the two regimens revealed significant enrichment of epigenetic regulation pathways and augmented expression of MHC class I and II molecules associated with MVA/Ad.

CONCLUSION

These data demonstrate that the order in which vaccines from heterologous prime-boost regimens are administered leads to distinct transcriptional responses and may shape the immune response induced by such combinations. The characterisation of early vaccine-induce responses strengthens our understanding of viral vector vaccine mechanisms of action ahead of their characterisation in human clinical trials and are a valuable resource to inform the pre-clinical design of appropriate vaccine constructs for emerging infectious diseases.

Transcriptional and Immunologic Correlates of Response to Pandemic Influenza Vaccine in Aviremic, HIV-Infected Children

People living with HIV (PWH) often exhibit poor responses to influenza vaccination despite effective combination anti-retroviral (ART) mediated viral suppression. There exists a paucity of data in identifying immune correlates of influenza vaccine response in context of HIV infection that would be useful in improving its efficacy in PWH, especially in younger individuals. Transcriptomic data were obtained by microarray from whole blood isolated from aviremic pediatric and adolescent HIV-infected individuals (4-25 yrs) given two doses of Novartis/H1N1 09 vaccine during the pandemic H1N1 influenza outbreak. Supervised clustering and gene set enrichment identified contrasts between individuals exhibiting high and low antibody responses to vaccination. High responders exhibited hemagglutination inhibition antibody titers >1:40 post-first dose and 4-fold increase over baseline. Baseline molecular profiles indicated increased gene expression in metabolic stress pathways in low responders compared to high responders. Inflammation-related and interferon-inducible gene expression pathways were higher in low responders 3 wks post-vaccination. The broad age range and developmental stage of participants in this study prompted additional analysis by age group (e.g. <13yrs and ≥13yrs). This analysis revealed differential enrichment of gene pathways before and after vaccination in the two age groups. Notably, CXCR5, a homing marker expressed on T follicular helper (Tfh) cells, was enriched in high responders (>13yrs) following vaccination which was accompanied by peripheral Tfh expansion. Our results comprise a valuable resource of immune correlates of vaccine response to pandemic influenza in HIV infected children that may be used to identify favorable targets for improved vaccine design in different age groups.