Benson Ogunjimi associate research professor - senior researcher

Research Benson Ogunjimi

Research team

Expertise

My team has experience in - paediatric rheumatology - mathematical modeling in immunology - systems immunology - bulk TCR & RNA sequencing - single cell GEX and TCR sequencing - FFPE TCR sequencing - VZV exogenous boosting

Creation, development and validation of an experimental protocol to obtain paired T-cell receptor alpha and beta data from FFPE tissue at a single cell level. 01/01/2024 - 31/12/2024

Abstract

T-cells are not only crucial actors in our defense against microbes but play an important role in protecting us from cancer. T-cells recognize their targets via its T-cell Receptor (TCR), which consists of a TCRa and TCRb chain. It has been shown that the cancer tissue TCR repertoire holds capacity in predicting which cancer patients will respond to checkpoint-inhibitor therapy, thereby supporting the concept that the tissue-specific TCR repertoire may be considered a stratification biomarker. Decoding the paired TCRab repertoire from the routinely obtained FFPE tissue, necessitates the development of a new single cell workflow method that will allow FFPE tissue paired TCRab sequencing. This would potentially represent a revolution, not only in oncology, but in autoimmunity diseases too where rogue Tcells could be found in affected tissues. In this project, we will create, develop and validate an experimental protocol to obtain paired TCRab data from FFPE tissue.

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  • Research Project

Modeling how pre-existing TCR clones affect vaccine-induced T-cell responses (CELLULO-EPI-BASE). 01/12/2023 - 31/05/2025

Abstract

T-cells are increasingly recognized to be pivotal actors in the development of vaccine-induced immune responses. Through their T-cell receptor (TCR) on their cell surface, T-cells can recognize antigens derived from pathogens or vaccines. The strength of the interaction between the TCRs and the vaccine antigens will direct the T-cell dynamics after vaccination. In this project, we will analyse the TCR repertoires from participants from three distinct vaccination cohorts prior to vaccination and after vaccination. We will develop a computational tool (later to be transformed into a software package) that will allow us to accurately predict, by using the baseline TCR data alone, which vaccinees will develop a robust immune response after vaccination. This tool holds the potential to have an important impact on different aspects and actors of vaccinology ranging from the vaccine industry to public health researchers.

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  • Research Project

RAPTOR: a novel multi-view integrative framework to identify key features of T cell based immunology. 01/11/2023 - 31/10/2025

Abstract

Disentangling the complex reticular components of the immune system represents an obstacle to a deep understanding of the interactions underpinning immune responses. The solution to this challenge likely lies in a systemic design that can illuminate emerging unique and shared biomarkers. However, thus far, the potential of fully integrated immunological data has remained largely untapped. By leveraging an unprecedentedly large cohort for the field, we aim to bridge the gap and build a framework for multi-view biological data fusion with a focus on the often overlooked T cell layer. The views of each cohort will be combined into a latent space. We will group individuals based on emerging new patterns, validate previously published biomarkers, deconvolute group parameters and perform response phenotyping. We will then overlay the T-cell receptor level on this space in an innovative integration to focus on the cellular mediated response. Informed by the discovered features, the T cell analysis will then be driven by epitope and disease specificity and compounded by a longitudinal aspect, to guide the development of the framework's modules. We foresee that this novel framework has great potential for transversal applicability within bioinformatics, biomedical and pharmaceutical companies. Specifically, we anticipate this framework could spark a paradigm shift towards more informed holistic therapeutics designs.

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  • Research Project

Immunoinformatics to discover novel diagnostics in Lyme arthritis: can T cells unlock the status quo? 01/11/2023 - 31/10/2025

Abstract

Current serology-based testing methods to support Lyme disease (LD) diagnosis are critically flawed: they lack sensitivity (25–50%) and specificity for early LD diagnosis, and are unable to differentiate active from past infections in the burdensome late LD stages such as Lyme arthritis (LA). However, in contrast to Borrelia-specific antibodies, T cells are consistently recruited in early LD. Furthermore, different T cell subsets are thought to play a key role in developing autoimmune-driven LA in some patients, although underlying mechanisms remain enigmatic. With this FWO-SB project, we will investigate the potential of T cells as a new avenue for diagnosis. Building upon the recent advances in single-cell immune profiling, this project will deliver a novel, integrative approach for characterizing disease-associated T-cell signatures in unprecedented detail, combining T cell phenotype with its receptor specificity information on a single-cell level. We will construct this detailed immune map in patients with acute and autoimmune-driven Lyme, and contextualize it through comparative analysis with various forms of chronic autoimmune arthritis. This novel methodology will allow us to convert complex immune sequencing data into clinically actionable insights and extremely specific biomarkers. This empowers us to address the imperative diagnostic needs in Lyme, and might shed light on the elusive pathogenesis of acute and chronic LA disease states.

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  • Research Project

Mathematical and Experimental Immunology. 01/10/2023 - 30/09/2028

Abstract

T-cells are white blood cells that are elicited after exposure to pathogens, either after natural infection or vaccination. Different phenotypes of T-cells exist and these are assumed to behave functionally differently. T-cells recognize specific epitopes from pathogens via so-called T-cell Receptors (TCR) that reside on the T-cell membrane. It remains currently not known how T-cells differentiate on a TCR level. During this 5-year research plan, we will develop highly innovative mathematical and computational models to simulate how unique T-cells, represented by their TCRs, against pathogens evolve as a function of different relevant variables and perturbations. We will first further develop the new ERC cellulo-epidemiology paradigm by combining unique cellular immune responses against pathogens on a population level with mathematical modeling, thereby generating unique and otherwise not obtainable multidimensional T-cell profiles. This population level mathematical model will be an agent-based model, but the T-cell dynamics after perturbation (natural infection or vaccination) will be modeled via different modeling strategies including ordinary differential equation (ODE) based modeling. Our agent-based population model will be parameterized and fitted by in-house cross-sectional T-cell data against a wide set of pathogens from over 400 individuals (sampled again after 1 year). Primary and secondary T-cell response shape modeling will be based on unique in-house data from individuals with known first infections with Chikungunya (natural infection) or Yellow fever (vaccination) and longitudinal data from individuals re-exposed to chickenpox (natural infection), hepatitis b surface antigen (vaccination), measles (vaccination) and poliovirus (vaccination). T-cell phenotyping will be achieved via multiparametric flow cytometry and advanced single cell sequencing technology. The overarching unique and innovative goal of my future research plan is to develop a holistic in silico T-cell dynamics model to quantify how T-cell differentiation and dynamics occur after perturbation (thus either post natural exposure or post-vaccination). This will be accomplished through combining unique (longitudinal) T-cell (receptor) responses against different pathogens after infection and/or vaccination with the use of computational and mathematical modeling to unify the multidimensional cellular profiles across age and time.

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  • Research Project

Towards the use of in vitro and in silico T-cell response prediction to guide the development of vaccines, using mRNA-based rabies vaccine as a proof-of-concept. 01/01/2023 - 31/12/2024

Abstract

The traditional process of designing and developing vaccines has been challenged dramatically by the COVID-19 pandemic, with the adoption of mRNA-based vaccines and a reduction of lengthy development pipelines from 10-15 years to 1-1.5 years. This creates a push for further innovation in vaccine development, in particular for diseases with a high unmet need. As an example, mortality due to rabies (a lyssavirus) remains unacceptably high. Although safe, effective vaccines are available for human and animal use, human vaccines are too expensive and generally inaccessible for widespread use in regions where the risk of bites from rabid animals is highest. mRNA approaches offer an opportunity to provide affordable vaccines with the possibility of manufacturing in low and middle income countries, with optimised design affording broader protection. The aim of such an approach would be to drive down cost and broaden supply and equity of access. Novel in silico approaches such as those analysing the T cell receptor response may permit insights into the immune response elicited by rabies vaccines, aid understanding of the mode of action and guide future use. The objective of the current project is to investigate if detailed analysis of the T-cell receptor response can be valuable to inform vaccine design and improve the vaccine development process, using a rabies mRNA vaccine as a proof-of-concept. We will combine in vitro (UAntwerp) and in silico (ImmuneWatch) techniques to gain insights into the T cell response against a range of experimental rabies mRNA vaccine constructs (Quantoom). The project is a public-private partnership aiming to explore novel approaches in vaccine development and to prepare future collaborations between the project partners.

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  • Research Project

Immunological control of Varicella zoster virus (VZV)-infected iPSC-derived brain models by steady-state and immune-compromised astrocytes and microglia. 01/01/2021 - 31/12/2024

Abstract

Varicella zoster virus (VZV) is a member of the herpesvirus family and is a highly successful and ubiquitous human pathogen. Both in children and in adults, varicella-related complications may lead to hospitalisation. While in children direct neurological complications may occur following primary infection (varicella), in adults vasculitis and neurological complications are not uncommon following reactivation of latent VZV (herpes zoster). With a clear link between VZV and neuropathology, it is inevitable that the immune system of the central nervous system (CNS) will be challenged by VZV. However, to date little is known about how astrocytes and microglia behave upon encounter of VZV in the CNS. In this project, we will address this question using an established human in vitro model of axonal infection of human induced pluripotent stem cell (hiPSC)-derived CNS neurons with fluorescent reporter VZV stains. Using this model, we will first longitudinal monitor how hiPSC-derived astrocytes and microglia influence the processes of VZV infection, latency and reactivation. Next, using iPSC models derived from VZV patients with mutations in POLRIII, we will investigate whether immune compromised astrocytes and/or microglia can control neuronal VZV infection. Altogether, these studies will help us understanding innate immune control of VZV in the CNS, and will allow - beyond the scope of this project – to develop novel strategies to prevent VZV spreading in the CNS.

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  • Research Project

Celluloepidemiology: a novel paradigm for modeling T-cell responses on a population level (CELLULO-EPI). 01/03/2020 - 31/08/2025

Abstract

Celluloepidemiology is a term invented to describe an interdisciplinary approach combining unique cellular immune responses against pathogens on a population level with mathematical modeling, thereby generating unique and otherwise not obtainable multidimensional T-cell profiles. CELLULO-EPI will develop and use such a highly innovative model to simulate how T-cells against pathogens evolve in a synthetic population as a function of age, gender, time since infection and other relevant variables. This model will be parameterized and fitted by cross sectional T-cell data against a wide set of pathogens from 500 individuals (sampled again after 1 year), unique data from individuals with known first infections with dengue and measles and longitudinal data from individuals re-exposed to chickenpox and parvovirus B19. The insights of CELLULO-EPI will be pivotal for public health. One important example: Varicella-zoster virus (VZV) causes chickenpox but also shingles after VZV reactivation. Vaccination can prevent chickenpox, but the predicted increase in shingles incidence has blocked chickenpox vaccination in many EU-countries. Indeed, re-exposure to chickenpox is hypothesized to protect against shingles through boosting of T-cells. Unfortunately, none of the available epidemiological or immunological tools allow for adequate validation of the boosting hypothesis. However, CELLULO-EPI will be able to solve this persisting VZV vaccination dilemma. Furthermore, CELLULO-EPI will also redefine infectious disease epidemiology, for example by allowing us to back-calculate the time since last exposure.

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  • Research Project

Identification of the T cell receptor (TCR) repertoire associated with sustained joint pains in chronic chikungunya virus disease. 01/01/2023 - 30/09/2023

Abstract

Chikungunya virus (CHIKV) is a reemerging human pathogen that has seen a rapid global spread in the past decade. It is the most wide-spread member of a group of mosquito transmitted, arthritogenic viruses that can leave up to half of the patients with chronic joint pains long after the initial infection. The chronic joint pain is caused by sustained inflammation and bears hallmarks of auto-immune rheumatoid arthritis. However, the antigenic driver of the prolonged joint inflammation, and the relative contribution of auto-reactive immune cells have not been elucidated. Using next-gen T-cell Receptor (TCR) sequencing on peripheral blood CD4 T cells from CHIKV patients that do or do not develop sustained joint pains we will identify the TCR signatures specifically associated with development of chronic disease. These preliminary findings will extend the role of T cells in the etiology of chronic CHIKV to humans, provide a basis for the search for the antigenic drivers of the disease and potentially identify biomarkers for progression to chronic CHIKV.

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  • Research Project

Immunoinformatics approach to discover novel diagnostics in Lyme Arthritis: can T cells unlock the status quo? 01/11/2022 - 31/10/2023

Abstract

Current serology-based testing methods to support Lyme disease (LD) diagnosis are critically flawed: they lack sensitivity (25–50%) and specificity for diagnosis in early LD, and are unable to differentiate active from past infections in the burdensome late LD stages such as Lyme arthritis (LA). In contrast to Borrelia-specific antibodies, T cells have been shown to be consistently recruited in early LD. Furthermore, different T cell subsets are thought to play a key role in the development of later postinfectious (autoimmune-driven) LA. With this FWO-SB project, we will investigate the potential of T cells as a new avenue for diagnosis. Building upon the recent advances in single-cell immune profiling, this project will deliver a novel framework for characterizing disease-associated T-cell signatures in unprecedented detail, integrating the T cell phenotype with its receptor specificity on a single-cell level. We will address the critical need for post-analysis tools for such complex datasets by developing novel immunoinformatic workflows, allowing efficient extraction of clinically actionable insights and extremely specific biomarkers. Employing the developed methodology and tools across various types of LD, LA, and other relevant autoimmune-driven arthritides will then empower us in addressing the imperative diagnostic need and in shedding light on the elusive pathogenic mechanisms behind postinfectious LA.

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Predicting and modeling vaccination-induced immune responses through the development of advanced computational models for immunosequencing data. 04/07/2022 - 31/12/2022

Abstract

High throughput sequencing allows the characterization of the human immune system, but the resulting data cannot simply be translated into clinical insights. We have therefore developed artificial intelligence models that can translate T-cell receptor (TCR) and gene expression data into useful insights about an individual's immune status. For example, we have developed the first online platform to predict the epitopes of TCRs. We have demonstrated its value for predicting and modeling vaccination-induced immune responses.

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Infrastructure for Diverse Applications of Single Cell Sorting and Dispensing using Microfluidics. 01/06/2022 - 31/05/2024

Abstract

This application relates to the purchase of new basic research infrastucture, a device for versatile Single Cell Sorting and Dispensing using Microfluidics. The equipment can be used for a variety of applications, including cell line development, monoclonal antibody development, iPSC cloning, single cell omics, rare cell isolation, microbiology, virology, immunology and microbial technology. The equipment works at low pressure and allows easy setup and easy switching between a variety of applications, both with or without infectious agents.

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Development and validation of a bona fide iPSC derived human neuronal infection model to evaluate antivirals targeted against neurotropic viral infections. 01/05/2022 - 30/04/2023

Abstract

Neurotropic viral infections continue to cause major disease and economic burden. Such infections are most commonly caused by herpesviruses, arboviruses and enteroviruses, often leading to severe neurological damage with poor clinical outcomes. The search for interventions to prevent and/or treat these infections is however challenging. The main reason for this is the nature of the target cells, neurons, which are chiefly non-renewable and drastically differ from other cells (or cell lines). Discovery of novel antivirals via the classically performed research with cell lines, is not appropriate for viruses that infect neurons. Highly specialized, bona fide, human neuronal culture models are imperative. With this project, we will develop specialized neuronal cultures aimed at higher throughput antiviral screening.

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Celluloepidemiology: generating and modeling SARS-COV-2 specific T-cell responses on a population level for more accurate interventions in public health. 01/11/2020 - 31/10/2021

Abstract

Mathematical simulation models have become indispensable tools for forecasting and studying the effectiveness of intervention strategies such as lockdowns and screening during the SARS-CoV-2 pandemic. Estimation of key modeling quantities uses the serological footprint of an infection on the host. However, although depending on the type of assay, SARS-CoV-2 antibody titers were frequently not found in young and/or asymptomatic individuals and were shown to wane after a relatively short period, especially in asymptomatic individuals. In contrast, T-cells have been found in different situations – also without antibodies being present - ranging from convalescent asymptomatic to mild SARS-CoV-2 patients and their household members, thereby indicating that T-cells offer more sensitivity to detect past exposure to SARS-CoV-2 than the detection of antibodies can. In this project, we will gather on a population level T-cell and antibody SARS-CoV-2 specific data from different well-described cohorts including 300 individuals (and 200 household members) who have had proven covid-19 infection > 3 months earlier, 100 general practitioners, 100 hospital workers, 500 randomly selected individuals and 75 pre-covid-era PBMC/sera. This data will be used in comparative simulation models and will lead to a reassessment of several key epidemiological estimates such as herd immunity and the reproduction number R that will significantly inform covid-19 related public health interventions.

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Diagnosis through Sorted Immune Repertoires (DiagnoSIR). 20/10/2020 - 19/07/2021

Abstract

Infectious disease laboratory diagnostic testing is still based on targeted test methods (Ag detection, PCR, ELISA, agglutination, ELISPOT, etc.). However, rapid evolutions in sequencing applications might soon dramatically change our diagnostic algorithms. For instance, metagenomic sequencing is an untargeted diagnostic tool for direct (in theory any) infectious pathogen detection without preassumptions on the causative agent. However, acute infectious pathogens rapidly disappear from the infected individual (causing diagnostic methods based on direct pathogen detection to fail) leaving behind its immune imprint (primed B and T cells). We here wish to demonstrate that immune repertoire sequencing (a cutting-edge sequencing tool that allows high-throughput mapping of B and T cell receptor variable domains) focused on recently activated immune cells is an indirect untargeted diagnostic tool for acute infectious pathogen detection. This method could therefore be an alternative to current indirect targeted assays (serology and T cell assays). To prove this concept, we will exploit recently collected acute COVID-19 patient samples.

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T Cell Receptor sequence mining platform MinTR. 01/04/2019 - 31/03/2020

Abstract

The T-cell repertoire is a key player in the adaptive immune system and is thus important in infectious disease defense, vaccine development, auto-immune disorders and oncology immunotherapies. T-cell receptor sequencing allows characterization of a full repertoire with a single experiment, however the data this generates cannot be readily translated into medical action. With artificial intelligence models we can translate T-cell receptor sequencing data to actionable insight into the immune status of an individual.

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T-cell receptor diversity and AT-rich DNA sensing by glial cells as key features in controlling neurological varicella-zoster virus infections. 01/10/2018 - 30/09/2023

Abstract

Varicella-zoster virus (VZV) causes chickenpox in children and remains latent in neural ganglia afterwards. VZV reactivation causes shingles (herpes zoster, HZ). In WP1, we will prospectively recruit 150 HZ patients and 150 controls. We aim to show that the affinity of Major Histocompatibility Complex class I (MHC-I) molecules to bind VZV peptides, as needed for the development of VZV-specific Tcells, is reduced in HZ patients. Next, we will assess whether this reduced affinity leads to a reduced diversity of T-cell receptors directed against VZV, thereby implying a narrower scope of protection against VZV, or at least against several key VZV proteins. Finally, we will develop induced pluripotent stem cells (iPSC) derived sensory neurons from healthy individuals, infect these with VZV and assess whether addition of VZV-protein specific T-cells affects the control of VZV reactivation. In WP2, we aim to show that following primary VZV infection, glial cells, which are immune-responsive cells in the central nervous system, recognize VZV and subsequently produce protective cytokines. Moreover, we will assess whether mutations in AT-rich DNA sensor POL III in children with encephalitis, cerebellitis or stroke/vasculitis due to chickenpox cause a defective recognition of VZV and subsequently increased VZV proliferation in central neurons. We will do this by differentiating iPSC from patients and controls into neurons and glial cells, and subsequently infecting these with VZV.

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AT-DNA sensing & autophagy as major features in the development of chickenpox-associated neurological complications. 01/10/2018 - 30/09/2022

Abstract

Varicella-zoster virus (VZV) causes chickenpox in children and remains latent in neural ganglia afterwards. VZV can cause encephalitis or cerebellitis during both the acute and subacute phases of chickenpox. After resolution of chickenpox, VZV can reactivate from its latent state and cause herpes zoster. Moreover, VZV reactivation is believed to be able to cause stroke in children. The pathophysiology underlying all of these central nervous system VZV complications remains largely unknown so far. In this project, we aim to deepen our understanding regarding two factors that might cause a genetic predisposition in humans for the development of chickenpox-associated neurological complications. Preliminary data from our lab previously showed that mutations in RNA polymerase III (POL III) cause a defect in VZV sensing (via AT-DNA "recognition") in blood cells and consequently cause a reduced control of VZV proliferation. In this project, we first aim to show that following primary VZV infection, glial cells, which are immune-responsive cells in the central nervous system, recognize VZV and subsequently produce protective cytokines. Moreover, we will assess whether mutations in AT-DNA sensor POL III in children with encephalitis, cerebellitis or stroke/vasculitis due to chickenpox have a defective recognition of VZV and subsequently increased VZV proliferation in central neurons. We will do this by differentiating induced pluripotent stem cells (iPSC) from patients and controls into neurons and glial cells, and subsequently infecting these with VZV. This will lead to a simultaneous analysis of VZV dynamics in neurons and cytokine production by glial cells. Preliminary data from our labs and others have shown that the cellular process called autophagy, important for protein processing, might be involved in cellular VZV dynamics as inhibition of autophagy led to reduced VZV proliferation. In this project, we aim to further address this potential pathogenic route by experimentally inhibiting autophagy in iPSC-derived neurons from healthy controls and measuring the subsequent effects on VZV dynamics. In addition, we noted that 3/9 cerebellitis patients had a mutation in the autophagy-associated gene TBC19DB. In a first exploration, we will assess how autophagy is affected by this mutation and whether this influences VZV proliferation in monocytes from these patients and controls.

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An interdisciplinary study on the role of the HLA genes and T-cell diversity as risk factors for herpes zoster. 01/01/2018 - 31/12/2021

Abstract

Chickenpox is a consequence of primary infection of varicella-zoster virus (VZV). Afterwards, VZV remains latent in neural ganglia until symptomatic reactivation called herpes zoster (HZ, shingles). In this project, we will first develop a novel computational framework that will allow us to estimate the probability that a pathogen-derived antigen is adequately recognised by the major histocompatibility complexes (MHC) encoded by HLA genes. Antigen bounding by MHC molecules is a necessary step prior to recognition (and further management) of infected cells. Next, we will obtain HLA data from 150 HZ patients and 150 matched controls. This will allow us to estimate whether and which HLA A/B/C genes are enriched or depleted in HZ patients. Our computational framework will allow us to estimate which VZV proteins are most likely of importance in controlling VZV. We will assess whether the HLA data is readily translated into the diversity of the T-cell receptor (TCR) against VZV, and against which of the most important VZV proteins. Finally, we will differentiate blood-derived inducible pluripotent stem cells (iPSC) into neuronal cells, infect these neuronal cells with VZV and study whether depletion of VZV-specific T-cells affects VZV proliferation, thereby confirming our earlier obtained HLA-TCR predictions.

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Rapid vaccine development through immunoinformatics ans immunisequencing. 01/01/2018 - 31/10/2020

Abstract

Vaccines are used to stimulate the immune system in its defense against pathogens and cancer. Vaccine development involves extensive clinical trials that study the changes in antibodies and immune cells in response to the vaccine to determine their efficacy and safety. This is often an extensive and costly process, with a high failure rate. This project aims to develop a computational framework for use within vaccine clinical trials to make the process more efficient, more rapid and more accurate. The basis of this framework is the new immunological and molecular insights that have been gained through the advent of immunosequencing and immune-informatics technologies, and it builds further upon a successful collaboration between immunologists and data scientists.

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BVK / SBP award for PhD thesis: "The quantitative analysis of varicella-zoster virus infection: from epidemiology to immunology". 11/03/2016 - 31/12/2016

Abstract

Varicella-zoster virus (VZV) causes varicella (chickenpox) mainly in childhood and remains afterwards latent in neural ganglia. Clinical reactivation of VZV, due to reduced VZV-specific cellular immunity, causes herpes zoster (shingles). The secondary immune response following re-exposure to varicella is hypothesized to boost VZV-specific cellular immunity and thus to decrease the risk of herpes zoster in boosted individuals. Universal childhood varicella vaccination would temporary reduce the contact frequency between VZV-experienced individuals and varicella patients and thus increase the incidence of herpes zoster. As such, many countries are currently hesitant to introduce universal childhood varicella vaccination. The main goals of this PhD thesis were (1) to identify risk factors associated with VZV complications, (2) to study the dynamics of the secondary immune response following re-exposure to VZV and (3) to predict the consequences of universal childhood varicella vaccination on herpes zoster incidence by developing an individual-based population model. Using a multidisciplinary approach we were able to confirm the existence of exogenous boosting. However, both our experimental and modeling analyses presented data suggesting the individual effects of exogenous boosting to be limited to at most two years after re-exposure to varicella. Nevertheless, we predict the effects of a universal childhood varicella vaccination program on total herpes zoster incidence to be more or less the same as those by previous estimations that created hesitance amongst policy makers to implement varicella vaccination.

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    Development of immunoinformatics tools for the discovery of T-cell epitope recognition rules. 01/02/2016 - 31/01/2020

    Abstract

    Herpes viruses are ubiquitous in human society and cause several common diseases, such as cold sores (Herpes simplex) and chickenpox (Varicella). The eight species of herpes viruses known to primarily infect humans are all clinically relevant and of these, five are known to be extremely widespread amongst humans with seroprevalence rates as high as 90%. Not all individuals are equally susceptible to equivalent viral pathogens. After infection, some individuals do not become symptomatic, while others experience a high severity of the disease with serious complications. For example, a relatively benign disease such as chickenpox can become life-threatening in a small set of individuals. These differences in disease susceptibility are likely to be caused in part due to the variation in the human immune system, but remain largely unknown up to date. A key step in the activation of the adaptive immune system is the presentation of viral epitopes, usually peptides (p), by the major histocompatibility complex (MHC) present on antigen presenting cells (APC) and the recognition of this complex by a T-cell receptor (TCR). There exist many allelic variants of the genes coding for the MHC genes within the population and each variant has a different propensity to bind immunogenic (viral) peptides. This variability in the MHC alleles is one of the underlying factors that leads to differences in disease susceptibility. Previous research has demonstrated that high accuracy models can be established for the affinity of the MHC molecules for the presentation of peptides, based on machine learning methods. The resulting affinity prediction models have made it possible to assess the affinity for almost all human MHC alleles for any given peptide. However, the MHC recognition variability is only part of the story, as each individual has a unique repertoire of T-cells with a large diversity of TCR variants. The variability in TCR epitope recognition is also an important factor in differences between individual immune responses. Unfortunately, few TCR recognition models exist and they are all very limited in scope and accuracy. Therefore, the scope of this project is to develop, evaluate and apply state-of-the-art computational approaches to enable the interpretation of complex MHC-p-TCR interaction data and to elucidate the patterns that govern this system. Within this scope, a key point of interest will be the modelling of the molecular interaction between the MHC complex, encoded by its corresponding HLA allele, the antigen-specific TCR and the peptide antigen itself. Ultimately, this will result in the development of computational tools capable of predicting personalized immune responses to Herpes viruses and the efficacy of vaccine-induced viral protection.

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    Host genetic susceptibility for chickenpox associated neurological complications. 01/01/2016 - 31/12/2018

    Abstract

    Although chickenpox, caused by varicella-zoster virus (VZV), is in general a benign childhood disease, severe morbidity due to chickenpox-associated central nervous system complications do occur including VZV-cerebellitis, VZV-meningoencephalitis, and VZV-stroke. In a pilot study in Flanders, we have used whole-exome sequencing, mutation analysis and a stringent statistical algorithm to identify unique or rare variants in genes that were overrepresented in the patient population (N=22) (compared to large databases and in-house controls). With this proposal, we aim to expand our study population (in order to increase the validity of our results) via a national multi-centric study. We aim to recruit 20 new patients distributed over the three study populations (VZV-cerebellitis, VZV-meningoencephalitis, and VZV-stroke). We will use the same methodology as before (whole-exome sequencing, mutation analyses and statistics) in order to validate or extend the earlier found results. Furthermore, by expanding our patient database we will be able to collect more samples allowing us to perform functional analyses in the next step. This study will broaden our understanding of the pathophysiology underlying the neurological complications of chickenpox, and possibly also of herpes zoster.

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      Study of the epidemiological impact of the Varicella-zoster virus, the validity of the exogenous boosting hypothesis and the possible implications for public health. 17/11/2015 - 31/12/2016

      Abstract

      Varicella-zoster virus (VZV) causes varicella (chickenpox) mainly in childhood and remains afterwards latent in neural ganglia. Clinical reactivation of VZV, due to reduced VZV-specific cellular immunity, causes herpes zoster (shingles). The secondary immune response following re-exposure to varicella is hypothesized to boost VZV-specific cellular immunity and thus to decrease the risk of herpes zoster in boosted individuals. Universal childhood varicella vaccination would temporary reduce the contact frequency between VZV-experienced individuals and varicella patients and thus increase the incidence of herpes zoster. As such, many countries are currently hesitant to introduce universal childhood varicella vaccination. The main goals of this PhD thesis were (1) to identify risk factors associated with VZV complications, (2) to study the dynamics of the secondary immune response following re-exposure to VZV and (3) to predict the consequences of universal childhood varicella vaccination on herpes zoster incidence by developing an individual-based population model. Using a multidisciplinary approach we were able to confirm the existence of exogenous boosting. However, both our experimental and modeling analyses presented data suggesting the individual effects of exogenous boosting to be limited to at most two years after re-exposure to varicella. Nevertheless, we predict the effects of a universal childhood varicella vaccination program on total herpes zoster incidence to be more or less the same as those by previous estimations that created hesitance amongst policy makers to implement varicella vaccination.

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        Gene expression analyses for the differentiation between viral and bacterial meningitis in children. 01/07/2015 - 30/06/2017

        Abstract

        Rapid detection of bacterial meningitis in children remains an important goal for emergency room doctors and paediatricians. The differentiation between viral and bacterial meningitis in children is mainly based on clinical scoring systems that are, however, neither 100% sensitive nor 100% specific. Additionally, adequate sampling of cerebrospinal fluid (CSF) is not always achievable. Recently, the value of gene expression analyses for infectious diseases has been illustrated in several clinical and experimental settings. Several studies were able to show a difference in gene expression between different types of influenza, between different types of bacterial infections, between tuberculosis and other inflammatory or infectious diseases in African children and between some viral infections and some bacterial infections. However, none of these studies specifically addressed the value of gene expression analyses in differentiating between viral and bacterial meningitis. In this multicentre prospective study, we will use whole blood gene expression analyses to differentiate between viral and bacterial infections in children with meningitis (N = 80). This study will add to the important clinical differentiation between viral and bacterial meningitis in children. Furthermore, we believe that the determination of the gene expression signalling in bacterial (but also viral) meningitis will elucidate the pathophysiology of this disease.

        Researcher(s)

        Research team(s)

          Project type(s)

          • Research Project

          A quantitative analysis of varicella-zoster virus infection: from immunology to epidemiology. 01/10/2013 - 31/07/2015

          Abstract

          It is our goal to conceptualise mathematical models that describe the basic immunology with regard to varicella-zoster virus (VZV) and immunological perturbations caused by VZV at the individual level. Furthermore, at the population based level we will formulate mathematical models describing the transmission of VZV between individuals. Simulations of both withinhuman and between-human dynamics will be based on biological and epidemiological parameters. These parameters will be estimated from our previous studies, and other international studies, as well as this project's experimental study, which is designed to provide major insights in the immunology of latency and reactivation. More specifically, we will longitudinally assess the immune response of about 120 VZV immune persons whose immune systems were recently perturbed for different reasons such as re-exposure to VZV and reactivation of VZV as shingles (Herpes Zoster). In an innovating way we will also perform similar analyses in 30 healthy individuals thereby creating a control group and defining a benchmark for longitudinal variation in immunity. The biological parameters will be implemented in our newly developed mathematical models after thorough statistical analysis. For the first time in this field, we will apply certain advanced statistical techniques (nonlinear mixed and growth mixture models).

          Researcher(s)

          Research team(s)

            Project type(s)

            • Research Project

            Identification of genetic factors leading to neurological complications of chickenpox. 31/01/2013 - 30/10/2015

            Abstract

            This project represents a formal research agreement between UA and on the other ESPID. UA provides ESPID research results mentioned in the title of the project under the conditions as stipulated in this contract.

            Researcher(s)

            Research team(s)

              Project type(s)

              • Research Project

              The quantitative analysis of varicella-zoster virus infection: from epidemiology to immunology 15/11/2011 - 31/12/2012

              Abstract

              The general aim is (1) to quantify exogenous boosting by means of an observational longitudinal study, (2) implement this result in newly adapted epidemiological models and (3) assess the population effects of universal vaccination against VZV.

              Researcher(s)

              Research team(s)

                Project type(s)

                • Research Project

                A quantitative analysis of varicella-zoster virus infection: from immunology to epidemiology. 01/10/2011 - 30/09/2013

                Abstract

                It is our goal to conceptualise mathematical models that describe the basic immunology with regard to varicella-zoster virus (VZV) and immunological perturbations caused by VZV at the individual level. Furthermore, at the population based level we will formulate mathematical models describing the transmission of VZV between individuals. Simulations of both withinhuman and between-human dynamics will be based on biological and epidemiological parameters. These parameters will be estimated from our previous studies, and other international studies, as well as this project's experimental study, which is designed to provide major insights in the immunology of latency and reactivation. More specifically, we will longitudinally assess the immune response of about 120 VZV immune persons whose immune systems were recently perturbed for different reasons such as re-exposure to VZV and reactivation of VZV as shingles (Herpes Zoster). In an innovating way we will also perform similar analyses in 30 healthy individuals thereby creating a control group and defining a benchmark for longitudinal variation in immunity. The biological parameters will be implemented in our newly developed mathematical models after thorough statistical analysis. For the first time in this field, we will apply certain advanced statistical techniques (nonlinear mixed and growth mixture models).

                Researcher(s)

                Research team(s)

                  Project type(s)

                  • Research Project