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Project

Systems vaccinology in toddlers en children

Despite great achievements in medicine, infectious diseases are still a leading cause of children morbidity and mortality. Up until now, most vaccines have been empirically generated without a true understanding of the precise immunologic mechanisms of action of successful vaccines. As we are now facing difficulties in developing new or more efficient vaccines, we need to understand the precise mechanisms underlying successful vaccination and identify the markers of successful response. Systems Vaccinology uses multiple parameter analyses from high throughput sources to apprehend the immunological basis of responses to vaccination by determining the changes in cellular composition and by performing molecular analysis, such as protein synthesis or gene expression, providing an opportunity to deeply understand the mechanisms that lead to vaccine-induced protection. Despite children being the most important recipients of vaccines, these studies have almost exclusively been performed on adults, which possess a radically different immune status. To correct this deficit, we aim to perform the first systems vaccinology study in children, across multiple age groups and multiple vaccines (coinciding with scheduled vaccinations), collaborating with well-baby clinics, day care centers and the school system. For each individual, blood will be collected before the vaccination, three days and four weeks later to assess the immune response.  We will prospectively perform in-depth immunophenotyping by flow cytometry before and after each vaccine, using advanced flow cytometry analyzer (BD FACSymphony). Extensive cell immune profiling will be achieved, including T cell subsets, B cell subsets, myeloid cell subsets and NK cell subsets. Moreover, activation and maturation markers on each subset can be assessed, allowing more than 1500 biologically relevant cell subsets to be quantified per sample. In addition, serum analysis for key cytokines will be performed via multiplex assay with electroluminescence detection (MSD). For weeks after vaccination, high-throughput assays to measure antibody response will be performed, allowing characterization of biophysical and functional antibody properties, in order to precisely determine vaccine response. Using the results from our previous step, we aim to identify the immune signature that dictates and that can predict immune responses after vaccination in children. To this aim, we will use a systems vaccinology and systems serology approach, with classical and machine-learning strategies to analyze the dataset. The immunological parameters measured in the phenotyping platform (at baseline and follow-up) as well as the cytokine production will be assessed for correlation with vaccine response. Multiple modelling will be used to determine the primary effect of each parameter as much as their synergistic effect on vaccine response. We aim to identify the immunological parameters, or the combination of them, that are key for the prediction of vaccine response and identify which predictors are restricted to age groups or common across the paediatric cohort and which are restricted or common among classes of vaccines. Using these high-throughput technologies, we seek to understand the immunological basis of responses to vaccination in paediatric population, which to our knowledge, has never been performed before. This knowledges will provide much needed insights in vaccinology, allowing vaccine development to shift from an empiric to a functional approach, targeting specific immune components in order to achieve optimal response for either challenging pathogens or for vulnerable populations such as children, who are the principal group exposed to infectious morbidity and mortality and to vaccination, which will undeniably be a major asset to improve children’s health care.

Date:1 Oct 2019 →  Today
Keywords:Immunology, Pediatrics, Vaccinology, Systems immunology, Systems vaccinology
Disciplines:Adaptive immunology, Applied immunology , Vaccinology
Project type:PhD project