Peanut allergy is an important public health problem carrying the risk of severe allergic reactions and even death. In this project, we will seek new fundamental understanding of peanut allergy and oral Immunotherapy (OIT) by studying allergen-specific B cell and T cell populations isolated by flow cytometry, and apply new high-throughput DNA sequencing methods to characterize these cells and the immunoglobulin (Ig) or T cell receptors (TCR) they express.
We aim to answer these questions: 1. What are the Ig and TCR gene rearrangements in peanut allergen-specific B cells and T cells? 2. What is the frequency, diversity, persistence, and cellular immunophenotype (or Ig isotype) of clonally-related peanut allergen-specific B cell populations or T cell populations in patients? 3. What phenotypic or population changes does OIT induce in allergen-specific B or T cell clones, and the rest of the patient's B cell and T cell repertoire? We will evaluate whether the peanut allergen-specific B cells and T cells In allergic patients have features that correlate with disease severity, such as greater clonal diversity, clonal expansion size, antibody affinity maturation, stereotypic receptor rearrangements, or membership in particular phenotypic subsets. In addition, we will track these lymphocyte population features In longitudinal samples from patients undergoing OIT to identify the effects of peanut oral immunotherapy or placebo treatment, and determine which alterations correlate most closely with the development of tolerance versus desensitization to peanut allergens. We will assess for the presence of clonal relationships between allergen-specific regulatory and effector T cell populations, and between B cells expressing different antibody isotypes to determine if the major effect of oral immunotherapy protocols on lymphocyte populations is to recruit new clonal lineages of allergen-specific B cells and T cells, or rather to alter the phenotype of pre-existing allergen-specific B cell and T cell clonal populations. Features of B cell or T cell populations that correlate with tolerance induction will be of particular interest, as they could offer information to improve patient management in OIT protocols. Our data will be integrated with those of Projects 1, 3, 4 and Scientific Core B in the statistical analysis of Core A to extract the best biomarkers for monitoring and predicting patient outcomes to OIT.
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