Publications by authors named "S I Mannering"

Type 1 diabetes (T1D) is an autoimmune disease that develops when T cells destroy the insulin-producing beta cells that reside in the pancreatic islets. Immune cells, including T cells, infiltrate the islets and gradually destroy the beta cells. Human islet-infiltrating CD4 T cells recognize peptide epitopes derived from proinsulin, particularly C-peptide.

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Antigen-driven T-cell proliferation is often measured using fluorescent dye dilution assays, such as the CFSE-based proliferation assay. Dye dilution assays have been powerful tools to detect human CD4 T-cell responses, particularly against autoantigens. However, it is not known how many cells within the proliferating population are specific for the stimulating antigen.

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Type 1 diabetes (T1D) is a T cell-mediated autoimmune disease that has a strong HLA association, where a number of self-epitopes have been implicated in disease pathogenesis. Human pancreatic islet-infiltrating CD4 T cell clones not only respond to proinsulin C-peptide (PI GQVELGGGPGAGSLQ) but also cross-react with a hybrid insulin peptide (HIP; PI-IAPP GQVELGGG-NAVEVLK) presented by HLA-DQ8. How T cell receptors recognize self-peptide and cross-react to HIPs is unclear.

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In an effort to improve HLA-"humanized" mouse models for type 1 diabetes (T1D) therapy development, we previously generated directly in the NOD strain CRISPR/Cas9-mediated deletions of various combinations of murine MHC genes. These new models improved upon previously available platforms by retaining β2-microglobulin functionality in FcRn and nonclassical MHC class I formation. As proof of concept, we generated H2-Db/H2-Kd double knockout NOD mice expressing human HLA-A*0201 or HLA-B*3906 class I variants that both supported autoreactive diabetogenic CD8+ T cell responses.

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Article Synopsis
  • * Ongoing research focuses on understanding T-cell responses and developing effective disease-modifying agents that could be useful in the early stages of T1D.
  • * Advanced profiling techniques at the single-cell level aim to discover new biomarkers and improve assays for characterizing antigen-specific T cells, enhancing the ability to predict disease progression and treatment responses.
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