Friday, May 9, 2025
5/9/2025
The Origins of Human Anti-Insulin B Lymphocytes in Type 1 Diabetes - PROJECT SUMMARY B lymphocytes orchestrate autoimmune beta cell attack in type 1 diabetes (T1D) by presenting autoantigen to T cells which kill beta cells. Circulating insulin autoantibodies (IAAs) are not directly pathogenic but help predict T1D by signaling this dangerous B/T lymphocyte crosstalk. Immune targeting of insulin-producing beta cells occurs for months or even decades before symptomatic diabetes onset. Heterogeneity in diabetes progression and clinical trial responses slow the search for a T1D cure. Better biomarkers to identify and mechanistically explain responders are needed to overcome this bottleneck. Protective immune responses typically arise by T cell selection and affinity maturation of B lymphocytes in germinal centers, resulting in memory B lymphocyte and antibody-secreting cell differentiation. However, autoimmune responses do not always follow this pathway. For example, we find anti-insulin B cells (AIBCs) accelerate diabetes in T1D-prone mice, yet few AIBCs differentiate into IAA-secreting cells, despite entering germinal centers. To fill gaps in knowledge AIBC expansion early in T1D, we built a unique, carefully-curated biobank of pre-symptomatic T1D TrialNet participants. We find AIBCs in the peripheral blood of IAA-negative pre-symptomatic T1D donors, demonstrating B lymphocyte autoimmunity for insulin evades conventional detection via circulating IAAs in a subset of at-risk individuals. Longitudinal sampling and clinical testing at each T1D TrialNet visit provide opportunities to identify donor-specific changes as T1D progresses from stage 1 (normal glucose tolerance) to stage 2 (impaired glucose tolerance) and stage 3 (diabetes). We find AIBCs are skewed towards a memory B cell phenotype. Clonally-expanded, memory B lymphocytes express germline and minimally-mutated B cell receptors in stage 1 T1D donors. These data support our hypothesis that AIBCs expand and enter the memory compartment prior to glucose tolerance impairment, sometimes without IAA production. We will integrate AIBC phenotype, B cell receptor (immunoglobulin) sequence identity, clonal relatedness, B cell receptor affinity/avidity for insulin, and insulin epitope mapping to identify features that govern insulin recognition. High- throughput single cell analysis of B cell receptor repertoire paired with cell phenotype will identify changes in the same donor over time and with T1D stage progression to determine B lymphocyte repertoire and subset shifts that occur as glucose tolerance is lost. In addition to memory skewing, AIBCs show biased V and J immunoglobulin gene use. We will track this combination of features and use LIBRAseq to identify candidate autoreactive BCRs to recombinantly express and test for islet autoantigen recognition, including other known islet autoantigens (GAD65, IA-2, ICA512, and ZNT8). The human monoclonal antibodies, anti-insulin BCR sequence database, and analysis pipeline/code we will develop will be made publicly available. These studies are a necessary step towards using AIBCs as biomarkers in clinical trials to identify favorable changes in cellular autoimmunity and zero in on specific changes AIBCs undergo to deconvolute response heterogeneity.
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