The Origins of Human Anti-Insulin B Lymphocytes in Type 1 Diabetes

项目总结 B淋巴细胞通过递呈自身抗原来协调1型糖尿病(T1D)的自身免疫β细胞攻击 杀死β细胞的T细胞。循环中的胰岛素自身抗体(IAA)不是直接致病的，但有助于预测 T1D通过发出这种危险的B/T淋巴细胞串扰的信号。产生胰岛素的β细胞的免疫靶向 在有症状的糖尿病发作前几个月甚至几十年内发生。糖尿病进展中的异质性 临床试验的反应减缓了对T1D疗法的探索。更好的生物标记物用于识别和机械地 解释需要响应者来克服这一瓶颈。保护性免疫反应通常由T细胞引起 生发中心B淋巴细胞的细胞选择和亲和力成熟，产生记忆B淋巴细胞 和抗体分泌细胞分化。然而，自身免疫反应并不总是遵循这一途径。 例如，我们发现抗胰岛素B细胞(AIBCs)会加速T1D倾向小鼠的糖尿病，但很少有AIBCs 分化为分泌IAA的细胞，尽管进入生发中心。填补AIBC知识空白 在T1D早期扩展，我们建立了一个独特的、精心管理的无症状T1D试验网生物库 参与者。我们在IAA阴性的症状前T1D捐赠者的外周血中发现了AIBCs， 通过循环IAA证明B淋巴细胞对胰岛素的自身免疫逃避常规检测 高危人群的子集。每次访问T1D TrialNet时的纵向采样和临床测试提供 随着T1D从阶段1(正常糖耐量)进展到T1D，识别供者特定变化的机会 阶段2(糖耐量受损)和阶段3(糖尿病)。我们发现AIBC偏向于记忆B 细胞表型。克隆扩增的记忆B淋巴细胞表达生殖系和最小突变的B细胞 第1阶段T1D供者的受体。这些数据支持我们的假设，即AIBCs扩展并进入记忆 糖耐量受损前的隔室，有时不产生IAA。我们将整合AIBC 表型，B细胞受体(免疫球蛋白)序列同一性，克隆相关性，B细胞受体 对胰岛素的亲和力/亲和力，以及胰岛素表位图，以确定支配胰岛素识别的特征。高- 通过对B细胞受体谱系与细胞表型配对的单细胞分析将发现 同一供者随时间和T1D分期进展来确定B淋巴细胞谱系和亚群 当糖耐量丧失时发生的变化。除了记忆偏差，AIBC还显示出偏向的V和J 免疫球蛋白基因的使用。我们将跟踪这些功能的组合，并使用LIBRAseq来确定候选 重组表达和检测胰岛自身抗原识别的自身反应性BCR，包括其他已知的 胰岛自身抗原(GAD65、IA-2、ICA512和ZnT8)。人源性抗胰岛素BCR单抗 我们将开发的序列数据库和分析管道/代码将公开提供。这些研究 是在临床试验中使用AIBCs作为生物标记物以确定有利的变化的必要步骤 细胞自身免疫，并聚焦于AIBCs经历的特定变化到去卷曲反应的异质性。

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.