Multi-modal single cell analysis for investigation of T1D pathogenesis

1型糖尿病（T1 D）是一种慢性自身免疫性疾病， 免疫调节失败。胰腺无法从活人身上获取，这就要求 大多数检查T1 D中免疫细胞功能的研究来自外周血，其可能不 准确反映靶器官中发生的事件。此外，尽管>150个基因组区域与 对于T1 D风险，关于这些基因座的亚群和激活状态特异性表达知之甚少， 风险变体对免疫功能的影响。因此，需要进行研究，检查分子基础 对于疾病相关组织中的T1 D相关免疫失调，即胰腺和胰腺癌， 引流淋巴结（pLN）。此外，虽然调节性T细胞（Treg）功能的缺陷涉及免疫缺陷，但其可能与免疫缺陷有关。 T1 D中所见的对β细胞抗原的耐受性丧失，其潜在机制尚未完全了解。我 总体目标是确定T1 D风险变异导致糖尿病免疫细胞的机制， 使用高参数单细胞数据集的无监督和有监督分析来识别基因的表型 以及当被操纵时将导致增强的Treg功能的途径。T1 D风险的富集 DNA调控区域内的变异意味着这些变异可能影响候选基因的表达。此外，委员会认为， 许多已知的候选基因与Treg的激活和功能有关。因此，我假设 免疫细胞中异常的候选基因表达和调节通过以下方式导致T1 D耐受性丧失： 促进Treg不稳定性，可以通过基因编辑进行机制研究。的技术创新 这项研究在于将高维单细胞技术应用于研究不足的组织， 对T1 D发病机制至关重要。本研究的理论创新之处在于有机会弥合多重 模式，从而通过整合它们的转录组，表观基因组， 和蛋白质组图谱。到目前为止，还不存在以单细胞分辨率包含此信息的数据集， 人体器官供体组织，因此，我的目标是评估免疫表型的遗传调控横截面 在一个人体器官捐献者队列中。重要的是，我的初步数据表明表达T1 D候选者的细胞亚群 风险基因和TH 1相关标记物在T1 D患者的pLN中过度表达。目前，分子 这种表型的基础尚不清楚。因此，我建议辨别T1 D风险变异在以下方面的潜在作用： 通过进行单细胞RNA测序（scRNA-DNA测序）来促进促炎性超过调节性T细胞表型。 seq）和scATAC-seq.最后，虽然T1 D候选基因被认为会影响Treg功能，但我建议 在抗原特异性背景下对此进行建模，因为这些细胞可能代表更有效的细胞治疗产品 与多克隆TclA相比。这项工作的意义在于有可能定义组织特异性 调节和糖尿病细胞亚群在高分辨率，以及为这方面的知识，以告知翻译 努力开发T1 D的优化途径靶点和细胞疗法。

Type 1 diabetes (T1D) is a chronic autoimmune disease which results from β-cell specific autoreactivity coupled with failures in immunoregulation. The inaccessibility of the pancreas from living individuals mandates that the majority of studies examining immune cell function in T1D be derived from peripheral blood, which may not accurately reflect events occurring in the target organ. Moreover, although >150 genomic regions are associated with T1D risk, little is known regarding subset- and activation state-specific expression of these loci, and the effect of risk variants on immune function. Thus, there exists a need for studies examining the molecular basis for T1D-associated immune dysregulation in disease-relevant tissues, namely, the pancreas and pancreatic draining lymph nodes (pLN). Additionally, while deficits in regulatory T cell (Treg) function are implicated in the loss of tolerance to β-cell antigens seen in T1D, the underlying mechanisms are incompletely understood. My overall goal is to identify the mechanisms by which T1D risk variants contribute to diabetogenic immune cell phenotypes using unsupervised and supervised analysis of high parameter single-cell datasets to identify genes and pathways which, when manipulated, will result in enhanced Treg function. The enrichment of T1D risk variants within DNA regulatory regions implies these variants may impact candidate gene expression. Moreover, many known candidate genes are associated with Treg activation and function. Therefore, I hypothesize that aberrant candidate gene expression and regulation in immune cells contributes to loss of tolerance in T1D by promoting Treg instability that can be studied mechanistically through gene-editing. The technical innovation of this research lies in the application of high-dimensional single cell technologies in understudied tissues that are essential to T1D pathogenesis. The theoretical innovation of this research lies in the opportunity to bridge multiple modalities and thereby, characterize key immune cell subsets by integrating their transcriptomic, epigenomic, and proteomic profiles. To date, a dataset comprising this information at single cell resolution does not exist for human organ donor tissue, thus I aim to assess the genetic regulation of immune phenotypes cross-sectionally in a human organ donor cohort. Importantly, my preliminary data indicate cell subsets expressing T1D candidate risk genes and TH1-associated markers are overrepresented in the pLN of T1D patients. Currently, the molecular basis for this phenotype is unclear. Therefore, I propose to discern the potential role of T1D risk variants in promoting proinflammatory over regulatory T cell phenotypes by performing single cell RNA-sequencing (scRNA- seq) and scATAC-seq. Lastly, while T1D candidate genes are thought to impact Treg function, I propose to model this in an antigen specific context, as these cells likely represent a more efficacious cell therapy product as compared to polyclonal Tregs. The significance of this work lies in the potential for defining tissue specific regulatory and diabetogenic cell subsets at high resolution, as well as for this knowledge to inform translational efforts developing optimized pathway targets and cellular therapies for T1D.