Multi-modal single cell analysis for investigation of T1D pathogenesis

1型糖尿病(T1D)是一种慢性自身免疫性疾病，是β-细胞特异性自身反应偶联的结果 免疫调节失灵。活着的个体无法接触到胰腺，这就要求 大多数检测T1D患者免疫细胞功能的研究来自于外周血，而外周血可能不是 准确反映目标器官中发生的事件。此外，尽管&gt；150个基因组区域是相关的 对于T1D风险，关于这些基因座的亚集和激活状态特异性表达知之甚少，并且 风险变异对免疫功能的影响。因此，需要对分子基础进行研究 对于与疾病相关的组织，即胰腺和胰腺中与T1D相关的免疫失调 引流淋巴结(PLN)。此外，尽管调节性T细胞(Treg)功能缺陷与 在T1D中出现对β细胞抗原的耐受性丧失，其潜在机制尚不完全清楚。我的 总体目标是确定T1D风险变异对糖尿病免疫细胞的作用机制 使用高参数单细胞数据集的非监督和监督分析识别基因的表型 和通路，当被操纵时，将导致增强的Treg功能。T1D风险的充实 DNA调控区域内的变异意味着这些变异可能会影响候选基因的表达。此外， 许多已知的候选基因与Treg的激活和功能有关。因此，我假设 免疫细胞中候选基因的异常表达和调节通过以下途径导致T1D耐受性丧失 促进Treg的不稳定性，这可以通过基因编辑进行机械研究。公司的技术创新 这项研究在于高维单细胞技术在未被研究的组织中的应用 在T1D发病机制中是必不可少的。本研究的理论创新之处在于有机会跨越多个 通过整合关键的免疫细胞亚群的转录，表观基因组， 和蛋白质组图谱。到目前为止，还不存在以单像元分辨率包含此信息的数据集 人体器官供体组织，因此我的目标是横断面评估免疫表型的遗传调节。 在人类器官捐赠者队列中。重要的是，我的初步数据表明细胞亚群表达T1D候选 风险基因和TH1相关标记物在T1D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T1D风险变量在 通过执行单细胞RNA测序(scRNA-Sequence)促进促炎作用超过调节性T细胞表型 Seq)和scatac-seq.最后，虽然T1D候选基因被认为影响Treg功能，但我建议 在抗原特定的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Tregs相比。这项工作的意义在于有可能定义组织特异性 高分辨率的调节和促糖尿病细胞亚群，以及这一知识为翻译提供信息 努力开发针对T1D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.