Multi-modal single cell analysis for investigation of T1D pathogenesis

1型糖尿病（T1D）是一种由β细胞特异性自身反应偶联引起的慢性自身免疫性疾病

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.