Type 1 diabetes (T1D) is an autoimmune disease, whose symptoms and complications result in increased morbidity, mortality, and life-long dependence on insulin. The Type 1 Diabetes Genetics Consortium (T1DGC, Stephen Rich, PI) conducted the largest T1D GWAS meta-analysis and identified over 40 T1D risk loci. The T1DGC refined the T1D risk variants by fine mapping with the ImmunoChip and constructing sets of 99% credible single nucleotide polymorphisms (SNPs) within each locus. Bioinformatic analyses of T1D-associated credible SNPs discovered enrichment in regions involved in gene regulation of immune-relevant cell types (CD4 and CD8 T cells, CD19 B cells). Despite these discoveries on the genetic basis of T1D, the mechanisms that define how T1D-associated SNPs contribute to disease susceptibility remain unclear. Here, we propose a powerful and innovative approach to define function of the T1D-associated SNPs and identify their target, causal effector genes through integrated analyses of T1D-relevant tissues. We will (Aim 1) generate an integrated 3D map of the gene regulatory architecture of T1D susceptibility by conducting ATAC-seq, RNA-seq and whole- genome promoter-focused Capture-C analysis on purified human cell populations;
(Aim 2) perform single-cell immunophenotyping and eQTL analysis of T1DGC samples using CITE-seq, a single-cell RNA-seq approach guided by DNA-barcoded antibodies against lineage markers to characterize the immune cell subsets identified in Aim 1, allowing us to focus on SNPs that are regulatory and likely contribute to T1D risk;
and (Aim 3) conduct functional validation of T1D SNP-gene regulatory effects using CRISPR/Cas9 genome editing in human immune cells to directly test whether these SNPs reside in regions that are required for T1D gene expression using Cas9-mediated editing. Our outstanding research team provides complementary and synergistic approaches to understanding the function and gene targets that modulate genetic risk of T1D. Together, we will establish the mechanisms underlying contribution of T1D-associated SNPs to inflammatory gene regulation and, by revealing the SNP-enhancer-gene link in 3D, are poised to discover novel molecular targets for therapeutic intervention to treat or prevent T1D.
We identified over forty type 1 diabetes (T1D) risk loci and fine-mapped each locus, revealing that the single nucleotide polymorphisms (SNPs) associated with T1D are enriched in DNA regulatory regions of immune- relevant cells. Here, we will determine the function of these T1D SNPs, identify their target genes using integrated 3D regulatory maps of T1D susceptibility regions coupled with single-cell immune-phenotyping of human samples; further, functional validation by genome editing will be applied to human immune cells. Together, these studies will establish the mechanisms underlying the contribution of T1D-associated SNPs to gene regulation, enabling the discovery of novel molecular targets for therapeutic intervention to treat or prevent T1D.
