Prioritizing and Characterizing T Cell-Relevant Genetic Variants Associated with Autoimmune Diseases

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PROJECT SUMMARY Greater than 8% of the United States population suffers from autoimmune disease, but, due to complex non- Mendelian inheritance, the genetic determinants of autoimmune disease are difficult to parse. To begin to address this problem, genome-wide association studies (GWAS) have identified thousands of genetic variants that track with disease, allowing the field of autoimmunity to focus on key disease-causal regions of the genome. However, the exact causal genetic variants for most of these associations remain unidentified, and thus the genes and pathways they alter remain poorly understood. To tackle this problem, I first will enrich for likely causal variants for diseases in which T cells are known to be pathogenic, including multiple sclerosis, type I diabetes, rheumatoid arthritis, psoriasis, and inflammatory bowel disease. I will use a high-throughput approach to test 20,000 variants for allelic skew in reporter expression. Furthermore, for 4 highly important GWAS loci (each with more than 10 disease associations), I will screen for regulatory regions that alter gene expression and the disease-associated variants that lie within these regions. With these two approaches (and other genomic data, such as chromatin accessibility and allele-specific transcription factor ChIP-seq), I will prioritize variants for engineering in the genomes of primary cells, and determine the effects of these engineered alleles on expression, activation, and polarization of T cells. This project will result in exhaustive characterization of variants associated to 5 important autoimmune diseases, elucidation of the regulatory architecture of 4 highly important disease loci, and experimental validation of 10 putatively causal variants through editing them into the genome of primary T cells. This work will provide an extensive resource for GWAS follow-up studies, help bring the field closer to understanding the pathways and regulatory architecture involved in disease, and inform approaches for identifying new targeted therapeutics for autoimmunity.