Project Summary During this past R01 funding period, we have mapped causal effects within the MHC region to specific HLA-DR binding groove amino acid sites, identified >100 rheumatoid arthritis (RA) non- MHC risk alleles across the genome, and have demonstrated that these alleles are largely within CD4+ T cell regulatory elements. If we could define the genetic mechanisms underpinning RA susceptibility, then it may be possible to define therapeutic strategies to abrogate or prevent RA. Central to this is defining the key T cells involved in mediating disease susceptibility – both in terms of their unique TCR sequence features and their pathogenic cell states. Here, we hypothesize that HLA-DR risk alleles act within the thymus to favor selection of “sentinel TCRs”, and that when autoantigens are presented to sentinel TCRs, risk alleles within T cell enhancers alter T cell specific gene regulation, which enables naïve T cells expressing sentinel TCRs to transition into a pathogenic state. We define “sentinel TCRs” as those receptors that bind to citrullinated peptides and trigger the initial autoimmune response. Risk alleles in T cell promoters and enhancers alter regulation of critical T cell genes that regulate the transition of T cells into pathogenic states. Hence, a T cell with a rare “sentinel TCR” can, under the right conditions, trigger the initial autoimmune response, drive a spreading immune response, and initiate persistent joint inflammation. But, the key pathogenic T cell states, sentinel TCRs, and the action of specific causal regulatory T cell alleles are not yet fully defined. Repertoire sequencing to define TCR sequences in blood and tissue, single cell analyses to resolve T cell states, and genetic engineering to interrogate causal T cell alleles and genes represent exciting methodologies that our lab has developed expertise in. In this proposal we seek to build support for this model. First, we will demonstrate that HLA class II HLA RA risk alleles alter TCR repertoire to harbor “sentinel TCRs”, using TCR and genotype data from 300 healthy individuals. Next, we will use polygenic RA risk models to define the key T cell states that RA risk alleles influence with single cell data on surface markers and transcripts in the same 300 individuals. Finally, we will define the molecular mechanisms of non-coding alleles using genomic editing in CD4+ T cells; to this end we will develop and apply strategies to edit primary T cells, sequence DNA to confirm the presence of the desired edit, and obtain RNA and ATAC sequencing data to understand the impact of the edit and confirm the functionality of non- coding alleles.