Defining the influence of RA genetic susceptibility factors on T cell antigen specificity and functional state

定义 RA 遗传易感因素对 T 细胞抗原特异性和功能状态的影响

• 批准号: 10414964
• 负责人: Soumya Raychaudhuri
• 金额: $ 68.39万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-02 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10414964
• 关键词: ATAC-seq; Affect; Alleles; Amino Acid Sequence; Amino Acids; Antigens; Autoantigens; Autoimmune Diseases; Autoimmune Responses; Automobile Driving; BACH2 gene; Base Pairing; Binding; Biological Assay; Blood; CCL21 gene; CD4 Positive T Lymphocytes; CTLA4 gene; Cells; Cellular Assay; Chromatin; DNA Sequence; Data; Disease; Disease susceptibility; Electrophoretic Mobility Shift Assay; Engineering; Enhancers; Funding; Gene Expression Regulation; Genes; Genetic; Genetic Engineering; Genetic Models; Genetic Predisposition to Disease; Genetic Risk; Genome; Genotype; HLA-DR Antigens; Human Genetics; IL2RA gene; Immune response; Individual; Link; Luciferases; Maps; Mediating; Methodology; Modeling; Molecular; Nucleic Acid Regulatory Sequences; Pathogenesis; Pathogenicity; Peptides; Predisposition; Proteomics; RNA; Regulation; Regulatory Element; Regulatory T-Lymphocyte; Research Personnel; Rheumatoid Arthritis; Risk; Role; Sentinel; Site; Specificity; Statistical Methods; Surface; Synovial Membrane; Synovitis; Systemic Lupus Erythematosus; T-Lymphocyte; T-cell inflamed; T-cell receptor repertoire; Technology; Therapeutic; Thymus Gland; Tissues; Transcript; Transgenic Organisms; Untranslated RNA; Variant; XCL1 gene; analytical method; base editing; causal variant; cohort; genome editing; genomic locus; high dimensionality; innovation; joint inflammation; novel; novel therapeutic intervention; prevent; promoter; protein biomarkers; receptor binding; risk variant; single cell analysis; transcriptomics

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.

项目概要 在过去的 R01 资助期间，我们将 MHC 区域内的因果影响映射到 特定的 HLA-DR 结合沟氨基酸位点，已鉴定 > 100 个非类风湿性关节炎 (RA) MHC 风险等位基因遍布整个基因组，并已证明这些等位基因很大程度上是 如果我们能够定义 CD4+ T 细胞调控元件的遗传机制。 RA 易感性的基础，那么就有可能定义治疗策略 消除或预防 RA 的核心是确定参与介导疾病的关键 T 细胞。 易感性——无论是其独特的 TCR 序列特征还是致病细胞 在这里，我们研究了 HLA-DR 风险等位基因在胸腺内的作用，以利于选择。 “前哨 TCR”，当自身抗原呈递给前哨 TCR 时，内部的风险等位基因 T 细胞增强剂改变 T 细胞特异性基因调控，使幼稚 T 细胞能够表达 我们将“前哨 TCR”定义为转变为致病状态的前哨 TCR。 与瓜氨酸肽结合并触发初始自身免疫反应的受体。 T 细胞启动子和增强子中的等位基因改变了关键 T 细胞基因的调节，这些基因调节 因此，具有罕见“前哨 TCR”的 T 细胞可以在以下情况下转变为致病状态： 合适的条件，触发最初的自身免疫反应，驱动免疫扩散 反应，并引发持续性关节炎症，但是，关键的致病性 T 细胞状态是， 前哨 TCR 以及特定因果调节 T 细胞等位基因的作用尚未完全确定。 库测序可定义血液和组织中的 TCR 序列，单细胞分析可 解析 T 细胞状态，并通过基因工程询问因果 T 细胞等位基因和基因 我们的实验室已经开发了令人兴奋的方法学专业知识。在这项提案中，我们 首先，我们将证明 HLA II 类 HLA RA 风险。 等位基因使用来自 300 个的 TCR 和基因型数据改变 TCR 库以容纳“哨兵 TCR” 接下来，我们将使用多基因 RA 风险模型来定义关键的 T 细胞状态。 RA 风险等位基因对表面标记和转录本的单细胞数据有影响 最后，我们将定义非编码等位基因的分子机制。 在 CD4+ T 细胞中使用基因组编辑；为此，我们将开发并应用编辑策略 原代 T 细胞，对 DNA 进行测序以确认所需编辑的存在，并获得 RNA 和 ATAC 测序数据以了解编辑的影响并确认非 编码等位基因。