Deciphering the role of noncoding variation in the pathogenesis of multiple sclerosis

解读非编码变异在多发性硬化症发病机制中的作用

• 批准号: 10450807
• 负责人: Maria Ciofani
• 金额: $ 61.86万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10450807
• 关键词: Antigens; Autoimmunity; Automobile Driving; Binding; Bioinformatics; Biological Assay; Brain; CD4 Positive T Lymphocytes; CRISPR/Cas technology; Cell physiology; Cells; Cerebrospinal Fluid; Chromatin; Chromatin Loop; Chronic; Clinic; Clinical; Core Facility; Data; Demyelinations; Development; Disease; Disease susceptibility; Elements; Enhancers; Environmental Risk Factor; Epigenetic Process; Etiology; Experimental Autoimmune Encephalomyelitis; Explosion; Functional disorder; Gene Expression Profile; Gene Expression Regulation; Gene Targeting; Genes; Genetic; Genetic Variation; Genome; Genomic approach; Genomics; Genotype; Glean; Goals; Human; Immune system; Immunologist; In Vitro; Inflammatory; Institutes; Knowledge; Link; Machine Learning; Maps; Mediating; Methods; Modeling; Molecular; Molecular Conformation; Multiple Sclerosis; Mus; Myelin; Neuraxis; Neurology; Nucleic Acid Regulatory Sequences; Pathogenesis; Pathogenicity; Patients; Phenotype; Physiological; Physiology; Regulator Genes; Regulatory Element; Reporter; Research Personnel; Risk; Role; Sampling; Scientist; Specialist; Spinal Cord; T cell response; T-Lymphocyte; T-Lymphocyte Subsets; Technology; Th1 Cells; Therapeutic Intervention; Transcriptional Regulation; Untranslated RNA; Variant; Work; analytical method; base; causal variant; disorder risk; epigenome editing; experimental study; gene therapy; genetic variant; genome wide association study; in vivo; insight; machine learning prediction; mouse model; multiple omics; multiple sclerosis patient; neuroimmunology; neuroinflammation; novel; promoter; risk variant; stem; transcription factor

Project Summary Multiple sclerosis (MS) is a chronic, inflammatory condition of the brain and spinal cord mediated largely by pathogenic T cell responses to myelin antigens, resulting in demyelination of the central nervous system (CNS). Myelin-reactive T cells are also crucial for induction of the experimental autoimmune encephalomyelitis (EAE) mouse model of MS. Studies of MS and EAE implicate CD4 T helper (Th) cells in disease pathogenesis, including pro-inflammatory Th17 and Th1 cells. In this regard, the disease-promoting ability of these T cell subsets stems from both their capacity to target and infiltrate the CNS and their pro-inflammatory effector function. An interplay between genetic and environmental factors is implicated in the pathogenesis of MS. However, despite a wealth of genome wide association data (GWAS) data revealing a strong genetic contribution to MS, it has been challenging to identify the bona fide disease-promoting gene target(s) of many risk-associated variants, and the cellular compartment in which they contribute to dysregulation. In preliminary work, we have applied global genomics approaches to map MS-associated noncoding risk variants to their long-range target gene by physically capturing enhancer-promoter interactions. These MS-implicated genes were further prioritized based on dysregulated expression signatures in pathogenic Th17 cells derived from MS patients. Using this approach, we have identified putative regulatory MS variants and gene targets that control CD4 T cell function in MS that are the basis of this application. We hypothesize that identifying noncoding variants that alter the regulatory function of cis elements controlling proinflammatory T cells will provide novel mechanistic insights into the underlying etiology governing the development of MS. Here, we propose an integrative strategy to prioritize and validate causal genetic variants in MS pathogenesis. The goal of Aim 1 is to determine the contribution of noncoding risk variants to CD4 T cell gene regulation. In particular, we will employ a combination of high-throughput regulatory reporter assays and machine learning approaches to identify SNPs with regulatory function in primary human CD4 T cells. In Aim 2, we will determine the mechanism by which these regulatory variants contribute to altered T cell function and pathogenicity in MS. Complementary CRISPR/Cas9-mediated genetic and epigenetic perturbations will define the enhancer context of risk alleles and delineate bona fide regulatory gene targets of regulatory risk variants. Moving from genotype to phenotype, we will define true causal variants that contribute to disease etiology in the context of an intact immune system using genetic interventions that model conserved risk variants in mice. Together, the proposed experiments will advance our understanding of the both the genetic and cellular mechanisms governing Th17 cell pathogenicity in MS and discover new loci with unknown functions in disease etiology.

项目摘要 多发性硬化症（MS）是大脑的慢性炎症状况，脊髓和脊髓很大程度上介导 致病性T细胞对髓磷脂抗原的反应，导致中枢神经系统脱髓鞘 （CNS）。髓磷脂反应性T细胞对于诱导实验性自身免疫性脑脊髓炎也至关重要 （EA）MS的鼠标模型。 MS和EAE的研究暗示CD4 T助手（Th）细胞在疾病发病机理中， 包括促炎性Th17和Th1细胞。在这方面，这些T细胞的促进疾病能力 子集源于其靶向和渗透中枢神经系统的能力及其促炎效应器 功能。遗传因素与环境因素之间的相互作用与MS的发病机理有关。 但是，尽管大量基因组广泛的关联数据（GWAS）数据揭示了强大的遗传 对MS的贡献，确定许多促进疾病的基因靶标的是挑战 风险相关的变体以及它们导致失调的细胞室。在初步 工作，我们应用了全球基因组学方法，以将MS相关的非编码风险变体映射到其 远程靶基因通过物理捕获增强子促销相互作用。这些MS刺激性基因 基于衍生自MS的致病性TH17细胞中的表达信号进一步优先考虑 患者。使用这种方法，我们已经确定了控制的推定调节性MS变体和基因靶标 MS中的CD4 T细胞功能是本应用程序的基础。我们假设识别非编码 改变控制促炎T细胞的顺式元件调节功能的变体将提供新颖的 对管理MS发展的基本病因的机械洞察。在这里，我们建议 在MS发病机理中优先级和验证因果遗传变异的综合策略。目标1的目标是 确定非编码风险变异对CD4 T细胞基因调控的贡献。特别是，我们会 采用高通量监管记者测定法和机器学习方法的组合 在原代人CD4 T细胞中识别具有调节功能的SNP。在AIM 2中，我们将确定 这些调节变体有助于MS中T细胞功能和致病性改变的机制。 互补的CRISPR/CAS9介导的遗传和表观遗传扰动将定义增强子环境 风险等位基因和划定调节风险变体的真正调节基因靶标。从基因型移动 对于表型，我们将定义真正的因果变异，这些变异在完整的背景下导致病因 免疫系统使用遗传干预措施模拟小鼠中保存风险变异的影响。一起，提议 实验将提高我们对控制TH17的遗传和细胞机制的理解 MS中的细胞致病性，发现具有疾病病因的未知功能的新基因座。