Epigenetic Mechanisms That Drive Genetic Risk in Juvenile Arthritis

导致幼年关节炎遗传风险的表观遗传机制

• 批准号: 10710032
• 负责人: JAMES N JARVIS
• 金额: $ 63.11万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-26 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710032
• 关键词: 3-Dimensional; ATAC-seq; Address; Affect; Alleles; Allelic Imbalance; Autoimmune Diseases; Bioinformatics; Biological; Biological Assay; Blood Cells; CD4 Positive T Lymphocytes; Cell physiology; Cells; ChIP-seq; Child; Childhood; Chromatin; Chromatin Structure; Chronic Childhood Arthritis; Chronic Disease; Clinical; Complex; DNA; DNA Resequencing; Data; Disease; Elements; Enhancers; Epigenetic Process; Frequencies; Gene Expression; Genes; Genetic; Genetic Diseases; Genetic Risk; Genetic Transcription; Genome; Genotype; Haplotypes; Histones; In Vitro; Influentials; Investigation; Knowledge; Laboratories; Link; Linkage Disequilibrium; Lupus; Maps; Methods; Pathologic; Patients; Phenotype; Process; Property; Publishing; Quantitative Trait Loci; Reporter; Reporter Genes; Research Personnel; Rheumatism; Risk; Role; Signal Transduction; Testing; Transactivation; Untranslated RNA; Variant; causal variant; chromatin modification; disease phenotype; disorder risk; epigenome; gene interaction; genetic association; genetic variant; genome wide association study; genotyped patients; improved outcome; in silico; innovation; insight; novel therapeutics; nuclease; permissiveness; promoter; risk variant; therapy outcome; tool; trait; transcriptome sequencing

Abstract We aim to move the field of genetics as applied to juvenile idiopathic arthritis (JIA) away from the identification of genetic associations and toward a mechanistic understanding of how genetic variants exert risk-conferring effects. We will accomplish two major tasks now facing the field: (1) identification of the variants that exert the biological effects that confer risk (the “causal variants”); (2) identification of the genes whose expression levels are altered by those variants (the “target genes”). In accomplishing these aims, we will also elucidate mechanisms through which those variants alter gene expression and cellular functions. One of the striking findings from GWAS for many complex traits, including rheumatic diseases such as JIA, is the frequency with which disease-associated genetic variants appear in the non-coding genome. As in other complex traits, the JIA genetic risk loci are highly enriched for H3K4me1/H3K27histone marks, epigenetic signatures frequently associated with enhancer function. This finding has led to the hypothesis that genetic risk in JIA impinges on enhancer function, leading to transcriptional abnormalities that can be observed in peripheral blood cells. In this application, we focus on CD4+ T cells, which our preliminary data suggest are among the cells likely to be impacted by causal genetic variants in JIA. In Aim 1, we will identify causal variants based on distinct biological properties. We will identify histone quantitative trait loci (hQTLs) in CD4+ T cells of children with JIA, i.e., regions where genetic variants are associated with differences in read depth on H3K4me1/H3K27ac Cut-and-Run sequencing. We will use the same approach as that previously used by our co-investigator, Dr. Gaffney, in his investigations into the genetics of systemic lupus. We will then identify the variants within the hQTLs that alter DNA topology, a critical determinant of regulatory function. Finally, from variants that pass both screens, we will use a massively parallel reporter assay (MPRA) to identify those variants within the hQTLs that have a significant influence on gene expression. In Aim 2, we will identify the target genes within the JIA risk haplotypes. The underlying premise of these studies is that, although the causal variants may not impact the nearest gene, the majority of relevant interactions will occur within the same topologically associated domains (TADs). Using Cut-and-Run data that we generate in Aim 1 as well as H3K27ac HiChIP data and supplemented by our published CTCF ChIPseq/HiChIP data, we will identify interactions between H3K27ac-marked regions on the risk haplotypes and gene promoters, focusing on those within CTCF-anchored TADs. Knowledge of the 3D chromatin structure, patient genotype, and RNAseq data will then allow us to identify the likely target genes of variants on the risk haplotypes.

抽象的 我们的目标是将应用于幼年特发性关节炎 (JIA) 的遗传学领域从 识别遗传关联并从机制上理解遗传变异如何发挥作用 带来风险的影响。我们将完成该领域目前面临的两项主要任务：（1）识别 产生带来风险的生物效应的变异（“因果变异”）； (2)基因的鉴定 其表达水平被这些变体（“目标基因”）改变。在实现这些目标的过程中， 我们还将阐明这些变异改变基因表达和细胞的机制 功能。 GWAS 对许多复杂特征的惊人发现之一，包括风湿病，例如 JIA 是非编码基因组中与疾病相关的遗传变异出现的频率。作为 在其他复杂性状中，JIA 遗传风险位点高度富集 H3K4me1/H3K27 组蛋白标记， 表观遗传特征通常与增强子功能相关。这一发现引出了以下假设 JIA 的遗传风险影响增强子功能，导致转录异常 在外周血细胞中观察到。在此应用中，我们重点关注 CD4+ T 细胞，我们的初步数据 表明这些细胞可能受到幼年特发性关节炎因果遗传变异的影响。 在目标 1 中，我们将根据不同的生物学特性识别因果变异。我们将鉴定组蛋白 JIA 儿童 CD4+ T 细胞中的数量性状位点 (hQTL)，即存在遗传变异的区域 与 H3K4me1/H3K27ac Cut-and Run 测序的读取深度差异相关。我们将使用 与我们的合作研究员加夫尼博士之前在研究中使用的方法相同 系统性狼疮的遗传学。然后我们将鉴定 hQTL 内改变 DNA 拓扑结构的变异， 调节功能的关键决定因素。最后，从通过两个屏幕的变体中，我们将使用 大规模平行报告分析 (MPRA) 来识别 hQTL 中具有显着差异的变异 对基因表达的影响。 在目标 2 中，我们将鉴定 JIA 风险单倍型中的目标基因。这些的基本前提 研究表明，虽然因果变异可能不会影响最近的基因，但大多数相关基因 交互将发生在相同的拓扑关联域（TAD）内。使用即切即运行数据 我们在 Aim 1 中生成以及 H3K27ac HiChIP 数据，并由我们发布的 CTCF 进行补充 ChIPseq/HiChIP 数据，我们将识别风险单倍型上 H3K27ac 标记区域之间的相互作用 和基因启动子，重点关注 CTCF 锚定的 TAD 内的启动子。 3D 染色质知识 结构、患者基因型和 RNAseq 数据将使我们能够识别变异的可能目标基因 关于风险单倍型。