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.

摘要 我们的目标是将遗传学领域应用于幼年特发性关节炎（JIA）， 识别遗传关联，并对遗传变异如何发挥作用的机制性理解 风险影响。我们将完成该领域目前面临的两项主要任务：（1）确定 产生生物学效应的变异体（“致病变异体”）;（2）基因鉴定 其表达水平被这些变体（“靶基因”）改变。为了实现这些目标， 我们还将阐明这些变异改变基因表达和细胞的机制， 功能协调发展的 GWAS对许多复杂性状的惊人发现之一，包括风湿性疾病，如 JIA是疾病相关遗传变异在非编码基因组中出现的频率。作为 在其他复杂性状中，JIA遗传风险位点高度富集H3 K4 me 1/H3 K27组蛋白标记， 通常与增强子功能相关的表观遗传特征。这一发现导致了一种假设， 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。在本申请中，我们专注于CD 4 + T细胞，我们的初步数据 这些细胞可能受到JIA中致病性遗传变异的影响。 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患儿CD 4 + T细胞中的数量性状基因座（hQTL），即，基因变异的区域 与H3 K4 me 1/H3 K27 ac切割-运行测序上的读取深度差异相关。我们将使用 与我们的合作研究者Gaffney博士以前在研究中使用的方法相同。 系统性狼疮的遗传学然后，我们将确定hQTL中改变DNA拓扑结构的变体， 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 大规模平行报告基因测定（MPRA）以鉴定hQTL内具有显著差异的那些变体。 影响基因表达。 在目标2中，我们将确定JIA风险单倍型中的靶基因。这些的基本前提是 研究表明，尽管因果变异可能不会影响最近的基因，但大多数相关基因都是由基因突变引起的。 相互作用将发生在相同的拓扑关联域（TADs）内。使用立即生产数据 我们在Aim 1中生成的数据以及H3 K27 ac HiChIP数据，并由我们发表的CTCF补充 ChIPseq/HiChIP数据，我们将确定风险单倍型上H3 K27 ac标记区域之间的相互作用 和基因启动子，集中在CTCF锚定的TADs内的那些。3D染色质的知识 结构、患者基因型和RNAseq数据将使我们能够识别变异体的可能靶基因， 风险单倍型。