Defining the functional variation underlying atrial fibrillation risk

定义心房颤动风险的功能变异

• 批准号: 9930154
• 负责人: Nathan Tucker
• 金额: $ 16.74万
• 依托单位: MASONIC MEDICAL RESEARCH LABORATORY, INC
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-15 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9930154
• 关键词: Address; Adult; Affect; Age; Alleles; Allelic Imbalance; American; Appointment; Arrhythmia; Atrial Fibrillation; Bioinformatics; Biological Assay; Cardiovascular Diseases; Cardiovascular system; Cells; Cellular biology; Cessation of life; ChIP-seq; Chromatin; Clinical; Clinical Treatment; Complex Genetic Trait; Computational Biology; Data; Dementia; Development; Disease; Enhancers; Epigenetic Process; Foundations; Gene Expression; Gene Targeting; General Hospitals; Genes; Genetic; Genetic Risk; Genetic Variation; Genome; Genomics; Genotype; Goals; Graduate Education; Healthcare Systems; Heart Atrium; Heart failure; Heritability; Histones; Hospitalization; Human; In Situ Hybridization; Individual; Interdisciplinary Study; Intervention; Knowledge; Lead; Left; Left atrial structure; Link; Maps; Massachusetts; Measurement; Medicine; Mentors; Modeling; Molecular Biology; Morbidity - disease rate; Pathogenesis; Pathway interactions; Population; Post-Translational Protein Processing; Predisposition; Preventive care; Publishing; Pulmonary veins; Regulatory Element; Reporter; Research; Research Personnel; Risk; Risk Factors; Signal Transduction; Stimulus; Striated Muscles; Stroke; Tissue Banks; Universities; Untranslated RNA; Variant; Washington; Work; base; career; causal variant; clinical risk; cost; disorder risk; epigenomics; experimental study; functional genomics; gene function; genetic association; genome sequencing; genome wide association study; genomic locus; human disease; improved; insight; instructor; interest; medical schools; molecular modeling; mortality; new therapeutic target; novel therapeutic intervention; novel therapeutics; post-doctoral training; risk prediction; risk variant; skills; societal costs; sound; systems research; trait; transcriptome sequencing; treatment planning

Project Summary: Atrial fibrillation (AF) is the most common cardiac arrhythmia, which affects over 3 million Americans. AF confers an increased risk of hospitalization, stroke, dementia, heart failure and death and places a major burden on the healthcare system. AF, particularly in younger individuals, arises from the ectopic stimuli within the pulmonary veins with propagation to left atrium; however, many other aspects of the underlying mechanisms for AF remain unresolved. Although many clinical risk factors have been identified, in recent years we have come to appreciate that AF is heritable. A proportion of this heritability is conferred through common genetic variation. Using, genome-wide association studies (GWAS), our group and others have identified 26 independent genetic loci for AF. These loci can provide a unique and often unexpected window into the mechanisms of disease; however, as with other GWAS studies, a primary challenge is moving from an association to a specific disease mechanism. There are at least three major challenges that make it difficult to link a genetic association to a specific disease mechanism. First, GWAS loci often reside in gene-dense regions, making it difficult to identify which gene is associated with disease. Second, the overwhelming majority of GWAS loci reside in non-coding regions of the genome. The disease risk variants are presumed to alter the activity of regulatory elements that modulate nearby gene expression in a cell-specific manner. Finally, these GWAS loci can be large, and it can be challenge to identify the functional variant from among the many common variants at a locus. Given these challenges, the truly causative variants and the gene of interest are unknown for most GWAS loci. This knowledge gap greatly impedes the ability to leverage GWAS data for translational potential, as any modeling of gene function at these loci would be speculative. These issues are not exclusive to AF, instead pertaining not only to similar studies across other cardiovascular diseases and traits, but also the thousands of GWAS loci in the full spectrum of human diseases and traits uncovered in the past decade. The focus of the current proposal is to address these knowledge gaps for AF GWAS loci, with the ultimate goal of applying new insights to other cardiovascular disease loci. Given the genomic localization of most GWAS signals, this proposal operates under the overarching hypothesis that non-coding variation at AF- association loci alters gene expression in adult human left atrium, ultimately leading to AF susceptibility. We propose to leverage the genome sequencing based association data and our left atrial tissue repository for epigenetic definition and functional variant discovery. We will then use the same genotype information to identify the gene targets of each association locus.

项目概要： 心房颤动 (AF) 是最常见的心律失常，影响超过 300 万美国人。 AF 导致住院、中风、痴呆、心力衰竭和死亡的风险增加，并导致重大 医疗保健系统的负担。房颤，尤其是年轻人，是由体内的异位刺激引起的。 肺静脉传播至左心房；然而，基础的许多其他方面 AF 的机制仍未解决。尽管许多临床危险因素已被确定，但近年来 我们逐渐意识到 AF 是可遗传的。 这种遗传力的一部分是通过共同的遗传变异赋予的。使用，全基因组 通过关联研究（GWAS），我们小组和其他人已经确定了 26 个独立的 AF 基因位点。这些 位点可以为了解疾病机制提供一个独特且常常意想不到的窗口；然而，正如 在其他 GWAS 研究中，主要挑战是从关联转向特定疾病机制。 至少存在三个主要挑战使得将遗传关联与特定的联系起来变得困难。 发病机制。首先，GWAS 基因座通常位于基因密集区域，因此很难识别哪些基因座 基因与疾病有关。其次，绝大多数 GWAS 位点位于非编码区域 基因组的区域。据推测，疾病风险变异会改变调节元件的活性， 以细胞特异性的方式调节附近的基因表达。最后，这些 GWAS 位点可能很大，而且可以 从一个基因座的许多常见变异中识别功能变异是一项挑战。 考虑到这些挑战，对于大多数 GWAS 来说，真正的致病变异和感兴趣的基因都是未知的 基因座。这种知识差距极大地阻碍了利用 GWAS 数据实现转化潜力的能力，因为任何 对这些位点的基因功能进行建模是推测性的。这些问题并非 AF 独有，而是 不仅涉及其他心血管疾病和特征的类似研究，还涉及数千个 过去十年发现的全谱人类疾病和性状中的 GWAS 位点。 当前提案的重点是解决 AF GWAS 位点的知识差距，最终解决 将新见解应用于其他心血管疾病基因座的目标。鉴于大多数基因组定位 GWAS 表示，该提案的总体假设是 AF- 的非编码变异 关联位点改变成人左心房的基因表达，最终导致房颤易感性。我们 建议利用基于基因组测序的关联数据和我们的左心房组织存储库 表观遗传学定义和功能变异发现。然后我们将使用相同的基因型信息 识别每个关联位点的基因靶标。