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.

项目摘要： 心房颤动（AF）是最常见的心律失常，影响了300万美国人。 AF 赋予住院，中风，痴呆，心力衰竭和死亡的风险增加 医疗保健系统负担。 AF，尤其是在年轻人中，来自内部的异位刺激 肺部静脉传播到左心房；但是，基础的许多其他方面 AF的机制仍未解决。尽管已经确定了许多临床风险因素，但近年来 我们已经意识到AF是可遗传的。 这种遗传力的一定比例是通过常见的遗传变异所赋予的。使用，全基因组 协会研究（GWAS），我们的小组和其他人已经确定了26个独立的遗传基因座。这些 基因座可以为疾病机理提供独特且经常出乎意料的窗口。但是，就像 其他GWAS研究，主要的挑战是从缔合转向特定的疾病机制。 至少有三个主要挑战使得很难将遗传关联与特定联系起来 疾病机制。首先，GWAS基因座经常居住在基因密集区域，使得难以识别哪个 基因与疾病有关。其次，绝大多数GWAS基因座都存在于非编码 基因组的区域。假定疾病风险变异是为了改变调节元素的活性 以细胞特异性方式调节附近的基因表达。最后，这些GWAS基因座可能很大，它可以 要挑战以确定位点上许多常见变体中的功能变体。 鉴于这些挑战，大多数GWAS的真正原因变体和感兴趣的基因是未知的 基因座。这种知识差距极大地阻碍了利用GWAS数据获得转化潜力的能力，因为 这些基因座基因功能的建模将是投机性的。这些问题不是AF独有的 不仅与其他心血管疾病和特征的类似研究有关，还与数千种有关 GWAS基因座在过去十年中发现的全部人类疾病和特质中。 当前建议的重点是解决AF GWAS基因座的这些知识差距 将新见解应用于其他心血管疾病基因座的目标。鉴于大多数的基因组定位 GWAS信号，该提案在总体假设下运行，即AF-的非编码变化 关联基因座改变了成年人类左心房中基因表达，最终导致AF敏感性。我们 提议利用基于基因组测序的关联数据，而我们的左心房组织存储库 表观遗传定义和功能变体发现。然后，我们将使用相同的基因型信息来 确定每个关联基因座的基因靶标。