From Variants to Mechanisms for Cardiac Arrhythmias

从心律失常的变异到机制

• 批准号: 10719850
• 负责人: Nathan Tucker
• 金额: $ 82.56万
• 依托单位: MASONIC MEDICAL RESEARCH LABORATORY, INC
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10719850
• 关键词: Address; American; Anatomy; Architecture; Area; Arrhythmia; Atrial Fibrillation; Biological Assay; Biology; CRISPR/Cas technology; Calcium; Candidate Disease Gene; Cardiac; Cardiac Myocytes; Cardiology; Cell model; Cell physiology; Chromatin; Chromatin Loop; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Code; Companions; Complement; Data; Diagnostic; Disease; Electrophysiology (science); Enhancers; Event; Follow-Up Studies; Gene Expression; Gene Proteins; Gene Targeting; Genes; Genetic; Genetic Risk; Genetic Transcription; Genomics; Genotype; Goals; Heart; Heart Atrium; Heritability; Hi-C; Human; Individual; Knowledge; Lateral; Left; Link; Location; Maps; Measurement; Measures; Membrane Potentials; Metadata; Modeling; Molecular Conformation; Nature; Pathology; Pathway interactions; Physical assessment; Physiology; Positioning Attribute; Proteins; Publishing; Quality of life; Quantitative Trait Loci; Regulator Genes; Regulatory Element; Repression; Resolution; Retrospective cohort; Risk; Sampling; System; Technology; Therapeutic; Time; Tissue Sample; Tissues; Transcriptional Regulation; Translational Research; Validation; Variant; ZFHX3 gene; biobank; candidate identification; cell type; clinical practice; cohort; detection limit; disorder risk; evidence base; expectation; experience; follow-up; genetic association; genetic variant; genome wide association study; genome-wide analysis; genomic locus; human stem cells; human tissue; improved; mortality risk; novel therapeutic intervention; novel therapeutics; power analysis; promoter; prospective; risk variant; single nucleus RNA-sequencing; success; therapeutic development; trait; transcription factor; transcriptome sequencing; translational potential; translational therapeutics; virtual; whole genome

Project summary There are hundreds of genomic loci where common genetic variants associate with the risk of cardiac arrhythmias, yet the slow rate of functional assessment severely limits our ability to unlock the unique biology that they identify. Our long-term goal is to systematically link arrhythmia risk loci to their mechanisms, identifying the unexpected mechanisms of arrhythmogenesis, and priming them for therapeutic translation. The key feature of arrhythmia genetic association loci is their non-protein-coding nature, a finding which leads to our overarching hypothesis that transcriptional misregulation underlies much of cardiac arrhythmia risk. To address this hypothesis, we first examine the relationships between known arrhythmia target genes which encode transcription factors and cardiomyocyte electrophysiology using inducible CRISPR-Cas9 modifiers of gene expression. We will seek to understand the transcriptional changes underlying electrophysiological changes by profiling gene expression and protein abundance. At the same time, we recognize that the vast majority of loci remain entirely undefined, a limitation which serves as a great impediment to further translational research. To address this, we will use two orthogonal approaches in human atrial tissue samples. First, our group has led early large-scale implementations of single nucleus RNA sequencing on the human heart, experience which we propose to extend to the goals of this proposal. We aim to link genotype to expression by performing single nucleus RNA sequencing on a large biobank of non-diseased left atrial tissue with available genotypes and clinical metadata. This will provide not only the target gene(s) for the association loci, but also the directionality of effect and the pertinent cell type(s), greatly facilitating downstream validation by our team and others. To complement the direct measurement of genotype to expression, we aim to supplement these analyses with chromatin conformation analysis. While these assays do not resolve the effects of genotype, they measure contact between regions of risk and target promoters to provide putative gene targets. Our preliminary high- resolution contact map from the left atrial lateral wall greatly improved the number of candidate genes for atrial fibrillation association loci. We recognize the importance of anatomically restricted events in the initiation and propagation of arrhythmias, and thus propose to assess the physical proximity between regulatory elements within association loci and their putative gene targets in prospectively sampled atrial tissues using micro-C, a technology which assesses chromatin conformation across the entire genome. Ultimately, accomplishing these aims could prove transformative for facilitating studies of cardiac arrhythmias, unlocking the mechanisms of arrhythmia genetic risk to generate novel therapeutic approaches and guide clinical practices.

项目摘要 有数百个基因组位点，其中常见的遗传变异与心脏病的风险相关。 然而，缓慢的功能评估速度严重限制了我们解锁独特生物学的能力。 他们识别。我们的长期目标是系统地将心律失常风险位点与其机制联系起来， 肿瘤发生的意外机制，并启动它们用于治疗翻译。该关键特征 心律失常遗传关联基因座的一个重要特征是它们的非蛋白质编码性质，这一发现导致了我们对心律失常遗传关联基因座的总体研究。 转录失调是心律失常风险的基础。为了解决这个 假设，我们首先检查已知的心律失常靶基因之间的关系， 使用基因的可诱导CRISPR-Cas9修饰剂的转录因子和心肌细胞电生理学 表情我们将通过以下方法来了解电生理变化背后的转录变化： 分析基因表达和蛋白质丰度。与此同时，我们认识到， 仍然是完全不确定的，这是一个限制，作为一个巨大的障碍，进一步的翻译研究。到 为了解决这个问题，我们将在人心房组织样本中使用两种正交方法。首先，我们的团队 在人类心脏上进行单核RNA测序的早期大规模实施， 建议扩展到本提案的目标。我们的目标是通过执行单一的基因型与表达之间的联系， 对具有可用基因型的非患病左心房组织的大型生物库进行核RNA测序， 临床元数据这将不仅为关联位点提供靶基因，而且还提供方向性。 的效果和相关的细胞类型，极大地促进了我们的团队和其他人的下游验证。到 补充基因型表达的直接测量，我们的目标是补充这些分析， 染色质构象分析虽然这些测定不能解决基因型的影响，但它们测量了 风险区域和靶启动子之间的接触，以提供推定的基因靶。我们初步的高- 从左心房侧壁的分辨率接触图大大提高了心房肌的候选基因的数量， 纤颤相关基因座我们认识到在开始阶段解剖学上的限制事件的重要性， 传播的心律失常，因此建议评估之间的物理接近的调节元件 在使用micro-C的前瞻性心房组织样本中， 这项技术可以评估整个基因组的染色质构象。最终，实现这些 目的可以证明是促进心律失常研究的变革， 心律失常遗传风险产生新的治疗方法和指导临床实践。