Multiomics and Functional Characterization Establish Druggable Targets for PVC-Driven Idiopathic VF

多组学和功能表征为 PVC 驱动的特发性心室颤动建立药物靶标

• 批准号: 10750784
• 负责人: Lee Lochbaum Eckhardt
• 金额: $ 79.06万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10750784
• 关键词: Address; Adult; Algorithms; Anti-Arrhythmia Agents; Arrhythmia; Biological Markers; Biological Models; Candidate Disease Gene; Cardiac; Cardiac Myocytes; Cause of Death; Cells; Clinical; Clinical Management; Clinical Practice Guideline; Coculture Techniques; Collaborations; Complex; Computer Analysis; Computer Models; Cues; Data; Data Set; Diagnosis; Diagnostic; Disease; Electrocardiogram; Electrophysiology (science); Etiology; Event; Exclusion; Exhibits; Fibroblasts; Functional disorder; Gene Expression; Gene Expression Profile; Genetic; Genotype; Goals; Heart; Heart Diseases; Individual; Intervention; Ion Channel; Knowledge; Label; Maps; Modeling; Morbidity - disease rate; Morphology; Muscle Cells; Myofibrils; Optics; Output; Pathologic; Pathway interactions; Patients; Pattern; Pharmacology; Phenotype; Population; Post-Translational Protein Processing; Prevention; Proteomics; Purkinje Cells; Regulation; Signal Transduction; Structure; Syndrome; System; Testing; Tissues; Transcript; Translating; United States; Use Effectiveness; Ventricular; Ventricular Fibrillation; Ventricular Premature Complexes; cellular targeting; cohort; data integration; design; diagnostic criteria; druggable target; experimental study; genetic architecture; genetic linkage; genetic variant; genome sequencing; hazard; in silico; in vivo; induced pluripotent stem cell; ineffective therapies; innovation; insight; mortality; multiple omics; nanoscale; new therapeutic target; optimal treatments; predicting response; protein expression; recruit; risk stratification; sudden cardiac death; targeted treatment; therapeutic target; transcription factor; transcriptome; variant of unknown significance; whole genome

PROJECT ABSTRACT Sudden cardiac death (SCD) claims >300,000 lives yearly in the US and despite aggressive attempts at phenotype-genotype correlations, ~50% of patients with primary electrical SCD do not meet diagnostic criteria for any SCD syndrome and are labeled Idiopathic Ventricular Fibrillation (IVF). This “catch-all” diagnosis of exclusion encompasses a cohort of individuals that are undefined phenotypically with arrhythmia that is mechanistically unexplored. Moreover, without defined genotype-phenotype characterization, clinical practice guidelines for IVF suggest homogenous treatment for a heterogenous disorder. Recognizing that genetic linkage studies have failed for IVF, we propose a paradigm shift to address these challenging gaps in knowledge. We propose to integrate computational modeling of comprehensive electrophysiologic and multiomic outputs to identify the mechanistic underpinnings of an emerging IVF subphenotype related to Purkinje-triggered VF (PVC- IVF). In collaboration with the Bordeaux group Deep Phenotype efforts, who originally described these emerging subphenotypes of IVF, PVC-IVF patients have been recruited to create induced pluripotent stem cells (iPSCs) from UW and Bordeaux. Our iPSC experimental system has distinct advantages including integration of PVC- IVF iPS-cardiomyocytes (iPS-CMs) with a mixed (ventricular myocyte and Purkinje) cell population with computational myocyte models reflecting region-specific phenotypes. Our group’s design for iPSCs experiments combine innovation of platforms that promote electrical and functional maturity, including incorporation of iPS- cardiac fibroblasts (iPS-CFs), and analysis by computational modeling of iPS-CMs and in silico adult human myocytes and tissue. In our pilot data we demonstrate the effectiveness of using iPSCs to differentiate IVF with experimental evidence and integrate this data into computational modeling approaches to gain mechanistic insight into cellular arrhythmic perturbations. Our overarching goal is to examine the mechanistic underpinning of PVC-IVF and identify specific complementary and synergistic therapeutic targets. In Aim 1 we will integrate experimental functional readouts from our advanced model system designed to recapitulate native cardiac milieu with a combination of micro and nanoscale cues with “bottom-up” computational modeling to unravel the specific cellular perturbations that cause the observed functional PVC-IVF readout. The focus of Aim 2 is to incorporate a broad, unbiased data-driven dataset from multiomic characterization of PVC-IVF patient-specific iPS-CMs into a computational systems pharmacology framework to define synergistic arrhythmogenic pathways and antiarrhythmic polytherapy, which we predict to be safer and more effective than monotherapy approaches. Finally, computational cross-cell translators will predict responses in the adult heart. With completion of our aims, we will define the cellular arrhythmic signature; unravel the down-stream transcriptome, protein expression changes and post-translational modifications; and integrate experimental readouts with computational modeling to create actionable data and find druggable targets for PVC-IVF arrhythmia prevention.

项目摘要 在美国，心脏性猝死（SCD）每年夺去超过30万人的生命， 表型-基因型相关性，约50%的原发性电气SCD患者不符合诊断标准 任何SCD综合征，并标记为特发性心室颤动（IVF）。这种“包罗万象”的诊断 排除包括一组表型不明确的心律失常个体， 未被探索的机械。此外，在没有明确的基因型-表型表征的情况下， IVF的指导方针建议对异质性疾病进行同质治疗。认识到遗传联系 尽管IVF的研究失败了，但我们提出了一种范式转变，以解决这些具有挑战性的知识差距。我们 建议整合综合电生理和多组输出的计算建模， 确定与浦肯野触发VF（PVC-1）相关的新出现的IVF亚表型的机制基础。 IVF）。与波尔多Deep Phenotype小组合作，该小组最初描述了这些新出现的现象 体外受精的亚表型，PVC-IVF患者已被招募来创建诱导多能干细胞（iPSC） 来自华盛顿大学和波尔多。我们的iPSC实验系统具有明显的优势，包括PVC- IVF iPS-心肌细胞（iPS-CM）与混合（心室肌细胞和浦肯野）细胞群， 反映区域特异性表型的计算肌细胞模型。我们小组的iPSCs实验设计 联合收割机平台创新，促进电气和功能成熟度，包括整合iPS- 心脏成纤维细胞（iPS-CF），并通过iPS-CM和计算机模拟成年人的计算建模进行分析 肌细胞和组织。在我们的试点数据中，我们证明了使用iPSC区分IVF与IVF的有效性。 实验证据，并将这些数据整合到计算建模方法中，以获得机械 对细胞代谢紊乱的深入了解我们的首要目标是研究 的PVC-IVF，并确定特定的互补和协同治疗目标。在目标1中，我们将 来自我们的先进模型系统的实验功能读数，该系统旨在重现天然心脏环境 结合微观和纳米尺度的线索与“自下而上”的计算建模， 导致观察到的功能性PVC-IVF读数的细胞扰动。目标2的重点是将 从PVC-IVF患者特异性iPS-CM的多组学表征到 一个计算系统药理学框架，以定义协同促癌途径， 抗肿瘤多药治疗，我们预测这是更安全和更有效的单药治疗方法。 最后，计算跨细胞翻译器将预测成人心脏的反应。随着我们目标的完成， 我们将定义细胞的代谢特征，解开下游转录组，蛋白质表达， 变化和翻译后修饰;并将实验读数与计算建模相结合 为PVC-IVF心律失常预防创建可操作的数据并找到可药物化的目标。