Development of a Hypertrophic Cardiomyopathy Consortium

描述（由申请人提供）：肥厚性心肌病（HCM）是世界上最常见的遗传性心血管疾病，发病率为1 / 500。它也是年轻人猝死的最常见原因，并与心力衰竭、心律失常和死亡有关。常规捕获的与该疾病的主要或次要特征有关的临床信息（表现为心脏结构和/或功能的变化）可能允许识别有这些不良后果风险的患者。我们的总体目标是通过利用世界各地现有研究团体聚集的大量具有良好特征的HCM人群的力量，研究HCM临床重要结果的潜在新预测因素。因此，我们的具体目标是：1)确定非同步化运动在预测HCM心衰中的作用；2)确定心房颤动的预测因素；3)确定晕厥和心源性猝死的电生理预测因素。理想情况下，对这些问题的全面评估需要大量的、特征明确的、系统累积的、最好是多种族的HCM患者，并以明确的协议方式进行纵向随访。尽管这些研究人群在组织和地理上分散，科学目标不同，但几乎所有人都收集了有助于解决我们假设的关键临床和影像学信息。将这些实体结合在一起的挑战是多方面的，但主要与信息的数量和复杂性不容易进行集成和分析这一事实有关。合并来自多个研究项目的数据需要复杂而强大的计算和信息学工具，这些工具将允许收集、存储和分析不同形式的信息。本提案寻求与HCM患者群体合作合并几个大型，不同的研究社区，以利用CVRG提供的独特架构和工具来测试我们的假设。我们计划利用CVRG的专业知识和资源来建立一个数据共享基础设施，在这个基础设施中，参与的研究人员将以符合HIPAA的方式安全地将大量信息上传到一个公共平台上。随后，我们将应用现有的定制CVRG工具来管理和分析电生理和成像数据。我们将使用现有的横断面和纵向数据来确定电生理参数、心脏结构和功能是否单独或联合预测HCM患者的临床相关结果。

DESCRIPTION (provided by applicant): Hypertrophic cardiomyopathy (HCM) is the commonest inherited cardiovascular disorder occurring in 1 in 500 persons worldwide. It is also the commonest cause of sudden death in the young and is associated with heart failure, cardiac arrhythmias and death. It is likely that routinely captured clinical information pertaining to primary or secondary features of the disease, manifesting as changes in cardiac structure and/or function, may allow identification of patients at risk for these adverse outcomes. Our overall goal is to examine potential novel predictors of clinically important outcomes of HCM by leveraging the power of large numbers of well-characterized HCM population available in a conglomeration of existing research communities across the world. Accordingly, our specific aims are: 1) To determine the role of dyssynchrony in predicting heart failure in HCM; 2) To ascertain the predictors of atrial fibrillation and 3) To determine the electrophysiologic predictors of syncope and sudden cardiac death. A comprehensive evaluation of these issues would ideally require large, well- characterized, systematically accrued, and preferably multi-ethnic populations of patients with HCM that have been followed longitudinally in a well-defined protocolized fashion. Although such research populations are organizationally and geographically dispersed with dissimilar scientific goals, almost all collect key clinical and imaging information that could help address our hypothesis. The challenges in bringing such entities together are manifold but primarily related to the fact that the volume and complexity of information does not lend itself to easy integration and analyses. Merging data from multiple research programs requires sophisticated and powerful computational and informatics tools that will allow collection, storage and analyses of disparate forms of information. This proposal seeks to collaboratively amalgamate several large, distinct research communities with populations of HCM patients to test our hypotheses exploiting the unique architecture and tools offered by the CVRG. We plan to use the CVRG expertise and resources to establish a data sharing infrastructure wherein participating investigators will securely, and in a HIPAA compliant fashion, upload large volumes of information on to a common platform. Subsequently, we will apply existing custom CVRG tools for management and analyses of electrophysiology and imaging data. We will use existing cross-sectional and longitudinal data to ascertain if parameters of electrophysiology, cardiac structure and function, either singly or in combination, predict clinically relevant outcomes in HCM patients. PUBLIC HEALTH RELEVANCE: This project seeks to develop a clinical consortium of hypertrophic cardiomyopathy using the cardiovascular research grid with several participating centers from the United States, Europe and Asia. This consortium, a first of its kind, would allow pooling of clinical and imaging information thus creating a large database capable of answering critical clinical questions concerning the management of hypertrophic cardiomyopathy, a common genetic disorder, not otherwise possible with smaller, single institution volumes.