Predictive multiscale modeling of atrial fibrillation for therapy development

描述(申请人提供)：房颤(房颤)是美国和其他发达国家最常见的持续性心律失常，具有严重的发病率和死亡率。由于房颤有多个变异体，是多因素的，并且随着时间的推移而演变，在大型动物模型中进行全面的研究是非常困难和昂贵的，部分原因是在活体成像全心房电生理学的固有技术困难。预测性多尺度计算建模有可能填补这一研究空白。虽然我们和其他人已经对房颤进行了一些早期的多尺度建模，但如果有一个系统的建模框架来阐明这种复杂疾病的许多方面，社区将受益匪浅。该项目的总体目标是开发一个多尺度建模框架，以便能够评估潜在的药物和基于设备的心房颤动治疗。除了开发这样的建模系统，作为其治疗设计效用的概念验证，我们将收集和利用细胞电生理学数据来预测在存在常见的人类离子通道多态性的情况下，药物在控制阵发性、持续性和慢性房颤方面的有效性。具体来说，我们的目标是：1.开发一个简单、可扩展的框架，能够对人体心房进行建模。2.建立反映房颤多种状态的多尺度房颤模型。3.获得常见离子通道基因多态性对药物-通道相互作用影响的电生理数据。4.在含有离子通道基因多态性的真实心房模型(S)中预测药物对房颤的控制效果。这个项目将产生一个可扩展的、开源的房颤建模框架，它不仅有助于测试离子通道多态背景下的特定药理疗效问题，而且对于整个建模社区调查围绕房颤及其治疗的大量问题也是有用的。 公共卫生相关性：(用不超过两到三句话描述这项研究与公共卫生的相关性。)房颤是美国和其他发达国家最常见的持续性心律失常，具有严重的死亡率和发病率。由于在大型动物模型中全面研究房颤是非常困难和昂贵的，因此一个系统的计算建模框架将使研究界受益良多，以阐明这一复杂疾病的许多方面。这个项目的总体目标是开发这样一个多尺度建模框架，它将能够评估潜在的药物和基于设备的心房颤动治疗。

DESCRIPTION (provided by applicant): Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in the United States and the rest of the developed world, and has serious morbidity and mortality. Because AF has several variants, is multi- factorial, and evolves over time, it is very difficult and expensive to study comprehensively in large-animal models, in part due to the inherent technical difficulties of imaging whole-atria electrophysiology in vivo. Predictive multiscale computational modeling has the potential to fill this research void. While we and others have performed some early-stage multiscale modeling of AF, the community would benefit greatly from a systematic modeling framework with which to illuminate the many facets of this complex disorder. The overall goal of this project is to develop a multiscale modeling framework that will enable the evaluation of potential pharmacological and device-based atrial fibrillation therapies. In addition to developing such a modeling system, as a proof-of-concept of its therapy-design utility we will collect and utilize cellular electrophysiological data to predict the efficacy of pharmacological agents at controlling paroxysmal, persistent, and chronic AF in the presence of common human ion-channel polymorphisms. Specifically, we aim: 1. To develop a straightforward, extensible framework capable of modeling the human atria. 2. To implement a multiscale model of atrial fibrillation representing the multiple states of the disorder. 3. To acquire electrophysiological data of the impact of common ion channel gene polymorphisms on drug- channel interactions. 4. To predict pharmacological AF control efficacy in the realistic atrial model(s) with incorporated ion channel gene polymorphisms. This project will produce an extensible, open-source atrial fibrillation modeling framework that will be useful not only to test the specific question of pharmacological efficacy in the context of ion channel polymorphisms, but also for the modeling community at large to investigate the vast array of issues surrounding atrial fibrillation and its therapy. PUBLIC HEALTH RELEVANCE: (Using no more than two or three sentences, describe the relevance of this research to public health.) Atrial fibrillation is the most common sustained cardiac arrhythmia in the United States and the rest of the developed world, and has serious mortality and morbidity. Because atrial fibrillation is very difficult and expensive to study comprehensively in large-animal models, the research community would benefit greatly from a systematic computational modeling framework with which to illuminate the many facets of this complex disorder. The overall goal of this project is to develop such a multiscale modeling framework, which will enable the evaluation of potential pharmacological and device-based atrial fibrillation therapies.