Quantifying the role of myocyte ultrastructure in atrial health and disease

项目摘要：房颤(房颤)是最常见的心律失常(影响~1-2%的 (一般人口)，导致生活质量显著下降和死亡率增加，原因是 血流动力学改变，进行性房室功能障碍，以及栓塞性中风。许多疾病和 众所周知，心力衰竭等疾病会导致房颤的病理变化。当前的限制 由于广泛的心房结构，治疗允许房颤阵发进展为持续性和慢性房颤 以及便于房颤维护的电学变化(“房颤产生房颤”)。迫切需要的发展 房颤治疗的新策略取决于对细胞功能异常的更好理解 引发并维持心房组织的心律失常。在细胞水平上，许多慢性疾病的标志性结构变化 心脏疾病是耦合心脏电兴奋的复杂膜结构的退化。 细胞内钙离子释放和心肌收缩(EC偶联)--即横管(TT)结构， 其从电池表面垂直地突出到其内部，从而在整个过程中同步EC耦合 牢房。TT结构的退化通常与心律失常有关，但尚不清楚是否 TT丢失是心律失常的直接因素，是一种代偿性适应不良，或者是一种附带现象。这就扯平了 在心房中不太清楚，因为心房肌细胞表现出非常不同的TT构筑，轴向突出 小管。此外，分离心房肌细胞过程引起的TT降解(与完整的致密TT相比 组织)和在实验中拔除完整心脏组织的挑战到目前为止限制了设计 机械性肌细胞和组织研究。因此，围绕亚细胞结构的作用的文献 房颤的(超微结构)重构仍然是断裂的，目前我们对其在房颤中的作用知之甚少。 对房颤的病理生理学有贡献。这项提议的首要目标是区分变化的作用 在其他疾病相关后遗症的心房肌细胞超微结构中结合详细的多水平 兔心房肌细胞、兔和人心房组织的广泛定量实验分析 多尺度计算建模。该项目将开发和验证一套用于 探讨以下机制：(1)房室传导速度的自然变化影响EC偶联和 心房肌细胞膜的稳定性；(2)TT组织中的组织梯度影响组织水平 电生理和EC偶联的结果；(3)超微结构重构与离子重构协同作用 目的：促进房性心肌病房性心律失常的发生。我们认为量化心房肌的作用 房颤病理的超微结构可能为房颤的治疗提供新的机制认识。每个目标包括 严格生成和验证的建模框架，由心房肌细胞和 组织，以及特定假说的检验。模型和数据将通过软件自由和广泛地分发 和数据库基础设施，由格兰迪博士的实验室和科学网络站点提供支持。

PROJECT SUMMARY: Atrial fibrillation (AF) is the most common cardiac arrhythmia (affecting ~1-2% of the general population), resulting in markedly reduced quality of life and increased mortality, due to a combination of altered hemodynamics, progressive atrial and ventricular dysfunction, and embolic stroke. Many diseases and conditions, like heart failure, are known to contribute to pathological changes leading to AF. Limitations in current therapy allow AF paroxysms to progress to persistent and chronic AF, as a result of extensive atrial structural and electrical changes that facilitate AF maintenance (“AF begets AF”). The development of urgently needed new strategies for AF treatment hinges upon improved understanding of how abnormalities in cellular function trigger and sustain arrhythmia in atrial tissue. At the cellular level, a hallmark structural change of many chronic cardiac diseases is degradation of the intricate membrane architecture that couples cardiac electrical excitation to intracellular Ca2+ release and myocardial contraction (EC coupling) – i.e., the transverse tubule (TT) structures, which project orthogonally from the cell surface to its interior and thereby synchronize EC coupling throughout the cell. Degradation of the TT architecture is generally associated with arrhythmia, but it is not yet clear whether TT loss is a direct contributor to arrhythmia, a compensatory maladaptation, or an epiphenomenon. This is even less clear in atria, as atrial myocytes exhibit a vastly variable range of TT architectures, with prominent axial tubules. Further, TT degradation induced by the process of isolating atrial myocytes (vs. denser TTs in intact tissues) and challenges in experimentally detubulating intact cardiac tissue has so far limited the design of mechanistic myocyte and tissue studies. As a result, the literature surrounding the role of subcellular structural (ultrastructural) remodeling in AF has remained fractured, and currently we know relatively little about its role in contributing to AF pathophysiology. The overarching goal of this proposal is to discriminate the role of changes in atrial myocyte ultrastructure from other disease-associated sequelae by combining detailed multi-level experimental analyses of rabbit atrial myocytes and rabbit and human atrial tissues with extensive quantitative multi-scale computational modeling. The project will develop and validate a suite of modeling tools used to investigate the mechanisms by which: (1) naturally occurring variations in atrial TTs influence EC coupling and membrane stability in isolated atrial myocytes; (2) tissue gradients in TT organization influence tissue-level electrophysiological and EC coupling outcomes; (3) ultrastructural remodeling synergizes with ionic remodeling to favor atrial arrhythmogenesis in atrial cardiomyopathy. We contend that quantifying the role of atrial ultrastructure in AF pathology may shed new mechanistic insight into AF management. Each aim includes rigorously generated and validated modeling frameworks, informed by novel experiments in atrial myocytes and tissues, and testing of specific hypotheses. Models and data will be distributed freely and widely via software and database infrastructure supported by Dr. Grandi's lab and scientific networking sites.