Ni Haibo, Morotti Stefano, Grandi Eleonora
Department of Pharmacology, University of California, Davis, Davis, CA, United States.
Front Physiol. 2018 Jul 20;9:958. doi: 10.3389/fphys.2018.00958. eCollection 2018.
In cardiac electrophysiology, there exist many sources of inter- and intra-personal variability. These include variability in conditions and environment, and genotypic and molecular diversity, including differences in expression and behavior of ion channels and transporters, which lead to phenotypic diversity (e.g., variable integrated responses at the cell, tissue, and organ levels). These variabilities play an important role in progression of heart disease and arrhythmia syndromes and outcomes of therapeutic interventions. Yet, the traditional framework for investigating cardiac arrhythmias is built upon a parameter/property-averaging approach that typically overlooks the physiological diversity. Inspired by work done in genetics and neuroscience, new modeling frameworks of cardiac electrophysiology have been recently developed that take advantage of modern computational capabilities and approaches, and account for the variance in the biological data they are intended to illuminate. In this review, we outline the recent advances in statistical and computational techniques that take into account physiological variability, and move beyond the traditional cardiac model-building scheme that involves averaging over samples from many individuals in the construction of a highly tuned composite model. We discuss how these advanced methods have harnessed the power of big (simulated) data to study the mechanisms of cardiac arrhythmias, with a special emphasis on atrial fibrillation, and improve the assessment of proarrhythmic risk and drug response. The challenges of using approaches with variability are also addressed and future directions are proposed.
在心脏电生理学中，存在许多个体间和个体内的变异性来源。这些包括条件和环境的变异性，以及基因型和分子多样性，包括离子通道和转运体的表达和行为差异，这些差异导致表型多样性（例如，在细胞、组织和器官水平上的可变综合反应）。这些变异性在心脏病和心律失常综合征的进展以及治疗干预的结果中起着重要作用。然而，传统的研究心律失常的框架是基于参数/属性平均方法构建的，这种方法通常忽略了生理多样性。受遗传学和神经科学领域工作的启发，最近开发了新的心脏电生理学建模框架，这些框架利用了现代计算能力和方法，并考虑了它们旨在阐明的生物学数据中的变异性。在这篇综述中，我们概述了考虑生理变异性的统计和计算技术的最新进展，并超越了传统的心脏模型构建方案，即在构建高度优化的复合模型时对来自许多个体的样本进行平均。我们讨论了这些先进方法如何利用大（模拟）数据的力量来研究心律失常的机制，特别强调心房颤动，并改善对促心律失常风险和药物反应的评估。还讨论了使用具有变异性的方法所面临的挑战，并提出了未来的方向。
