Department of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, China.
Department of Cardiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China.
Comput Methods Programs Biomed. 2023 Apr;231:107372. doi: 10.1016/j.cmpb.2023.107372. Epub 2023 Jan 26.
Knowledge of electromechanical coupling in cardiomyocyte and how it is influenced by various pathophysiological factors is fundamental to understanding the pathogenesis of myocardial disease and its response to medication, which is however hard to be thoroughly addressed by clinical/experimental studies due to technical limitations. At this point, computational modeling offers an alternative approach. The main objective of the study was to develop a computational model capable of simulating the process of electromechanical coupling and quantifying the roles of various factors in play in the human left ventricular cardiomyocyte.
A new electrophysiological model was firstly built by combining several existing electrophysiological models and incorporating the mechanism of electrophysiological homeostasis, which was subsequently coupled to models representing the cross-bridge dynamics and active force generation during excitation-contraction coupling and the passive mechanical properties of cardiomyocyte to yield an integrative electromechanical model. Model parameters were calibrated or optimized based on a large amount of experimental data. The resulting model was applied to delineate the characteristics of electromechanical coupling and explore underlying determinant factors in hypertrophic cardiomyopathy (HCM) cardiomyocyte, as well as quantify their changes in response to different medications.
Model predictions captured the major electromechanical characteristics of cardiomyocyte under both normal physiological and HCM conditions. In comparison with normal cardiomyocyte, HCM cardiomyocyte suffered from systemic changes in both electrophysiological and mechanical variables. Numerical simulations of drug response revealed that Mavacamten and Metoprolol could both reduce the active contractility and alleviate calcium overload but had marked differential influences on many other electromechanical variables, which theoretically explained why the two drugs have differential therapeutic effects. In addition, our numerical experiments demonstrated the important role of compensatory ion transport in maintaining electrophysiological homeostasis and regulating cytoplasmic volume.
A sophisticated computational model has the advantage of providing quantitative and integrative insights for understanding the pathogenesis and drug responses of HCM or other myocardial diseases at the level of cardiomyocyte, and hence may contribute as a useful complement to clinical/experimental studies. The model may also be coupled to tissue- or organ-level models to strengthen the physiological implications of macro-scale numerical simulations.
了解心肌细胞的机电耦合以及各种病理生理因素如何影响机电耦合，对于理解心肌疾病的发病机制及其对药物的反应至关重要，但由于技术限制，临床/实验研究很难彻底解决这一问题。此时，计算建模提供了一种替代方法。本研究的主要目的是开发一种能够模拟机电耦合过程并量化各种因素在人左心室心肌细胞中作用的计算模型。
首先通过结合几个现有的电生理模型并纳入电生理稳态机制，构建了一个新的电生理模型，随后将其与代表兴奋-收缩耦联期间横桥动力学和主动力产生以及心肌细胞被动机械特性的模型相结合，生成一个综合的机电模型。根据大量实验数据对模型参数进行校准或优化。将得到的模型应用于描绘机电耦合的特征，并探讨肥厚型心肌病（HCM）心肌细胞中的潜在决定因素，以及量化它们对不同药物的反应变化。
模型预测捕获了正常生理和 HCM 条件下心肌细胞的主要机电特性。与正常心肌细胞相比，HCM 心肌细胞在电生理和机械变量方面都受到全身性变化的影响。药物反应的数值模拟表明，Mavacamten 和 Metoprolol 均可降低主动收缩力并减轻钙超载，但对许多其他机电变量有明显的不同影响，这从理论上解释了为什么这两种药物具有不同的治疗效果。此外，我们的数值实验表明，补偿性离子转运在维持电生理稳态和调节细胞质体积方面发挥着重要作用。
复杂的计算模型具有提供定量和综合见解的优势，可用于理解 HCM 或其他心肌疾病在心肌细胞水平的发病机制和药物反应，因此可能有助于临床/实验研究。该模型还可以与组织或器官水平的模型相结合，以增强宏观数值模拟的生理意义。
