Devenyi Ryan A, Ortega Francis A, Groenendaal Willemijn, Krogh-Madsen Trine, Christini David J, Sobie Eric A
Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Graduate School, New York, NY, USA.
J Physiol. 2017 Apr 1;595(7):2301-2317. doi: 10.1113/JP273191. Epub 2016 Dec 28.
Arrhythmias result from disruptions to cardiac electrical activity, although the factors that control cellular action potentials are incompletely understood. We combined mathematical modelling with experiments in heart cells from guinea pigs to determine how cellular electrical activity is regulated. A mismatch between modelling predictions and the experimental results allowed us to construct an improved, more predictive mathematical model. The balance between two particular potassium currents dictates how heart cells respond to perturbations and their susceptibility to arrhythmias.
Imbalances of ionic currents can destabilize the cardiac action potential and potentially trigger lethal cardiac arrhythmias. In the present study, we combined mathematical modelling with information-rich dynamic clamp experiments to determine the regulation of action potential morphology in guinea pig ventricular myocytes. Parameter sensitivity analysis was used to predict how changes in ionic currents alter action potential duration, and these were tested experimentally using dynamic clamp, a technique that allows for multiple perturbations to be tested in each cell. Surprisingly, we found that a leading mathematical model, developed with traditional approaches, systematically underestimated experimental responses to dynamic clamp perturbations. We then re-parameterized the model using a genetic algorithm, which allowed us to estimate ionic current levels in each of the cells studied. This unbiased model adjustment consistently predicted an increase in the rapid delayed rectifier K current and a drastic decrease in the slow delayed rectifier K current, and this prediction was validated experimentally. Subsequent simulations with the adjusted model generated the clinically relevant prediction that the slow delayed rectifier is better able to stabilize the action potential and suppress pro-arrhythmic events than the rapid delayed rectifier. In summary, iterative coupling of simulations and experiments enabled novel insight into how the balance between cardiac K currents influences ventricular arrhythmia susceptibility.
心律失常是由心脏电活动紊乱引起的，尽管控制细胞动作电位的因素尚未完全明确。我们将数学建模与豚鼠心脏细胞实验相结合，以确定细胞电活动是如何被调节的。建模预测与实验结果之间的差异使我们能够构建一个改进的、更具预测性的数学模型。两种特定钾电流之间的平衡决定了心脏细胞对干扰的反应方式及其发生心律失常的易感性。
离子电流的失衡会使心脏动作电位不稳定，并可能引发致命的心律失常。在本研究中，我们将数学建模与信息丰富的动态钳实验相结合，以确定豚鼠心室肌细胞动作电位形态的调节机制。参数敏感性分析用于预测离子电流变化如何改变动作电位持续时间，并通过动态钳技术进行实验验证，该技术允许在每个细胞中测试多种干扰。令人惊讶的是，我们发现一个用传统方法开发的主要数学模型系统性地低估了对动态钳干扰的实验反应。然后，我们使用遗传算法对模型进行重新参数化，这使我们能够估计所研究的每个细胞中的离子电流水平。这种无偏的模型调整一致地预测快速延迟整流钾电流增加，而缓慢延迟整流钾电流急剧下降，这一预测得到了实验验证。随后用调整后的模型进行的模拟得出了临床上相关的预测，即缓慢延迟整流器比快速延迟整流器更能稳定动作电位并抑制促心律失常事件。总之，模拟与实验的迭代耦合使我们对心脏钾电流之间的平衡如何影响室性心律失常易感性有了新的认识。
