Gilchrist Kristin H, Lewis Gregory F, Gay Elaine A, Sellgren Katelyn L, Grego Sonia
RTI International, 3040 E. Cornwallis Road, Research Triangle Park, NC 27709, USA.
RTI International, 3040 E. Cornwallis Road, Research Triangle Park, NC 27709, USA.
Toxicol Appl Pharmacol. 2015 Oct 15;288(2):249-57. doi: 10.1016/j.taap.2015.07.024. Epub 2015 Jul 29.
Microelectrode arrays (MEAs) recording extracellular field potentials of human-induced pluripotent stem cell-derived cardiomyocytes (hiPS-CM) provide a rich data set for functional assessment of drug response. The aim of this work is the development of a method for a systematic analysis of arrhythmia using MEAs, with emphasis on the development of six parameters accounting for different types of cardiomyocyte signal irregularities. We describe a software approach to carry out such analysis automatically including generation of a heat map that enables quick visualization of arrhythmic liability of compounds. We also implemented signal processing techniques for reliable extraction of the repolarization peak for field potential duration (FPD) measurement even from recordings with low signal to noise ratios. We measured hiPS-CM's on a 48 well MEA system with 5minute recordings at multiple time points (0.5, 1, 2 and 4h) after drug exposure. We evaluated concentration responses for seven compounds with a combination of hERG, QT and clinical proarrhythmia properties: Verapamil, Ranolazine, Flecainide, Amiodarone, Ouabain, Cisapride, and Terfenadine. The predictive utility of MEA parameters as surrogates of these clinical effects were examined. The beat rate and FPD results exhibited good correlations with previous MEA studies in stem cell derived cardiomyocytes and clinical data. The six-parameter arrhythmia assessment exhibited excellent predictive agreement with the known arrhythmogenic potential of the tested compounds, and holds promise as a new method to predict arrhythmic liability.
微电极阵列(MEA)记录人诱导多能干细胞衍生心肌细胞(hiPS-CM)的细胞外场电位,为药物反应的功能评估提供了丰富的数据集。这项工作的目的是开发一种使用MEA系统分析心律失常的系统方法,重点是开发六个参数,以解释不同类型的心肌细胞信号不规则性。我们描述了一种软件方法来自动进行这种分析,包括生成热图,以便快速可视化化合物的心律失常倾向。我们还实施了信号处理技术,即使从低信噪比的记录中也能可靠地提取复极化峰值,用于测量场电位持续时间(FPD)。我们在48孔MEA系统上测量hiPS-CM,在药物暴露后的多个时间点(0.5、1、2和4小时)进行5分钟的记录。我们评估了七种具有hERG、QT和临床致心律失常特性的化合物的浓度反应:维拉帕米、雷诺嗪、氟卡尼、胺碘酮、哇巴因、西沙必利和特非那定。研究了MEA参数作为这些临床效应替代指标的预测效用。心率和FPD结果与先前在干细胞衍生心肌细胞中的MEA研究以及临床数据显示出良好的相关性。六参数心律失常评估与受试化合物已知的致心律失常潜力表现出极好的预测一致性,有望成为预测心律失常倾向的新方法。