Drug-induced Torsades de Pointes (TdP) arrhythmia is of major interest in predictive toxicology. Drugs which cause TdP block the hERG cardiac potassium channel. However, not all drugs that block hERG cause TdP. As such, further understanding of the mechanistic route to TdP is needed. Early afterdepolarisations (EADs) are a cell-level phenomenon in which the membrane of a cardiac cell depolarises a second time before repolarisation, and EADs are seen in hearts during TdP. Therefore, we propose a method of predicting TdP using induced EADs combined with multiple ion channel block in simulations using biophysically-based mathematical models of human ventricular cell electrophysiology. EADs were induced in cardiac action potential models using interventions based on diseases that are known to cause EADs, including: increasing the conduction of the L-type calcium channel, decreasing the conduction of the hERG channel, and shifting the inactivation curve of the fast sodium channel. The threshold of intervention that was required to cause an EAD was used to classify drugs into clinical risk categories. The metric that used L-type calcium induced EADs was the most accurate of the EAD metrics at classifying drugs into the correct risk categories, and increased in accuracy when combined with action potential duration measurements. The EAD metrics were all more accurate than hERG block alone, but not as predictive as simpler measures such as simulated action potential duration. This may be because different routes to EADs represent risk well for different patient subgroups, something that is difficult to assess at present.

中文翻译：

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早期后除极倾向作为模拟促心律失常风险指标

药物引起的尖端扭转型室性心动过速 (TdP) 心律失常是预测毒理学的主要关注点。引起 TdP 的药物会阻断 hERG 心脏钾通道。然而，并非所有阻断 hERG 的药物都会导致 TdP。因此，需要进一步了解 TdP 的机制途径。早期后去极化 (EAD) 是一种细胞水平现象，其中心脏细胞膜在复极化之前第二次去极化，并且 EAD 在 TdP 期间在心脏中可见。因此，我们提出了一种在使用基于生物物理的人体心室细胞电生理学数学模型的模拟中使用诱导 EAD 与多个离子通道阻滞相结合来预测 TdP 的方法。使用基于已知导致 EAD 的疾病的干预措施在心脏动作电位模型中诱导 EAD，这些干预措施包括：增加 L 型钙通道的传导、减少 hERG 通道的传导以及移动快钠失活曲线渠道。引起 EAD 所需的干预阈值用于将药物分类为临床风险类别。使用 L 型钙诱导 EAD 的指标是将药物分类为正确风险类别的 EAD 指标中最准确的指标，并且与动作电位持续时间测量相结合时准确性更高。EAD 指标比单独的 hERG 模块更准确，但不如模拟动作电位持续时间等更简单的指标具有预测性。这可能是因为 EAD 的不同途径代表了不同患者亚组的风险，目前很难评估这一点。