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[用于评估药物诱导癫痫发作风险的药物处理大鼠原代神经元和人诱导多能干细胞衍生神经元的膜片钳数据分析方法]

[Method for MEA Data Analysis of Drug-treated Rat Primary Neurons and Human iPSC-derived Neurons to Evaluate the Risk of Drug-induced Seizures].

作者信息

Ojima Atsuko, Miyamoto Norimasa

机构信息

Eisai Co., Ltd.

Bio Medical Technology HYBRID.

出版信息

Yakugaku Zasshi. 2018;138(6):823-828. doi: 10.1248/yakushi.17-00213-3.

Abstract

Use of the microelectrode array (MEA) system to record spontaneous neuron activity from networks of cultured neurons has potential as a good risk evaluation method for drug-induced seizure events. Spontaneous electrical activity in neural networks consists of action potential spikes and organized patterns of action potential bursts. In both potentiated rodent primary neurons and human induced pluripotent stem cell (iPSC)-derived neurons, an epileptogenic response pattern manifests as a synchronized burst from spatially separated neurons. Here, we delineate how to perform MEA experiments using cultured neurons, and how to analyze the MEA data to detect drug-induced seizurogenic abnormalities. Usually, a drug's effects, as shown by MEA data, include changes in spike frequency, inter-spike intervals (ISI), burst frequency, burst duration, spikes in a burst, etc. Subsequently, seizurogenic events are evidenced by changes in synchronized burst phenotypes from spatially separated multiple channels in an MEA probe, such as a change in the cross correlation of the spike events from all channels in an MEA probe, or a change in histogram from the sum of ISI for all channels in a probe, etc. We attempted to depict an epileptogenic marker using a histogram of the sum of spikes for all channels in an MEA probe. Verification of these metrics for drug induced abnormalities is ongoing in various collaboration organizations, including the Consortium for Safety Assessment using Human iPS Cells (CSAHi), iPS Non-clinical Experiments for the Nervous System (iNCENS). Collaboration networks for the utilization of iPSC-derived cells during drug development are also summarized here.

摘要

使用微电极阵列(MEA)系统记录培养神经元网络的自发神经元活动,有潜力成为一种评估药物诱发癫痫事件的良好风险评估方法。神经网络中的自发电活动由动作电位尖峰和动作电位爆发的有组织模式组成。在增强的啮齿动物原代神经元和人类诱导多能干细胞(iPSC)衍生的神经元中,致癫痫反应模式表现为空间上分离的神经元的同步爆发。在这里,我们描述了如何使用培养的神经元进行MEA实验,以及如何分析MEA数据以检测药物诱发的致癫痫异常。通常,MEA数据显示的药物作用包括尖峰频率、峰间间隔(ISI)、爆发频率、爆发持续时间、爆发中的尖峰等的变化。随后,可以通过MEA探针中空间上分离的多个通道的同步爆发表型的变化来证明致癫痫事件,例如MEA探针中所有通道的尖峰事件的互相关变化,或探针中所有通道的ISI总和的直方图变化等。我们试图使用MEA探针中所有通道的尖峰总和的直方图来描绘一个致癫痫标记。包括使用人类iPS细胞进行安全评估联盟(CSAHi)、神经系统iPS非临床实验(iNCENS)在内的各个合作组织正在对这些药物诱发异常指标进行验证。这里还总结了药物开发过程中利用iPSC衍生细胞的合作网络。

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