Parkinson disease (PD) is a neurodegenerative disorder caused by the progressive loss of midbrain dopaminergic neurons, and mitochondrial dysfunction is involved in its pathogenesis. This study aimed to establish an imaging-based, semi-automatic, high-throughput system for the quantitative detection of disease-specific phenotypes in dopaminergic neurons from induced pluripotent stem cells (iPSCs) derived from patients with familial PD having Parkin or PINK1 mutations, which exhibit abnormal mitochondrial homeostasis. The proposed system recapitulates the deficiency of mitochondrial clearance, ROS accumulation, and increasing apoptosis in these familial PD-derived neurons. We screened 320 compounds for their ability to ameliorate multiple phenotypes and identified four candidate drugs. Some of these drugs improved the locomotion defects and reduced ATP production caused by PINK1 inactivation in Drosophila and were effective for idiopathic PD-derived neurons with impaired mitochondrial clearance. Our findings suggest that the proposed high-throughput system has potential for identifying effective drugs for familial and idiopathic PD.

帕金森病（PD）是一种神经退行性疾病，由中脑多巴胺能神经元的逐渐丧失引起，线粒体功能障碍参与其发病机理。这项研究旨在建立一种基于成像的半自动高通量系统，用于定量检测多巴胺能神经元中疾病特异性表型，该多巴胺能神经元来自具有帕金或PINK1家族性PD患者的诱导性多能干细胞（iPSC）突变，表现出异常的线粒体稳态。拟议的系统概括了这些家族性PD衍生神经元中线粒体清除，ROS积累和凋亡增加的缺陷。我们筛选了320种化合物改善多种表型的能力，并确定了四种候选药物。其中一些药物改善了果蝇中PINK1失活引起的运动缺陷并减少了ATP的产生，并且对于线粒体清除受损的特发性PD衍生神经元有效。我们的发现表明，拟议的高通量系统具有识别家族性和特发性PD有效药物的潜力。