人类神经前代细胞的形态分析对阿尔茨海默病的试点药物选中的命中药物进行了分类
Amina H McDiarmid1, Katerina O Gospodinova1, Richard J R Elliott2
1Centre for Genomic & Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK.
Brain communications
|April 5, 2024
概括
这项研究使用SORL1基因开发了一种基于细胞形态的阿尔茨海默病药物选. 它确定了14种可以逆转疾病相关细胞变化的药物,为阿尔茨海默氏症药物发现提供了新的途径.
科学领域:
- 神经科学是一个神经科学.
- 遗传学 是一个遗传学.
- 药理学 药理学是指药理学的学科.
背景情况:
- 阿尔茨海默病 (AD) 是导致痴呆的主要原因,目前的治疗方法不足.
- 遗传风险因素,如SORL1基因的变异,在AD病变发生过程中发挥着重要作用.
- SORL1基因变异与阿尔茨海默病中SORLA蛋白表达减少和内分泌体路径改变有关.
研究的目的:
- 评估使用基于细胞形态的表型查用于阿尔茨海默病药物发现的可行性.
- 开发和验证一个以AD风险基因SORL1为中心的高通量查方法.
- 通过选批准的小分子图书馆来识别潜在的阿尔茨海默病候选药物.
主要方法:
- 调整了细胞绘画试验,用于神经前代细胞 (NPC) 的自动形态分析.
- 使用诱导多能干细胞 (iPSC) 生成的SORL1淘汰赛NPCs来建模与AD相关的细胞表型.
- 对330个化合物的库进行了SORL1缺乏NPC的选,以确定可以逆转疾病相关形态变化的化合物.
主要成果:
- 与野生类型对照相比,在缺乏SORL1的NPC中发现了明显的表型特征.
- 发现16种化合物,代表14种不同的药物,可以逆转观察到的突变形态表型.
- 网络药理学分析表明,这些化合物向的途径包括20S蛋白酶,化脱酶,拓酶和DNA合成.
结论:
- 定量表型指标可以有效地区分缺乏SORL1的NPC和同位素对照.
- 表型查与高内容图像分析相结合,是阿尔茨海默病模型中药物重新定位和发现的可行策略.
- 这些已识别的化合物通过准关键的生物通路,为阿尔茨海默病提供了潜在的治疗途径.
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