Esmail Sally, Danter Wayne R
123Genetix, London, ON, Canada.
Front Aging Neurosci. 2021 Feb 23;13:643889. doi: 10.3389/fnagi.2021.643889. eCollection 2021.
Alzheimer's disease (AD) is the most common type of neurodegenerative diseases. There are over 44 million people living with the disease worldwide. While there are currently no effective treatments for AD, induced pluripotent stem cell-derived brain organoids have the potential to provide a better understanding of Alzheimer's pathogenesis. Nevertheless, developing brain organoid models is expensive, time consuming and often does not reflect disease progression. Using accurate and inexpensive computer simulations of human brain organoids can overcome the current limitations. Induced whole brain organoids (aiWBO) will greatly expand our ability to model AD and can guide wet lab research. In this study, we have successfully developed and validated artificially induced a whole brain organoid platform (NEUBOrg) using our previously validated machine learning platform, DeepNEU (v6.1). Using NEUBorg platform, we have generated aiWBO simulations of AD and provided a novel approach to test genetic risk factors associated with AD progression and pathogenesis.
阿尔茨海默病（AD）是最常见的神经退行性疾病类型。全球有超过4400万人患有这种疾病。虽然目前尚无针对AD的有效治疗方法，但诱导多能干细胞衍生的脑类器官有潜力帮助更好地理解阿尔茨海默病的发病机制。然而，开发脑类器官模型成本高昂、耗时且往往无法反映疾病进展。使用准确且廉价的人脑类器官计算机模拟可以克服当前的局限性。诱导全脑类器官（aiWBO）将极大地扩展我们对AD进行建模的能力，并可指导湿实验室研究。在本研究中，我们利用之前经过验证的机器学习平台DeepNEU（v6.1）成功开发并验证了人工诱导全脑类器官平台（NEUBOrg）。使用NEUBorg平台，我们生成了AD的aiWBO模拟，并提供了一种新方法来测试与AD进展和发病机制相关的遗传风险因素。
