Drug repositioning for Alzheimer's disease via genetics, electronic health records, and human iPSC models

阿尔茨海默病（AD）是一种进行性神经退行性疾病，也是导致阿尔茨海默病（AD）的主要原因 痴呆症在美国不幸的是，没有治愈AD的方法。AD的药物发现 遭受了重大的失败，许多在后期阶段的临床试验，部分原因是我们的穷人， 对AD病理学的理解以及缺乏疾病相关和人类相关的发现， 发展模式。这需要团队努力，利用各种互补的专业知识来解决 通过从多个角度制定创新办法， 识别AD药物的目标。 在本申请中，我们提出了三个互补的具体目标，共同旨在确定 FDA批准的具有AD再利用潜力的药物，从不同但互补的角度， 协同地提高成功的可能性。AD是一种高度遗传性疾病， 估计遗传率为70%，突出了遗传学在理解遗传学中的关键作用。 疾病病因学最近的遗传学研究已经确定了30多个基因座，使我们能够解剖 AD的遗传结构，包括疾病中涉及的生物学过程和细胞类型 病因学特别是，我们的目标是将高度多基因的AD病因学分解为不同的 病理生理成分来指导药物再利用，这是近年来才可行的 这要归功于大规模的GWAS和大量的基因组学数据（Aim 1）。同时，我们 将挖掘数百万电子健康记录（EHR），以确定降低AD风险的药物， 认知下降，通过开发EHR的AD相关表型的表型分型算法（目的2）。 此外，我们将开发一种高通量筛选（HTS）基因表达谱分析方法， 使用人类诱导多能干细胞（iPSC）模型来鉴定候选化合物，并将 进一步测试候选物在源自患者的iPSC系和AD小鼠模型中的功效 (Aim 3）。这三个目标是相辅相成和协同增效的，因为它们独立地 从截然不同的角度处理同一个问题，而一个人的发现可以作为 为他人的认可。总之，利用独特和互补的专业知识，我们希望 用正交载体制备真正的可重复利用的AD药物。

Alzheimer's disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia in the United States. Unfortunately, there is no cure for AD. Drug discovery for AD has suffered significant failures, many at late stage clinical trials, partly due to our poor understanding of AD pathology and the lack of disease-relevant and human-relevant discovery and development models. This calls for team efforts with diverse and complementary expertise to tackle the challenges together, by developing innovative approaches from multiple angles to achieve the goal of identifying AD drugs. In this application, we propose three complementary Specific Aims that together aim to identify FDA approved drugs with repurpose potential for AD, from distinct but complementary angles that act synergistically to boost the likelihood of success. AD is a highly heritable disease, with an estimated heritability of 70%, highlighting the critical role of genetics in understanding the disease etiology. Recent genetic studies have identified over 30 loci, enabling us to dissect the genetic architecture of AD, including the biological processes and cell types involved in disease etiology. In particular, we aim to dissect the highly polygenic AD etiology into distinct pathophysiological components to guide drug repurposing, which is only feasible in recent years thanks to large scale GWAS and massive genomics data available publicly (Aim 1). In parallel, we will mine millions of electronic health records (EHRs) to identify drugs that reduce AD risk and cognitive decline, by developing phenotyping algorithms from EHR for AD related phenotypes (Aim 2). In addition, we will develop a high­ throughput screening (HTS) gene expression profiling assay and use human induced pluripotent stem cell (iPSC) models to identify candidate compounds, and will further test the efficacy of the candidates in both patient-derived iPSC lines and AD mouse models (Aim 3). The three aims are complementary and synergistic, in the sense that they independently tackle the same problem from drastically distinct angles, while findings from one can be served as validation for others. Altogether, leveraging distinct and complementary expertise, we expect to yield bona fide repurposable drugs for AD with orthogonal support.