The Alzheimer's Disease Resiliome: Pathway Analysis and Drug Discovery.

目前还没有有效的药物来预防阿尔茨海默病（AD）。我们致力于预防 通过发现和增强自然发生的途径，防止其发生的活动。这 自然恢复力是重要的，因为它是唯一已知的方式，阿尔茨海默氏症似乎是 控制。在这里，我们利用了一个事实，即一部分老龄人口似乎保持认知完整 同时控制或补偿AD相关的Tau病理，并对认知功能具有相对天然的抵抗力。 AD的诊断或诊断。使用全基因组测序（WGS）和转录组分析， 自然AD弹性人群，我们将确定新的药物敏感的弹性相关（RA）的途径， AD.我们将实施一种新的、经过验证的技术，即通路药物网络（PDN）， 人类基因表达数据丰富的药物途径基因簇，以确定药物，增强RA 途径。PDN预测的单一或组合导联的第一轮筛选将在我们的 创新的AD 3D人类神经细胞培养模型，概括了AD的各个致病阶段 包括Ab沉积（Ab斑块）、Ab驱动的tau病理（神经元缠结（NFT），以及 神经炎症和神经变性。然后将在转基因AD小鼠中对经验证的导联进行评分 减少突触损失和认知完整性的模型。该方法将为 治疗干预可以预防或减少与AD相关的认知下降。智力价值：这 该项目将大大促进对老年人大脑神经保护的理解， 为AD相关病理学的控制和认知丧失之间的关系提供了新的见解。 更广泛的影响：AD越来越多地影响老龄化人口，并且没有有效的干预措施。减少 其发病率将具有重大意义。如果成功，该项目将允许临床开发 应用新药或FDA批准的重新用途的药物，同时为 开发成功的AD药物组合。目标1：使用网络分析技术，我们将生成一个 分子系统定义RA途径使用途径，基因和网络模块从整体 基因组测序数据和文献，以及死后大脑转录组，显示弹性高或低 斑块/缠结，AD症状低，但认知评分高。目的2：比较PDN内的RA通路与 预测药物/途径组合，赋予弹性。一系列药物再利用筛选将优化 排名药物/组合和途径活性的列表。选定的组合将在多个3D中进行验证 AD的人神经细胞培养模型，其模拟AD的不同致病阶段，用于它们对AD的影响 致病标记物目的3：在AD转基因APP小鼠模型中验证认知代理的使用。评分 对于在AD转基因小鼠模型中赋予抗体沉积的恢复力和神经保护的能力， 突触/认知缺陷和/或神经炎症。

There are no effective drugs to prevent Alzheimer’s disease (AD). We seek to prevent onset or progression of AD by discovering and enhancing the activity of naturally occurring pathways that prevent its occurrence. This natural resilience is significant because it is the only known manner in which Alzheimer’s appears to be controlled. Here, we exploit the fact that a proportion of the aging population appear to remain cognitively intact while controlling or compensating AD related Tau pathology and enjoy a relative natural resistance to cognitive impairment or diagnosis of AD. Using whole genome sequencing (WGS) and transcriptome analysis of a naturally AD-resilient population, we will identify novel drug-sensitive resilience associated (RA) pathways in AD. We will implement a novel, validated technology, the Pathway Drug Network (PDN), constructed from human gene expression data enriched in drug–pathway–gene clusters, to identify drugs that enhance RA pathways. First round screening of the PDN-predicted single or combinations of leads will be tested in our innovative 3D human neural cell culture models of AD, which recapitulate various pathogenic stages of AD including Ab deposition (Ab plaque), Ab-driven tau pathology (neurofibrillary tangles (NFTs), and neuroinflammation and neurodegeneration. Validated leads will then be scored in transgenic AD mouse models for reduction of synaptic loss and cognitive integrity. The approach will establish the basis for a therapeutic intervention that can prevent or reduce cognitive decline related to AD. Intellectual merit: This project will significantly advance the understanding of neuroprotection in aging adult human brains while providing novel insights into the relationships between control of AD related pathology and loss of cognition. Broader impact: AD increasingly affects the aging population and there is no effective intervention. Reduction of its incidence will be of major significance. If successful, the project will allow development of clinical application of novel drugs or repurposed FDA approved drugs while creating a powerful new paradigm for developing successful AD drug combinations. Aim1: Using network analytical techniques, we will generate a molecular systems definition of RA pathways using pathways, genes and network modules from whole genome sequencing data and literature, and post mortem brain transcriptomes that show resilient high or low plaque/tangle, low AD symptoms, but high cognitive scores. Aim 2: Compare RA pathways within PDN to predict drug/pathway combinations that confer resilience. A series of drug-repurposing screens will optimise lists of ranked drugs/combinations and pathway activity. Selected combinations will be validated in multiple 3D human neural cell culture models of AD that mimic various pathogenic stages of AD for their impact on AD pathogenic markers. Aim 3: Validate using proxies of cognition in an AD transgenic APP mouse model. Score for the ability to confer resilience and neuroprotection in AD transgenic mouse models for either Ab deposition, synaptic/cognitive deficits and/or neuroinflammation.