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)。我们试图预防疾病的发生或发展 AD通过发现和增强防止其发生的自然发生途径的活动来实现。这 自然的恢复力很重要，因为这是阿尔茨海默氏症唯一已知的表现方式 控制住了。在这里，我们利用了这样一个事实，即一部分老龄化人口似乎在认知上保持不变 同时控制或补偿AD相关的Tau病理，并享有相对天然的认知抵抗 阿尔茨海默病的损害或诊断。利用全基因组测序和转录组分析 ，我们将确定新的药物敏感的弹性相关(RA)途径 广告。我们将实施一项新的、经过验证的技术，即路径药物网络(PDN)，该网络由 富含药物途径基因簇的人类基因表达数据，以识别增强类风湿关节炎的药物 小路。PDN预测的单个或组合导联的第一轮筛选将在我们的 AD的创新3D人类神经细胞培养模型，概括了AD的各个致病阶段 包括抗体沉积(抗体斑块)，抗体驱动的tau病理(神经原纤维缠结(NFT)，以及 神经炎症和神经变性。然后在转基因AD小鼠中对验证的导联进行评分 减少突触丢失和认知完整性的模型。该方法将为建立一个 可以预防或减少与AD相关的认知功能下降的治疗干预。智力价值：这一点 该项目将极大地促进对老年成人大脑神经保护的理解，同时 为控制AD相关病理和认知丧失之间的关系提供了新的见解。 更广泛的影响：AD对老龄化人口的影响越来越大，而且没有有效的干预措施。减少 它的发病率将具有重大意义。如果成功，该项目将允许开发临床 应用新药或FDA批准的重新调整用途的药物，同时为 开发成功的AD药物组合。目的1：使用网络分析技术，我们将生成一个 从整体上利用途径、基因和网络模块对类风湿关节炎途径的分子系统定义 基因组测序数据和文献，以及显示弹性高或低的死后脑转录 斑块/缠结，AD症状低，但认知分数高。目标2：比较PDN内的RA通路与 预测具有弹性的药物/途径组合。一系列药物再利用筛查将使 排序的药物/组合和途径活性列表。选定的组合将在多个3D中进行验证 模拟AD不同发病阶段的AD神经细胞培养模型及其对AD的影响 致病标志物。目的3：在AD转基因APP小鼠模型中验证使用认知指标的有效性。得分 为了在AD转基因小鼠模型中赋予抗体沉积的弹性和神经保护的能力， 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.