Identifying the origins of resilience through human single cell molecular networks, then testing them in diverse, resilient, human IPS lines

项目摘要 老年认知能力下降的大部分不能用阿尔茨海默病（AD）或其他常见的年龄来解释， 相关神经病理学事实上，每个人在一定程度上都对AD有弹性或易感性， 因为他们独特的基因和环境。在过去的15年里，我们的中心已经确定了许多 与更快或更慢的认知衰退相关的环境和心理风险因素，以及一些 弹性的分子标记，指出弹性基础的分子网络的存在。的 该项目建立在这项工作的基础上。该提案的总体目标是定义复杂的 抗AD能力的分子基础，使用具有不同抗AD能力水平的大脑和体外人类 模型系统，以确定新的治疗目标的认知能力下降。为此，我们将采取 全基因组方法来确定人类大脑中特定细胞类型的弹性的关键分子驱动因素。 然后，我们将对我们已经确定的分子进行严格的测试，使用来自许多不同脑细胞的脑细胞。 人类具体来说，我们将看看我们是否可以通过基因刺激这些细胞，使其对环境变得更有弹性。 老年痴呆症的影响。两个关键的创新将这个项目与以前的工作分开。的 第一个方面是我们专注于单个细胞类型。通常，大脑数据的分子测量包含 几十种细胞类型的混合物。我们将分别测量每种细胞类型，使用单细胞 RNAseq（scRNAseq），以鉴定哪些细胞类型与对AD的恢复力最相关。在这些具体 细胞类型我们将使用计算网络分析来识别细胞内少量的基因 影响恢复力的分子系统这些预测有助于本研究的第二个方面， 这是不寻常的，这是我们的计划，改变这些基因在人类模型的AD。我们将使用的模型是 神经元和神经胶质细胞来自50个不同水平的恢复能力的共同散发 老年痴呆症的症状我们将使用基因组工程来影响我们预测的基因丰度， 与这些细胞系的弹性有关。通过这种方式，我们可以检查产生的基因表达签名 弹性以及与健康认知相关的细胞表型，这些表型在AD面前持续存在 病理拟议的项目将提供一套全面的分子网络和关键分子 这是抗AD和其他常见脑部疾病的基础。它将通过打破共同的障碍来做到这一点 在这一领域取得进展：1）通过单细胞方法和计算方法准确识别目标 网络方法; 2）在真实人体模型中进行测试。该项目将提供高置信度 治疗发展的目标。因此，该提案将对实地产生强有力的持续影响。

PROJECT SUMMARY Much of late-life cognitive decline cannot be explained by Alzheimer’s disease (AD) or other common age- related neuropathologies. In fact, every individual is either resilient or susceptible to AD to a certain extent, due to their unique genetics and environment. Over the past 15 years our center has identified numerous environmental and psychological risk factors associated with faster or slower cognitive decline, and several molecular markers of resilience, that point to the existence of molecular networks that underlie resilience. The proposed project builds on this prior work. The overall goal of this proposal is to define the complex molecular basis of resilience to AD, using brains with various levels of resilience and in vitro human model systems, to identify novel therapeutic targets for cognitive decline. To do this, we will take a genome-wide approach to identify key molecular drivers of resilience in specific cell types in the human brain. Then we will perform rigorous tests of the molecules we have identified using brain cells from many different humans. Specifically we will see if we can genetically stimulate these cells to become more resilient to the effects of aging and Alzheimer’s disease. Two key innovations separate this project from previous work. The first aspect is our focus on individual cell types. Typically molecular measurements of brain data contain a mixture of dozens of cell types. We will measure each of these cell types individually, using single-cell RNAseq (scRNAseq), to identify which cell types are most related to resilience to AD. Within these specific cell types we will use computational network analysis to identify a smaller number of gene genes within the molecular systems affecting resilience. These predictions facilitate the 2nd aspect of this study which is unusual, which is our plan to change these genes in a human model of AD. The model we will use are neurons and glial cells derived from 50 individuals with different level of resilience to the common sporadic form of Alzheimer’s. We will use genome engineering to affect the abundance of genes that we predict are related to resilience in all of these cell lines. In this way we can check for resulting gene expression signatures of resilience as well as cellular phenotypes associated with health cognition, which persist in the face of AD pathology. The proposed project will deliver a comprehensive set of molecular networks and key molecules that underlie resilience to AD and other common brain pathologies. It will do so by breaking common barriers to progress in this area: 1) accurate identification of targets through a single cell approach and computational network methods, and 2) testing in realistic human models. The proposed project will provide high-confidence targets for therapeutic development. Thus, the proposal will have a strong and sustained impact on the field.