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

通过人类单细胞分子网络识别恢复力的起源，然后在多样化、有恢复力的人类 IPS 系中对其进行测试

• 批准号: 10730100
• 负责人: Christopher A. Gaiteri
• 金额: $ 47.72万
• 依托单位: UPSTATE MEDICAL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10730100
• 关键词: Identifying; origins; resilience; through; human; Identifying; origins; resilience; through; human

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.

项目摘要 阿尔茨海默氏病（AD）或其他常见的年龄 - 相关神经病理学。实际上，每个人在一定程度上都具有弹性或容易受到AD的影响， 由于它们独特的遗传学和环境。在过去的15年中，我们的中心已经确定了无数次 环境和心理危险因素与更快或更慢的认知能力下降相关，有几个 弹性的分子标记，这表明存在弹性的分子网络的存在。 拟议的项目以这项先前的工作为基础。该提议的总体目标是定义复杂 使用具有各种弹性和体外人类的大脑的AD弹性分子基础 模型系统，以确定认知下降的新型治疗靶标。为此，我们将 识别人脑特定细胞类型中关键弹性的关键分子驱动因素的全基因组方法。 然后，我们将对使用来自许多不同不同的脑细胞鉴定的分子进行严格的测试 人类。具体而言，我们将看看是否可以遗传刺激这些细胞，以使其对 衰老和阿尔茨海默氏病的影响。两个关键的创新与以前的工作分开。这 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值 数十种细胞类型的混合物。我们将使用单细胞分别测量这些细胞类型 RNASEQ（SCRNASEQ），确定哪些细胞类型与AD的弹性最相关。在这些特定的内部 细胞类型我们将使用计算网络分析来识别少量基因基因 影响弹性的分子系统。这些预测促进了这项研究的第二方面 不寻常，这是我们在人类AD模型中改变这些基因的计划。我们将使用的模型是 神经元和神经胶质细胞来自50个具有不同弹性水平的个体与普通零星 阿尔茨海默氏症的形式。我们将使用基因组工程来影响我们预测的基因的抽象 与所有这些细胞系中的弹性有关。通过这种方式，我们可以检查产生的基因表达特征 与健康认知相关的弹性以及蜂窝表型，面对AD的持续存在 病理。拟议的项目将提供一组全面的分子网络和关键分子 这是对AD和其他常见大脑病理的韧性。它将通过打破普通障碍来做到这一点 在该领域进步：1）通过单个单元格和计算准确识别目标 网络方法和2）在现实的人类模型中进行测试。拟议的项目将提供高信心 热发育的目标。这是该提案将对该领域产生强大的持续影响。