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: 10474954
• 负责人: Christopher A. Gaiteri
• 金额: $ 49.9万
• 依托单位: RUSH UNIVERSITY MEDICAL CENTER
• 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 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10474954
• 关键词: Address; Affect; Aging; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease pathology; Amyloid beta-Protein; Area; Astrocytes; Automobile Driving; Autopsy; Back; Biological Assay; Biological Models; Brain; Brain Pathology; Brain region; CRISPR screen; Categories; Cell Line; Cell model; Cells; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Cognition; Cognitive; Cohort Studies; Communities; Complex; Computer Analysis; Data; Data Set; Dementia; Drug Targeting; Elderly; Engineering; Environment; Gene Expression Profile; Gene Expression Regulation; Genes; Genetic; Genome engineering; Goals; Health; Human; Impaired cognition; In Vitro; Individual; Influentials; Learning; Link; Magnetic Resonance Imaging; Maps; Measurement; Measures; Memory; Methods; Microglia; Modeling; Molecular; Molecular Probes; Monitor; Neuroglia; Neurons; Participant; Pathologic; Pathology; Pathway Analysis; Patients; Phenotype; Predisposition; Risk Factors; System; Systems Biology; Testing; Work; age effect; age related; base; brain cell; cell type; cognitive function; cohort; drug discovery; experimental study; gene interaction; genome-wide; human model; induced pluripotent stem cell; innovation; molecular marker; neuropathology; new therapeutic target; precision medicine; predictive test; psychologic; religious order study; resilience; single-cell RNA sequencing; stem cell model; stressor; targeted treatment; therapeutic development; tool

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.

项目概要 许多晚年认知能力下降不能用阿尔茨海默病（AD）或其他常见的年龄相关疾病来解释。 事实上，每个人在一定程度上都对AD有抵抗力或易感性， 由于其独特的遗传学和环境，在过去的 15 年里，我们的中心已经鉴定出许多。 与更快或更慢的认知能力下降相关的环境和心理风险因素，以及一些 复原力的分子标记，表明复原力背后的分子网络的存在。 拟议的项目建立在之前的工作之上。该提案的总体目标是定义复杂性。 AD复原力的分子基础，使用具有不同复原力水平的大脑和体外人类 模型系统，以确定认知能力下降的新治疗靶标。为此，我们将采取一种方法。 全基因组方法来识别人脑特定细胞类型恢复能力的关键分子驱动因素。 然后我们将使用来自许多不同的脑细胞对我们识别出的分子进行严格的测试 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变得更有弹性。 衰老和阿尔茨海默病的影响使该项目与之前的工作区分开来。 第一个方面是我们对个体细胞类型的关注通常，大脑数据的分子测量包含以下内容： 我们将使用单细胞单独测量每种细胞类型。 RNAseq (scRNAseq)，以确定哪些细胞类型与这些特定的 AD 恢复能力最相关。 我们将使用计算网络分析来识别细胞类型中较少数量的基因 这些预测促进了本研究的第二个方面，即影响弹性的分子系统。 不寻常的是，我们计划改变 AD 人类模型中的这些基因，我们将使用的模型是 来自 50 个个体的神经元和神经胶质细胞，对常见散发性病毒具有不同程度的恢复能力 我们将利用基因组工程来影响我们预测的基因丰度。 与所有这些细胞系的恢复能力相关，通过这种方式，我们可以检查由此产生的基因表达特征。 恢复力以及与健康认知相关的细胞表型，这些在 AD 中仍然存在 拟议的项目将提供一套全面的分子网络和关键分子。 它将通过打破常见的障碍来实现这一目标。 为了在这一领域取得进展：1）通过单细胞方法和计算准确识别目标 网络方法，2）在真实的人体模型中进行测试，所提出的项目将提供高可信度。 因此，该提案将对该领域产生强烈而持续的影响。