Cell Type-Specific Proteins that Promote Resilience to Cognitive Aging and Alzheimer's Disease

促进认知衰老和阿尔茨海默病恢复能力的细胞类型特异性蛋白质

• 批准号: 10846926
• 负责人: CATHERINE COOK KACZOROWSKI
• 金额: $ 155.84万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10846926
• 关键词: Age; Aging; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease patient; Amino Acids; Amyloid; Attention; Autopsy; Behavior; Cells; Chronology; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Cognitive; Cognitive aging; Cognitive deficits; Communities; Complex; DNA; Data; Data Set; Databases; Disease; Disease Progression; Electrophysiology (science); Environmental Risk Factor; Exhibits; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Engineering; Genetic Risk; Genetic Transcription; Genetic Variation; Genomics; Grant; Hand; Hippocampus; Human; Human Genetics; Human Genome; Immune; Impaired cognition; Individual; Ion Channel; Knowledge; Knowledge Portal; Label; Late Onset Alzheimer Disease; Learning; Link; Mediating; Memory; Memory impairment; Meta-Analysis; Metadata; Methods; Microglia; Molecular; Molecular Analysis; Molecular Target; Mouse Strains; Mus; Mutation; Neurobehavioral Manifestations; Neurons; Pathology; Pathway interactions; Patients; Phenotype; Population; Predisposition; Protein Biosynthesis; Proteins; Proteome; Proteomics; RNA; Research; Resources; Sampling; Shiga-Like Toxin I; Synapses; Synaptic plasticity; System; Technology; Testing; The Jackson Laboratory; Time; Transcript; Translating; Variant; Work; aging brain; asymptomatic Alzheimer' s disease; behavioral phenotyping; brain cell; brain tissue; candidate identification; cell type; cognitive function; cohort; data integration; drug discovery; familial Alzheimer disease; genetic approach; high dimensionality; high risk; human data; human model; human tissue; improved; knowledge base; mouse model; multidimensional data; neuroinflammation; neuronal excitability; neuropathology; novel; prevent; promote resilience; protective factors; protein expression; protein protein interaction; resilience; resilience factor; response; segregation; spatial memory; synaptic function; tau Proteins; therapeutic target; transcriptomics; usability

Resilience to brain aging and Alzheimer’s disease (AD) is a phenomenon whereby cognitive functioning is better than predicted based on chronological age, genetic risk and/or advanced neuropathology, likely because of the presence of as yet unidentified protective factors. These factors, once identified, are expected to provide key targets for treatment and prevention of AD. However, significant barriers limit discovery of the genetic mechanisms of resilience using human genetic methods alone, including: difficulties in identifying large numbers of individuals with asymptomatic AD, extracting age and interacting genetic effects from complex human genomes, controlling environmental factors, and obtaining brain tissue from asymptomatic AD cases. Moreover, it is well known that transcript abundance is not sufficient to infer protein abundance, as they differ spatially, temporally, and in response to learning tasks. Yet, our ability to discern how proteomes change across aging and AD progression is limited by the impossibility of longitudinal molecular analyses on human brain tissues, as well as the technology needed to profile cell type-specific proteomes associated with susceptibility versus resilience to AD. To fill these significant technological and knowledge gaps, here we will develop a robust pipeline using the most translationally relevant mouse models of human brain aging and AD (i.e., the AD-BXDs and their non-transgenic Ntg-BXDs controls) to obtain a longitudinal knowledge base of proteomes in specific cell types that we have found to exhibit robust changes in gene expression associated with highly susceptible and highly resilient phenotypes. We will focus on the hippocampus as it is required for spatial memory formation and recall in mice and humans, and hippocampus-dependent memory deficits are common in AD. Indeed, our work and preliminary data suggest that mouse strain differences in the age at onset and progression of cognitive deficits in the AD-BXDs (from extremely susceptible to resilient) result from cell type-specific differences in gene expression in the hippocampus. We will integrate these mouse data with clinical and omics data from NIA-sponsored AMP-AD and Resilience-AD Consortia to identify molecular drivers of cognitive resilience. In Aim 1, we will identify cell type-specific changes in neuron and microglia protein expression associated with resilience to AD using bioorthogonal non-canonical amino acid tagging (BONCAT) in AD-BXDs. In Aim 2, we will translate drivers and molecular networks underlying cognitive resilience to human AD cohorts. In Aim 3, we will leverage the unmatched genetic engineering resources at The Jackson Laboratory to functionally validate ‘in-hand’ resilience candidates by determining their effects on memory, hippocampal neuronal excitability, and synaptic plasticity in CRISPRed AD-BXDs. Using this pipeline, we will thereby discover novel and translationally relevant proteins and complexes for consideration under AMP-AD/TREAT-AD drug discovery pipelines to delay or prevent cognitive symptoms in susceptible AD mice, and ultimately AD patients.

对大脑衰老和阿尔茨海默病 (AD) 的抵抗力是一种认知功能比根据实际年龄、遗传风险和/或高级神经病理学预测的要好的现象，可能是因为存在尚未识别的保护因素。这些因素一旦确定，预计将为 AD 的治疗和预防提供关键目标。然而，仅使用人类遗传学方法发现恢复力的遗传机制存在重大障碍，包括：难以识别大量无症状 AD 个体、从复杂的人类基因组中提取年龄和相互作用的遗传效应、控制环境因素以及从无症状 AD 病例中获取脑组织。此外，众所周知，转录本丰度不足以推断蛋白质丰度，因为它们在空间、时间上和对学习任务的响应上有所不同。然而，由于无法对人脑组织进行纵向分子分析，以及分析与 AD 易感性和恢复力相关的细胞类型特异性蛋白质组所需的技术，我们辨别蛋白质组如何随着衰老和 AD 进展而变化的能力受到限制。为了填补这些重大的技术和知识空白，我们将开发一个强大的管道，使用与人类大脑衰老和AD最相关的小鼠模型（即AD-BXD及其非转基因Ntg-BXD对照）来获得特定细胞类型中蛋白质组的纵向知识库，我们发现这些细胞类型表现出与高度易感性和高度弹性表型相关的基因表达的强大变化。我们将重点关注海马体，因为它是小鼠和人类空间记忆形成和回忆所必需的，而海马体依赖性记忆缺陷在 AD 中很常见。事实上，我们的工作和初步数据表明，小鼠品系在 AD-BXD 认知缺陷（从极易感到弹性）的发病年龄和进展方面存在差异，是由于海马体中细胞类型特异性基因表达差异造成的。我们将把这些小鼠数据与 NIA 赞助的 AMP-AD 和 Resilience-AD Consortia 的临床和组学数据整合起来，以确定认知弹性的分子驱动因素。在目标 1 中，我们将使用 AD-BXD 中的生物正交非规范氨基酸标签 (BONCAT) 来识别与 AD 恢复能力相关的神经元和小胶质细胞蛋白表达的细胞类型特异性变化。在目标 2 中，我们将把认知弹性背后的驱动因素和分子网络转化为人类 AD 人群。在目标 3 中，我们将利用杰克逊实验室无与伦比的基因工程资源，通过确定 CRISPR 编辑的 AD-BXD 中的记忆、海马神经元兴奋性和突触可塑性的影响，对“现有”弹性候选者进行功能验证。利用这个管道，我们将因此发现新的和翻译相关的蛋白质和复合物，供在 AMP-AD/TREAT-AD 药物发现管道下考虑，以延迟或预防易感 AD 小鼠以及最终 AD 患者的认知症状。