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.

对大脑老化和阿尔茨海默病(AD)的复原力是一种现象，根据年龄、遗传风险和/或高级神经病理学，认知功能比预测的要好，这可能是因为存在尚不确定的保护因素。一旦确定了这些因素，预计将为AD的治疗和预防提供关键目标。然而，巨大的障碍限制了仅使用人类遗传方法发现弹性的遗传机制，包括：难以识别大量无症状AD患者，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，转录的丰度不足以推断蛋白质的丰度，因为它们在空间上、时间上和对学习任务的反应是不同的。然而，我们识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，因为不可能对人脑组织进行纵向分子分析，以及描述与AD易感性和韧性相关的细胞类型特定蛋白质组所需的技术。为了填补这些重大的技术和知识空白，在这里，我们将使用翻译上最相关的人脑衰老和AD的小鼠模型(即AD-BXD及其非转基因NTG-BXD对照)来开发一个强大的管道，以获得特定细胞类型的蛋白质组的纵向知识库，我们发现这些蛋白质组显示出与高度敏感和高弹性表型相关的基因表达的强劲变化。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记忆所必需的，而海马体依赖的记忆缺陷在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(从极度敏感到有弹性)的发病和进展年龄上的差异是由于海马区基因表达的细胞类型差异造成的。我们将把这些小鼠数据与NIA赞助的AMP-AD和Resilience-AD联盟的临床和组学数据结合起来，以确定认知弹性的分子驱动因素。在目标1中，我们将使用生物正交非典型氨基酸标签(BONCAT)在AD-BXD中识别与AD复原性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，我们将把潜在的认知弹性的驱动因素和分子网络转化为人类AD队列。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，通过确定它们对记忆、海马神经元兴奋性和CRISPRed AD-BXD突触可塑性的影响，从功能上验证“手持”韧性候选。使用这条管道，我们将因此发现新的和翻译相关的蛋白质和复合体，供在AMP-AD/Treat-AD药物发现管道下考虑，以延迟或预防易感AD小鼠的认知症状，并最终预防AD患者。