High-resolution multiplex localization of Alzheimer’s disease risk and resilience factors

阿尔茨海默病风险和恢复因素的高分辨率多重定位

• 批准号: 10670488
• 负责人: DANIEL A NICHOLSON
• 金额: $ 60.7万
• 依托单位: RUSH UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2023-06-19
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10670488
• 关键词: Age-associated memory impairment; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease model; Alzheimer' s disease pathology; Alzheimer' s disease risk; Amyloidosis; Antibodies; Array tomography; Astrocytes; Autopsy; Behavioral; Binding; Brain; Brain imaging; Brain region; Cells; Clinical; Cognition; Cognitive; Consensus; Deposition; Diagnosis; Disease Progression; Elderly; Electron Microscopy; Epitopes; Excitatory Synapse; Future; Genes; Genetic; Genetic Risk; Genomics; Glial Fibrillary Acidic Protein; Human; Human Gene Mapping; Image; Immunofluorescence Immunologic; Impaired cognition; Impairment; Individual; Inhibitory Synapse; Knock-in; Link; Magnetic Resonance Imaging; Maps; Microglia; Modeling; N-Methylaspartate; Neurobiology; Neurofibrillary Tangles; Neurons; Neuropil; Normalcy; Pathogenesis; Pathologic; Pathology; Pattern; Persons; Population; Prefrontal Cortex; Presynaptic Terminals; Proteins; Proteomics; Relaxation; Resolution; Risk; Rodent; Rodent Model; Selection for Treatments; Senile Plaques; Severities; Severity of illness; Structural defect; Susceptibility Gene; Synapses; Synapsins; Systems Biology; Techniques; Temporal Lobe; Therapeutic Studies; Tracer; Transgenic Organisms; Validation; Water; asymptomatic Alzheimer' s disease; brain tissue; cell type; comorbidity; drug candidate; frontal lobe; gephyrin; gray matter; human model; human tissue; imaging study; insight; preservation; protein expression; receptor; resilience; sex; submicron; transcriptome sequencing; transcriptomics; vesicular GABA transporter; white matter

What distinguishes persons with Alzheimer’s disease (AD) or other age-related cognitive impairments from age- and sex-matched cognitively healthy individuals, and what distinguishes these two populations from those who are of very advanced age with preserved cognition (e.g., Super Agers), has been intensely investigated for decades. A multitude of techniques and approaches has provided key insights, but the consensus is that some still-unknown combination of parameters is the most likely explanation. Recent systems biology studies have identified genetic networks that are linked to AD risk, resilience, severity, or pathology, which can be consid- ered “interactomes” that promote or protect against AD progression and pathogenesis, referred to here as the m109 and the BIN1 interactomes. Recent studies examining these interactomes with targeted proteomics in the human dorsolateral prefrontal cortex (dlPFC) have expanded this tight linkage to the proteomic level. As the genomic landscape conferring either risk of, or resilience to, AD continues to be established, determining the neuroanatomical expression patterns of the proteins encoded by these genes is critical. Moreover, how their expression patterns relate to each other and to individual cell-types is crucial for understanding why these net- works are implicated in AD. Furthermore, expression patterns of these interactomes may differ substantially in regions with AD-linked pathology as compared to adjacent, pathology-lacking microregions. This application is relevant to NOT-AG-19-033 and proposes three Aims that build upon recent RNAseq/genomic/proteomic studies using a combination of high-resolution immunolocalization techniques that will uniquely generate neu- roanatomical expression patterns with multiplexed detail using both immunofluorescence array tomography and immunogold electron microscopy in AD, asymptomatic AD, non-cognitively impaired, and Super Ager dlPFC. The overarching hypothesis is that proteins encoded by the genetic risk/resilience interactomes are mis- localized or aberrantly expressed in AD brain and cortical white matter with MRI abnormalities. Aim 1 will de- termine the expression patterns of proteins encoded by the m109 and BIN1 interactomes in relation to synaptic markers in the dlPFC neuropil. Aim 2 determine the expression patterns of proteins encoded by the m109 and BIN1 protein clusters in relation to AD pathology in both the dlPFC gray matter and white matter. Aims 1 and 2 will also include examination of protein expression patterns in behaviorally characterized rodent models of AD to establish cross-species validation of distributional motifs in human dlPFC and rodent prelimbic cortex. Aim 3 will determine the expression patterns of proteins encoded by the m109 and BIN1 protein clusters in relation to the MRI abnormalities in human frontal and temporal cortex white matter. The main deliverable is to use distributional motifs of risk and resilience factors, considered in aggregate with the most recent transcriptomic and proteomic information from the Rush Alzheimer’s Disease Center and others, to identify high-confidence hits for future mechanistic perturbation and therapeutic studies.

阿尔茨海默病（AD）或其他与年龄相关的认知障碍患者与 年龄和性别匹配的认知健康个体，以及这两个群体与那些 具有保留的认知的非常高龄的人（例如，超级老年人），一直在激烈的调查， 几十年许多技术和方法提供了关键的见解，但共识是， 最有可能的解释是未知的参数组合。最近的系统生物学研究 确定了与AD风险、恢复力、严重程度或病理学相关的遗传网络，可以认为- 促进或防止AD进展和发病的已知“相互作用组”，在此称为“相互作用组”。 m109和BIN 1相互作用组。最近的研究用靶向蛋白质组学检查了这些相互作用组， 人类背外侧前额叶皮层（dlPFC）已经将这种紧密联系扩展到蛋白质组水平。为 赋予AD的风险或对AD的恢复力的基因组格局继续建立，决定了AD的发病率。 由这些基因编码的蛋白质的神经解剖学表达模式是至关重要的。此外，他们的 表达模式相互关联，并与个别细胞类型是至关重要的理解为什么这些净， 作品与AD有关。此外，这些相互作用组的表达模式可能在以下方面有实质性差异： 与相邻的病理学缺乏的微区域相比，具有AD相关病理学的区域。本申请是 与NOT-AG-19-033相关，并提出了三个基于最近RNAseq/基因组学/蛋白质组学的目标 研究使用高分辨率免疫定位技术的组合，将独特地产生neu， 使用免疫荧光阵列断层扫描和免疫荧光阵列断层扫描的具有多重细节的解剖学表达模式 AD、无症状AD、非认知功能受损和超级AD患者的免疫金电子显微镜检查 dlPFC。总体假设是，由遗传风险/弹性相互作用组编码的蛋白质是错误的， MRI异常的AD脑和皮质白色物质中存在局限性或异常表达。目标1将- 确定由m109和BIN 1相互作用体编码的蛋白质在突触后的表达模式， 标记物在dlPFC神经元中。目的2确定m109编码蛋白的表达模式， BIN 1蛋白簇与dlPFC灰质和白色物质中的AD病理学相关。目标1和2 还将包括在行为特征的AD啮齿动物模型中检查蛋白质表达模式 建立跨物种验证的分布图案在人类dlPFC和啮齿动物前边缘皮层。目的 3将确定由m109和BIN 1蛋白簇编码的蛋白质的表达模式， 人类额叶和颞叶皮质白色物质的MRI异常。主要的可交付成果是使用 风险和弹性因素的分布基序，与最近的转录组学研究一起考虑。 和来自拉什阿尔茨海默病中心和其他人的蛋白质组信息，以确定高置信度 为未来的机械扰动和治疗研究提供了新的突破。