The Phenotypic Landscape of Cognitive Decline as Revealed by Next-Generation Multiplexed Ion Beam Imaging

下一代多重离子束成像揭示认知衰退的表型景观

• 批准号: 9910356
• 负责人: Robert michael Angelo
• 金额: $ 51.42万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9910356
• 关键词: Abbreviations; Affect; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease risk; American; Amyloid beta-Protein; Apolipoprotein E; Biology; Brain; Brain region; Cessation of life; Color; Communities; Data; Disasters; Disease; Electrons; Family; Financial compensation; Fluorescence-Activated Cell Sorting; Formalin; Foundations; Funding; Gene Proteins; Generations; Genetic Predisposition to Disease; Genetic Risk; Genomics; Genotype; Goals; Healthcare Systems; Hippocampus (Brain); Human; Image; Image Analysis; Immune system; Immunohistochemistry; Impaired cognition; Infrastructure; Laboratories; Late Onset Alzheimer Disease; Longitudinal cohort; Malignant Neoplasms; Measurement; Middle frontal gyrus structure; Molecular; Multiplexed Ion Beam Imaging; Nerve Degeneration; Neurofibrillary Tangles; Neuroglia; Neurons; Paraffin Embedding; Participant; Pathogenicity; Pathologic; Pathway interactions; Phenotype; Population; Proteins; Public Health; Research; Resistance; Resolution; Resources; Role; Running; Scientist; Senile Plaques; Signal Transduction; Spectrometry, Mass, Secondary Ion; Surface; Synapses; Technology; Testing; Time; Translating; Work; aged; aging brain; area striata; burden of illness; collaborative approach; computational pipelines; data sharing; data warehouse; disability; gene product; high dimensionality; imaging modality; imaging platform; imaging study; innovation; insight; instrumentation; machine learning method; mental state; molecular imaging; molecular phenotype; multiplexed imaging; neuroinflammation; neuropathology; new therapeutic target; next generation; novel; paired helical filament; pre-clinical; predictive signature; repository; risk variant; statistical and machine learning; symposium; web portal

PROJECT SUMMARY/ABSTRACT Alzheimer's disease (AD) is a leading cause of disability and death in the US and a major global public health problem. Time is running short if we wish to avert a global public health disaster with untold suffering, disruption of families, and severe challenges to health care systems and economies. Solutions will come only from innovative research. Genomic studies for late-onset AD (LOAD) have identified over 20 risk loci; however, translating the relevant molecules identified by genomics to AD-specific mechanistic pathways has been challenging. Our application, entitled “The Phenotypic Landscape of Cognitive Decline Revealed by Next- Generation Multiplexed Ion Beam Imaging,” is highly responsive to this urgent scientific need by proposing a uniquely innovative molecular imaging platform called multiplexed ion beam imaging (MIBI) that will determine high dimensional protein interactions for AD-relevant molecules identified by genomics studies in normal and pathological states. Our proposal has three Specific Aims. In Aim 1, we propose to analyze four regions in healthy aged brains: two sectors of the hippocampal pyramidal layer and from two isocortical regions. Next- generation MIBI instrumentation will be used to image simultaneously 30+ proteins that mark subtypes of neurons, synapses, and non-neuronal cells, while covering regulatory signaling, neuro-inflammatory components, and AD risk gene protein products with subcellular resolution. In Aim 2, we propose to use the same multiplexed imaging methods in AD brain stratified by APOE genotype. We will analyze these data with statistical machine learning methods already established in our laboratory, similar to what we have done previously with different cancers and the immune system. In Aim 3, using infrastructure we have already have established, we will create a web-based portal where all of the images from this study can be accessed, multi- color overlays generated ad hoc, and all the features we derive shared freely. We propose a transformative, collaborative approach to AD that leverages a long-standing NIA-funded longitudinal cohort and is highly responsive to the National Alzheimer's Plan. These novel insights will illuminate pathways that hold potential for new therapeutic targets and will create a shared research resource and analysis platform for the community of scientists committed to developing solutions for AD.

项目总结/摘要 阿尔茨海默病（AD）是美国残疾和死亡的主要原因，也是全球主要的公共卫生问题。 问题.如果我们希望避免一场带来无尽痛苦的全球公共卫生灾难， 家庭破裂，卫生保健系统和经济面临严峻挑战。解决方案只会出现 从创新的研究。晚发性AD（LOAD）的基因组研究已经确定了20多个风险位点;然而， 将基因组学鉴定的相关分子转化为AD特异性机制途径， 挑战性我们的申请，题为“下一个揭示的认知衰退的表型景观- 第二代多路复用离子束成像”，是高度响应这一迫切的科学需要，提出了一个 独特的创新分子成像平台，称为多路复用离子束成像（MIBI），将确定 通过正常人和正常人的基因组学研究确定的AD相关分子的高维蛋白质相互作用 病理状态。我们的建议有三个具体目标。在目标1中，我们建议分析四个区域， 健康老年脑：海马锥体层的两个部分和两个等皮质区域。下一篇： 第二代MIBI仪器将用于同时成像30多种蛋白质，这些蛋白质标志着 神经元，突触和非神经元细胞，同时涵盖调节信号，神经炎性 成分和AD风险基因蛋白产物的亚细胞分辨率。在目标2中，我们建议使用 在按APOE基因型分层的AD脑中使用相同的多重成像方法。我们将分析这些数据， 我们实验室已经建立了统计机器学习方法，类似于我们所做的 之前有不同的癌症和免疫系统。在目标3中，利用我们已经拥有的基础设施， 我们将创建一个基于网络的门户网站，可以访问本研究的所有图像， 颜色覆盖生成的特设，和所有的功能，我们得到免费共享。我们提出了一个变革性的， AD的协作方法，利用长期的NIA资助的纵向队列， 响应国家老年痴呆症计划这些新的见解将照亮具有潜力的途径 新的治疗目标，并将为社区创建一个共享的研究资源和分析平台 致力于开发AD解决方案的科学家。