High-Throughput 3D Multiscale Mass Spectrometry Imaging for Understanding Neurochemical Heterogeneity in Alzheimer's Disease

高通量 3D 多尺度质谱成像用于了解阿尔茨海默病的神经化学异质性

• 批准号: 10516527
• 负责人: Fan Lam
• 金额: $ 74.72万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10516527
• 关键词: 3-Dimensional; Address; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease model; Amyloid; Amyloid beta-Protein Precursor; Amyloid deposition; Amyloidosis; Animal Model; Area; Atlases; Biochemical; Biological; Biological Markers; Brain; Brain Mass; Brain region; Cells; Characteristics; Chemicals; Cognitive; Computing Methodologies; Data; Dementia; Deposition; Deterioration; Disease; Disease Progression; Enhancement Technology; Exhibits; Fourier Transform; Gender; Generations; Healthcare; Heterogeneity; Hippocampal Formation; Hippocampus (Brain); Imaging Device; Imaging Techniques; Imaging technology; Impairment; Inflammatory; Knowledge; Life; Lipids; Magnetic Resonance Imaging; Maps; Mass Spectrum Analysis; Measurement; Memory; Memory Loss; Methods; Molecular; Molecular Bank; Molecular Profiling; Mus; Mutation; Neurofibrillary Tangles; Neurons; Pathologic; Phenotype; Play; Population; Portraits; Research; Resolution; Role; Sampling; Slice; Speed; Synapses; Tamoxifen; Technology; Tissue Model; Tissues; Wild Type Mouse; autosomal dominant Alzheimer' s disease; base; computer framework; data acquisition; data fusion; deep learning; dentate gyrus; early onset; effective intervention; entorhinal cortex; experimental group; experimental study; extracellular; frontier; human model; human tissue; imaging approach; imaging platform; innovation; insight; interest; mass spectrometric imaging; mouse model; multimodality; multiscale data; nestin protein; neurochemistry; neurogenesis; neuron development; neuron loss; new technology; novel; presenilin-1; presenilin-2; reconstruction; restoration; single cell analysis; spatial relationship; targeted treatment; therapeutic target; tool

PROJECT ABSTRACT: Understanding Alzheimer’s disease (AD) and identifying effective interventions are among the most exciting scientific frontiers and most critical healthcare challenges. While the roles of several pathological hallmarks of AD have been extensively studied, the biochemical alterations associated with these hallmarks and the mechanisms underlying progressive neuron loss and neuronal vulnerability in AD are not fully understood. Neurogenesis, a unique characteristic of the hippocampal formation, has been shown to play important roles in aging and AD progression. Abnormal early declines in neurogenesis have been observed in AD brains in both human and animal models, but the molecular profile of alterations in vulnerable brain circuits and neurons associated with varied neurogenesis have not been documented. Fourier transform mass spectrometry imaging (MSI) and single cell analyses allow for mapping and profiling hundreds to thousands of molecules in biological samples and single cells, providing unparalleled chemical insights relevant to AD as discussed above. However, several major challenges exist: (1) the limited throughput that prohibits the analysis of many tissue slices and samples; (2) the challenges associated with high-resolution volumetric reconstruction of biomolecular distributions for regional analysis across samples and experimental groups; (3) the need for integrating multiscale tissue MSI and single-cell MS data to relate cellular neurochemistry to tissue chemical heterogeneity. The proposed research addresses these challenges by developing a suite of novel mass spectrometry-based technologies and uses these technologies to map biomolecules related to AD and neurogenesis. Aim 1 develops a new technology to significantly enhances the throughput of FT-MSI by synergizing compressed sensing and deep learning, and a multimodal approach to integrate many MSI slices for 3D chemical atlases of AD and wild type mouse brain. Aim 2 develops an experimental framework to generate multiscale tissue MSI and single-cell MS data, a computational framework to jointly analyze these data, and -omics based molecular libraries to aid in interpreting the MSI and single cell data. Aim 3 leverages the tools developed in Aims 1 & 2 to determine the temporal and spatial signature of vulnerable circuits and neurons in a FAD mouse model of AD. Aim 4 investigates the effects of hippocampal neurogenesis on neuronal vulnerability and AD progression using the new multiscale MSI technology, as well as creates 3D chemical atlas of the mouse brain. The proposed research, synergistic with both technology- and hypothesis- driven aims, will expand the technological envelop of MSI and transform how high-resolution MSI data are generated and analyzed. The proposed measurements will address critical knowledge gaps on the mechanism underlying neuronal vulnerability in AD, potentially identifying new biomarkers and therapeutic targets.

项目摘要： 了解阿尔茨海默氏病（AD）并确定有效的干预措施是最重要的 令人兴奋的科学领域和最关键的医疗保健挑战。而几个角色 AD的病理标志已广泛研究，与 这些标志和渐进神经元丧失和神经元脆弱性的机制 广告没有完全理解。神经发生是海马形成的独特特征，具有 我们被证明在衰老和AD进展中起着重要作用。异常早期下降 在人类和动物模型中，在AD大脑中已经观察到了神经发生，但是分子 与不同神经发生相关的脆弱脑回路和神经元改变的变化的概况 没有记录。傅立叶变换质谱成像（MSI）和单细胞分析 允许在生物样品和单个的生物样品中映射和分析数百至数千分子 如上所述，细胞提供与AD相关的无与伦比的化学见解。但是，有几个 存在重大挑战：（1）有限的吞吐量，禁止分析许多组织切片和 样品； （2）与生物分子的高分辨率体积重建相关的挑战 分布在样品和实验组之间进行区域分析； （3）需要集成 多尺度组织MSI和单细胞MS数据，以将细胞神经化学与组织化学相关联 异质性。拟议的研究通过开发一套新颖的质量来解决这些挑战 基于光谱的技术并使用这些技术来绘制与AD和AD相关的生物分子 神经发生。 AIM 1开发了一项新技术，以显着增强FT-MSI的吞吐量 协同压缩感官和深度学习，以及一种整合许多MSI的多模式方法 AD和野生型小鼠脑的3D化学图集的切片。 AIM 2发展实验 生成多尺度组织MSI和单细胞MS数据的框架，这是一个计算框架 共同分析这些数据和基于 - 组的分子库，以帮助解释MSI和单个 单元数据。 AIM 3利用目标1和2中开发的工具来确定临时和空间 AD的FAD小鼠模型中脆弱电路和神经元的签名。 AIM 4调查 海马神经发生对使用新的神经元脆弱性和AD进展的影响 多尺度MSI技术，并创建了小鼠大脑的3D化学图集。提议 研究，与技术和假设驱动的目的协同作用，将扩大技术 MSI的包膜并改变了如何生成和分析高分辨率MSI数据的方式。提议 测量将解决有关神经元脆弱性机制的关键知识差距 在AD中，有可能识别新的生物标志物和治疗靶标。