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： 了解阿尔茨海默病 (AD) 并确定有效的干预措施是最重要的 令人兴奋的科学前沿和最关键的医疗保健挑战，而几个角色。 AD 的病理特征已被广泛研究，与相关的生化改变 这些特征以及进行性神经丧失和神经脆弱性的潜在机制 AD 尚未完全了解，神经发生是海马结构的独特特征。 已被证明在衰老和 AD 进展的异常早期衰退中发挥重要作用。 在人类和动物模型的 AD 大脑中都观察到神经发生，但分子 与不同神经发生相关的脆弱大脑回路和神经元的变化概况 尚未记录傅里叶变换质谱成像（MSI）和单细胞分析。 允许对生物样本和单个分子中数百至数千个分子进行绘图和分析 细胞，提供了与上面讨论的 AD 相关的无与伦比的化学见解。 存在的主要挑战：(1) 吞吐量有限，无法对许多组织切片进行分析； 样品；（2）与生物分子高分辨率体积重建相关的挑战 跨样本和实验组的区域分析分布；（3）整合的需要 多尺度组织 MSI 和单细胞 MS 数据，将细胞神经化学与组织化学联系起来 拟议的研究通过开发一套新颖的质量来解决这些挑战。 基于光谱测定的技术，并使用这些技术来绘制与 AD 相关的生物分子图谱 Aim 1 开发了一种新技术，通过显着提高 FT-MSI 的吞吐量。 协同压缩感知和深度学习，以及集成许多 MSI 的多模态方法 Aim 2 开发了 AD 和野生型小鼠大脑的 3D 化学图谱切片。 生成多尺度组织 MSI 和单细胞 MS 数据的计算框架 共同分析这些数据，并基于组学的分子库来帮助解释 MSI 和单个 目标 3 利用目标 1 和 2 中开发的工具来确定时间和空间数据。 Aim 4 研究了 AD 小鼠模型中脆弱电路和神经元的特征。 使用新方法研究海马神经发生对神经元脆弱性和 AD 进展的影响 多尺度 MSI 技术，以及创建小鼠大脑的 3D 化学图谱。 研究与技术和假设驱动的目标相协同，将扩大技术范围 MSI 的包络并改变高分辨率 MSI 数据的生成和分析方式。 测量将解决神经脆弱性背后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点。