Mass spectrometry and multiplexed immunofluorescence imaging of metabolic and proteomic contributors to selective neuronal vulnerability in Alzheimer's disease

阿尔茨海默病选择性神经元脆弱性的代谢和蛋白质组学贡献者的质谱和多重免疫荧光成像

• 批准号: 10704682
• 负责人: PARAG Kumar MALLICK
• 金额: $ 86.05万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 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/10704682
• 关键词: Address; Affect; Alzheimer' s Disease; Alzheimer' s disease pathology; Architecture; Area; Autopsy; Blood Vessels; Brain; Brain region; Cells; Chimera organism; Classification; Clinical; Computer Vision Systems; Data; Data Set; Detection; Development; Disease; Disease Progression; Disease susceptibility; Energy Metabolism; Environment; Exhibits; Experimental Models; Feasibility Studies; Future; Genetic; Goals; Human; Image; Imaging Device; Imaging Techniques; Immunofluorescence Immunologic; In Situ; Individual; Inflammation; Intervention; Knowledge; Laboratories; Location; Machine Learning; Mass Spectrum Analysis; Measures; Metabolic; Metabolic Pathway; Modality; Modeling; Molecular; Molecular Profiling; Morphology; Mus; Myelin; Neighborhoods; Neocortex; Nerve Degeneration; Neuroglia; Neurons; Organoids; Outcome Study; Oxidative Stress; Pathologic; Pathway interactions; Pattern; Phase; Phenotype; Pilot Projects; Population; Predisposition; Prefrontal Cortex; Proteins; Proteomics; Pyramidal Cells; Resistance; Resolution; Senile Plaques; Severities; Signal Pathway; Signal Transduction; Signaling Protein; Slide; Spatial Distribution; Specimen; Testing; Tissue Microarray; Tissue Stains; Tissues; Validation; Visual; area striata; biomarker identification; cell type; comparative; comparison control; data integration; density; differential expression; gray matter; hippocampal pyramidal neuron; humanized mouse; imaging capabilities; imaging detection; imaging modality; imaging study; insight; large datasets; mass spectrometric imaging; metabolic imaging; metabolic profile; molecular imaging; molecular phenotype; neocortical; neuroinflammation; neuropathology; novel; protein aggregation; regional difference; resilience; risk variant; segregation; small molecule; spatial relationship; tau aggregation; tool; transcriptomics; white matter

We aim to uncover metabolic and protein signaling pathways contributing to the regional vulnerability of neocortical pyramidal neurons in Alzheimer's disease and to identify novel targets for detection and intervention. We will compare the prefrontal cortex, a neocortical brain area afflicted by neuropathology early in Alzheimer's disease, with the primary visual cortex, a brain area that is relatively spared. We will use mass spectrometric imaging in combination with segmentation analyses, to identify spatial changes of small molecules and proteins in postmortem brain sections prepared from these neocortical areas from donors at various clinical and pathological stages of Alzheimer's disease compared to controls. Then, we will apply multiplexed immunofluorescence imaging on sequential sections from the same specimens, to obtain information on cellular and microenvironment changes in and around vulnerable neocortical neurons during disease progression, correlated with the clinical severity, degree and location of neuropathological changes, and the risk genotype. Further, we will register the data from both imaging techniques to identify metabolic pathways and protein signaling changes at the regional, laminar and cellular level and to locate covariation in molecular and cellular phenotypes contributing to Alzheimer's disease vulnerability. In addition to generating a comprehensive dataset of the cellular and molecular changes at various stages of Alzheimer's disease, these studies will involve the development, validation, and dissemination of novel tools for analysis of large datasets generated using two powerful imaging tools, one that detects hundreds of analytes with the possibility of detecting previously unknown contributors to disease and the other that provides higher resolution with a select set of known markers. In the long term, the data generated from these studies could provide the basis for testing novel disease- modifying treatments by cell-type specific targeting of identified metabolic pathways using experimental models, such as brain organoids to replicate cortical lamination with human neurons or humanized mouse chimeras to model interactions between neurons and non-neuronal cell types.

我们的目标是发现代谢和蛋白质信号通路导致局部易损性。 阿尔茨海默病中的新皮质锥体神经元和识别新的检测和 干预。我们将比较前额叶皮质，这是一个受神经病理影响的大脑新皮质区域 在阿尔茨海默病的早期，初级视觉皮质是一个相对幸免的大脑区域。我们会 将质谱学成像与分段分析相结合，以识别空间变化 从这些新皮质区域制备的尸检脑切片中的小分子和蛋白质 将阿尔茨海默病不同临床和病理阶段的捐赠者与对照组进行比较。然后，我们 将在同一标本的连续切片上应用多路免疫荧光成像，以 获取有关易受攻击的新皮质内及其周围细胞和微环境变化的信息 疾病进展过程中的神经元，与临床严重程度、程度和位置相关 神经病理改变和危险基因。此外，我们将配准来自两个成像的数据 确定代谢途径和蛋白质信号变化的技术在区域、层流和 细胞水平并定位导致阿尔茨海默病的分子和细胞表型的协同变异 疾病的脆弱性。除了生成细胞和分子的全面数据集之外 阿尔茨海默病不同阶段的变化，这些研究将涉及发展，验证， 和传播用于分析使用两个强大的成像生成的大数据集的新工具 工具，一种检测数百种分析物的工具，可以检测到以前未知的 一种是疾病的诱因，另一种是通过一组精选的已知标志物提供更高分辨率的。 从长远来看，这些研究产生的数据可以为测试新的疾病提供基础- 通过实验确定的代谢途径的细胞类型特异性靶向来修改治疗 模型，如用人类神经元或人源化小鼠复制皮质层的脑有机体 嵌合体来模拟神经元和非神经元细胞类型之间的相互作用。