Elucidating Molecular Drivers of Aging and Alzheimer's Disease via Multimodal Imaging Mass Spectrometry

项目总结：拟议工作的总体目标是应用一个集成的 多组成像模式和空间分辨分子表征技术到正常 衰老和阿尔茨海默病脑组织，以发现和定义关键分子和 驱动疾病潜在异质性的途径。这项工作将利用独特的 质谱学研究中心和弗吉尼亚大学生物分子成像中心的资源 作为世界一流的范德比尔特大学医学中心的临床环境，以及先进的 通过范德比尔特大学的数据分析实验室提供生物计算基础设施 以及代尔夫特理工大学。我们拟议工作的主要目标，我们认为 将推动这一领域向前发展，是：(1)在一个 一种新的和强大的方法来创建观察到的异种神经病理的分子图谱 人脑组织，(2)定义神经炎斑块和神经原纤维的分子基础 缠结与参与神经病理的通路重叠，以提供更准确的信息 开发实验性疗法；以及(3)部署多组学工具来记录细胞类型特异性 正常衰老与阿尔茨海默病分子变化的显微解剖学研究 代谢组、脂组、蛋白质组和转录组的变化可以归因于 正确的细胞类型和微环境。有了这套技术，高级数据分析 能力，以及在开发适龄健康人体组织图谱方面的先前经验，该团队将 以前所未有的细节生成数据集，并具有推动分子发现的潜力。至 为了实现这些目标，我们组建了一个互动的、成熟的调查团队，包括 在阿尔茨海默病、细胞生物学、分析化学和数据科学方面的互补专业知识； 并可直接在内部使用先进的仪器和设施。我们相信我们的空间 解决和分子综合的方法将导致更好的机制理解 阿尔茨海默氏症和这些洞察力可以提供更好的治疗选择。

PROJECT SUMMARY: The overarching goal of the proposed work is to apply a platform of integrated multiomic imaging modalities and spatially resolved molecular characterization technologies to normal aging and Alzheimer’s disease brain tissues in order to discover and define key molecules and pathways that drive the underlying heterogeneity of the disease. This work will leverage the unique resources of the Mass Spectrometry Research Center and VU Biomolecular Imaging Center, as well as the world-class clinical environment of the Vanderbilt University Medical Center, and the advanced biocomputational infrastructure available through the data analysis laboratories at Vanderbilt University and the Delft University of Technology. The main objectives of our proposed work, which we believe will move the field forward, are to: (1) engage the molecular complexities of Alzheimer’s disease in a new and robust way to create molecular atlases of the heterogenous neuropathologies observed in human brain tissue, (2) define how the molecular underpinnings of neuritic plaques and neurofibrillary tangles overlap with pathways implicated in contributory neuropathologies to inform more precise development of experimental therapies; and (3) deploy multiomic tools to document cell-type specific molecular changes between normal aging and Alzheimer’s disease in well-defined microanatomical regions so changes in the metabolome, lipidome, proteome, and transcriptome can be attributed to the correct cell types and microenvironment. With this suite of technologies, advanced data analysis capabilities, and prior experience in developing atlases of healthy-for-age human tissues, this team will generate datasets with unprecedented detail and the potential to drive molecular discovery. To accomplish these aims, we assembled an interactive and established team of investigators, covering complementary expertise in Alzheimer’s disease, cell biology, analytical chemistry, and data science; and with direct in-house access to advanced instrumentation and facilities. We believe that our spatially resolved and molecularly comprehensive approach will lead to improved mechanistic understanding of Alzheimer’s disease and that these insights could inform better treatment options.