Integrative analysis of proteomics and transcriptomics to delineate vesicular transport related protein abnormalities related to Alzheimer's, Lewy body and mixed Pathologies

项目总结/摘要 痴呆症在全球范围内具有重大的疾病负担，约有5000万人患有痴呆症。 阿尔茨海默病（AD）是痴呆的最常见病因，其特征在于淀粉样蛋白的异常积累 β（A β）和tau蛋白。在AD之后，路易体痴呆（DLB）通常是最常见的疾病之一。 两种常见的痴呆形式，包括α-突触核蛋白（α-syn）神经元包涵体作为关键病理 标记。即使AD和DLB是常见的，神经病理学研究也一直注意到， 单一基础病因，患者中有一种以上病理（混合病理）的频率较高 会导致痴呆综合症当这些病理一起发生时， 神经变性的开始和发展以及认知衰退的发展还有待于 全面理解。 R21的基础研究是一项临床转化研究，使用系统生物学， 蛋白质组学技术，以表征差异表达的基因和蛋白质之间的属性， 仅患有AD或DLB病理学的患者，以及在患有AD和DLB的混合性痴呆病理学的患者中， DLB病理学。在这项工作中，我们将澄清，如果有一个机械的原因，一些大脑更容易发展 ADP-LRP（A β-α-syn）的混合病理学优于主要具有A β或α-syn的其他病理学。既往AD研究 和DLB表明内体-溶酶体途径的失调。在这些先前的研究中， 通常包括混合病理学，解开内体-溶酶体的作用一直是具有挑战性的。 每种病理的失调。我们的初步数据使我们假设A β的存在 脑中的病理学沿着共存的细胞囊泡转运异常使得更有可能 包括ADP-LRP在内的混合病理的发展。我们将通过蛋白质组学和 三个患者组（AD、DLB和混合AD-DLB）的脑、CSF和血浆的转录组学评价，以及 在年龄和性别匹配的正常对照组中。我们将确认和验证我们的数据对其他数据 大型国家数据（ADNI，加速药物合作伙伴关系-AD）。我们将开发一个模型范例来评估 囊泡转运蛋白在遗传、转录和免疫系统中的作用 蛋白质组水平如果假设和模型得到验证，这项研究的科学见解将有助于确定 这些病理之间的协同关系的性质，以开发更好的治疗靶向的混合 病理性痴呆如果假设被发现是不正确的，这项研究的结果仍然代表一个 在我们对个体蛋白质组学和转录组学特征的变异性的认识方面取得了重大进展， 神经退行性疾病病理学的面孔。这一结果将有助于临床和设计 并解释未来的研究成果。

PROJECT SUMMARY/ABSTRACT Dementia has a significant disease burden worldwide with around 50 million people having it. Alzheimer’s disease (AD), the most common etiology of dementia is characterized by abnormal accumulation of amyloid beta(Aβ) and tau proteins in the brain. After AD, dementia with Lewy bodies (DLB) is often noted among the top two common forms of dementia and includes α-synuclein protein (α-syn) neuronal inclusions as a key pathology marker. Even as AD and DLB are common, neuropathology studies have consistently noted that rather than a single underlying etiology, there is a high frequency of patients where more than one pathology (mixed pathology) contributes to the dementia syndrome. The pathophysiological impact of these pathologies when together, on the initiation and progression of neurodegeneration and development of cognitive decline is yet to be comprehensively understood. The research at the foundation of this R21 is a clinical translational study that uses systems biology and proteomics techniques to characterize the properties of differentially expressed genes and proteins between patients with AD or DLB pathology alone and among those patients with mixed dementia pathology of AD and DLB pathology. In this work we will clarify if there is a mechanistic reason some brains are more prone to develop mixed pathology of ADP-LRP (Aβ-α-syn) over others that have predominantly Aβ or α-syn. Prior studies in AD and DLB suggest dysregulation of endosomal-lysosomal pathways. As clinical AD dementia in these prior studies often included mixed pathology, it has been challenging to disentangle the role for endosomal-lysosomal dysregulation for each individual pathology. Our preliminary data leads us hypothesize that presence of Aβ pathology in the brain along with co-existing cellular vesicular transport abnormalities makes it more likely for the development of mixed pathologies including ADP-LRP. We will evaluate this hypothesis by proteomic and transcriptomic evaluation of brain, CSF and plasma of three patient groups (AD, DLB and mixed AD-DLB) and among age and sex matched normal controls. We will confirm and validate our data against data from other large national data (ADNI, Accelerating Medicines Partnership-AD). We will develop a model paradigm to assess the role for dysregulation of vesicular transport proteins in mixed pathologies at the genetic, transcriptional and proteomic levels. If the hypothesis and models are validated, scientific insights from this research will help identify the nature of synergistic relationship between these pathologies to develop better therapeutic targeting of mixed pathology dementia. If the hypothesis is found to be not true, the findings from this study will still represent a significant advance in our knowledge of variability in individual proteomic and transcriptomic signatures in the face of neurodegenerative disease pathology. The results of this will be useful both clinically and in designing and interpreting future research outcomes.