ANALYSIS OF PROTEOMIC PATTERNS IN NEURODEGENERATION

这项研究的长期目标是识别和验证神经退行性变发展中的蛋白质组学变化。阿尔茨海默病（Alzheimer's disease，AD）和帕金森病（Parkinson's disease，PD）是两种最常见的神经退行性疾病。尽管AD和PD被认为是不同的疾病，但存在显着的重叠。轻度认知障碍（MCI）是介于健康老龄化和痴呆之间的一种短暂状态，通常代表与退行性痴呆疾病相关的认知衰退的非常早期阶段。在组织学上，异常蛋白质的积累已被认为是AD和PD中神经变性的标志，这表明在AD、PD和AD/PD重叠疾病中共有的分子机制可能介导神经变性的发病机制。使用新的基于质谱的技术，我们将测试我们的中心假设：泛素化蛋白质组和突触后蛋白质组的变化将揭示AD，PD和AD/PD重叠综合征之间的分子共性，蛋白质模式的变化将伴随疾病从MCI到AD的演变。我们 将使用临床上充分表征的人类死后样本来评估泛素化蛋白质组和突触后密度（PSD）中的蛋白质模式变化。将对MCI、AD、PD和AD/PD重叠疾病的样本进行分析和比较，以发现共享的蛋白质模式。这些蛋白质变化将在大量疾病病例中得到进一步证实。这些结果将能够识别潜在的生物标志物，并为后续的神经变性研究提供关键的分子图谱。

The long-term goal of this research is to identify and validate the proteomic changes in the development of neurodegeneration. Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most common neurodegenerative diseases. Although AD and PD are considered distinct disorders, significant overlap occurs. Mild cognitive impairment (MCI) is a transient state between healthy aging and dementia, often representing a very early stage of cognitive decline associated with a degenerative dementing illness. Histopathologically, accumulation of abnormal proteins has been recognized as hallmarks of neurodegeneration in both AD and PD, suggesting that shared molecular mechanisms may mediate the pathogenesis of neurodegeneration in AD, PD, and AD/PD overlap disorders. Using novel mass spectrometry-based technologies, we will test our central hypothesis: changes in the ubiquitinated proteome and the postsynaptic proteome will reveal molecular commonality among AD, PD, and AD/PD overlap syndromes, and changes in protein patterns will accompany the evolution of disease from MCI to AD. We will use clinically well-characterized human postmortem samples to evaluate protein pattern changes in the ubiquitinated proteome and in the postsynaptic density (PSD). Samples of MCI, AD, PD and AD/PD overlap disease will be analyzed and compared to discover shared protein patterns. These protein changes will be further confirmed in a large set of disease cases. The results will enable the identification of potential biomarkers and provide critical molecular maps for subsequent studies of neurodegeneration.