BIOMARKER DISCOVERY AND VALIDATION IN PSP

摘要 进行性核上性麻痹（PSP）是一种破坏性的非典型帕金森病，目前缺乏 有意义的对症治疗，缩短寿命，大大损害日常功能和生活质量。是 临床上通常难以与帕金森病（PD）区分，这对于适当和及时地治疗帕金森病至关重要。 管理、预后和临床试验入组。尽管迫切需要一种可靠的诊断标志物， 帕金森病，目前没有生物标志物可以用于常规临床实践， 区分PSP和PD。本项目的目的是发现脑脊液（CSF） 这些生物标志物可以可靠地区分PSP，PD和健康个体。很难确定 可靠的生物标志物可归因于临床样品的可变性， 参与PSP和PD的发病机制，以及在验证生物标志物候选物方面缺乏可重复性。 为了克服这些局限性，我们建议使用一个大的CSF队列，具有更大的统计功效， 发现，和深入的蛋白质组分析，以揭示PSP生物标志物参与PSP发病机制，但 以低丰度存在。此外，通过同量异位素串联质量标记的多重样品分析 (TMT)数据标准化的共同参考将确保定量分析的稳健分析精度 蛋白质组学数据用于从更大的样本集合中发现。此外，大脑的额外蛋白质组学分析 将使用组织来选择在CSF以及球中显示差异表达的那些生物标志物 苍白球，用于病理学定义PSP的代表性脑区域。这些发现平台将利用 一种生物信息学方法，用于选择最合理的候选物进行靶向验证研究， 对所发现的生物标志物候选物进行密集验证。为了实现这些目标，我们提出了四个目标： 具体目的1：前瞻性采集临床特征良好的PSP患者的CSF。具体目标 2：发现PSP患者与对照组和PD患者相比差异表达的蛋白质。我们 计划对PSP患者的CSF和苍白球样本进行定量蛋白质组学分析， 通过采用基于TMT的多路复用技术，通过这种方法，我们希望 获得更全面的覆盖范围，包括在分析的样品中定量的大量蛋白质。 具体目标3：根据CSF改变的综合分析，优先考虑PSP生物标志物候选物 和苍白球。通过网络方法整合CSF和脑组织中的表达变化 利用PSP中描述的已知生物途径，我们的建议将是 能够选择可靠的PSP生物标志物候选物，用于通过靶向PRM实验进行验证。具体目标4： 使用靶向平行反应监测（PRM）在较大队列中验证候选蛋白质生物标志物 使用来自约翰霍普金斯大学，密歇根大学， 宾夕法尼亚州，加州大学旧金山分校和PDBP。通过基于这些PRM实验的算法选择的生物标志物 最终将使用PSP的盲态PDBP CSF样本进行确认，并与CSF样本进行比较 从PD。通过上述方法，我们期望发现和验证可靠的PSP生物标志物 其以可再现的方式与PD区分。

ABSTRACT Progressive supranuclear palsy (PSP) is a devastating atypical parkinsonian disorder that currently lacks meaningful symptomatic therapies, reduces lifespan and greatly impairs daily function and quality of life. It is often difficult to distinguish from Parkinson disease (PD) clinically, which is crucial for appropriate and timely management, prognosis and clinical trial enrollment. Despite a critical need for a reliable diagnostic marker for parkinsonian disorders, there is currently no biomarker that can be used in routine clinical practice to distinguish between PSP and PD. The purpose of this project is to discover cerebrospinal fluid (CSF) biomarkers that reliably distinguish between PSP, PD and healthy individuals. The difficulty of identifying reliable biomarkers can be attributed to the variability of clinical samples, low abundance of proteins that are involved in the pathogenesis of PSP and PD, and the lack of reproducibility in validating biomarker candidates. To overcome these limitations, we propose use of a large CSF cohort with greater statistical power for true discovery, and deep proteome analysis to reveal PSP biomarkers that are involved in PSP pathogenesis, but are present at low abundance. In addition, multiplexed sample analysis by isobaric tandem mass tagging (TMT) with a common reference for data normalization will ensure robust analytical precision of quantitative proteomic data for discovery from a larger set of samples. Moreover, additional proteomic analysis of brain tissue will be used to select those biomarkers that show differential expression in CSF as well as the globus pallidus, a representative brain region used to pathologically define PSP. These discovery platforms will utilize a bioinformatics approach to select the most plausible candidates for targeted validation studies followed by an intensive validation of the discovered biomarker candidates. To achieve these goals, we propose four aims: Specific Aim 1: To prospectively collect CSF on patients with clinically well-characterized PSP. Specific Aim 2: To discover proteins that are differentially expressed in patients with PSP compared to controls and PD. We plan to carry out a quantitative proteomic analysis of CSF and globus pallidus samples from patients with PSP, PD and from controls by employing TMT-based multiplexing technology. With this approach, we expect to obtain a more comprehensive coverage of a larger number of proteins quantified across the analyzed samples. Specific Aim 3: To prioritize PSP biomarker candidates based on an integrative analysis of alterations in CSF and globus pallidus. By integrating the expression changes in CSF and brain tissue with a network approach that takes advantage of the known biological pathways that have been described in PSP, our proposal will be able to select reliable PSP biomarker candidates for validation by targeted PRM experiments. Specific Aim 4: To validate candidate protein biomarkers in a larger cohort using targeted parallel reaction monitoring (PRM) mass spectrometry using CSF samples from a PSP cohort at Johns Hopkins University, the University of Pennsylvania, UCSF and PDBP. Biomarkers that are selected by algorithms based on these PRM experiments will finally be confirmed using blinded PDBP CSF samples from PSP and will be compared to CSF samples from PD. Through the approaches outlined above, we expect to discover and validate reliable PSP biomarkers that are distinguishable from PD in a reproducible manner.