Project 1: Discovery of proteins with altered abundance and stability

摘要 尽管CSF Aβ42、tau蛋白、磷酸化tau蛋白水平与基础AD之间存在相关性， 在病理学方面，用于临床诊断的生物标志物准确性的测量在研究之间变化很大。鉴于 其他神经退行性疾病可表现为AD样临床症状， 经常有共病的病理，需要额外的标志物，可以帮助鉴别诊断， 识别混合病理。在过去的十年中，已经鉴定了许多候选生物标志物，反映了 一系列病理生理过程，包括胆固醇代谢、神经炎症和淀粉样蛋白 处理.然而，很少有在临床实践中采用或在大规模独立研究中得到验证。 队列1. MacCoss实验室和其他人一直在开拓下一代蛋白质组学方法的发展 作为经典的基于随机质谱的方法的替代。这些新方法提供了一个 目标蛋白质组学策略和全局蛋白质组学策略之间的混合。虽然质谱数据收集在 以无偏的方式，以靶向策略分析数据，其中分析特定肽，尽管分析了1000个 利用先验信息。因此，可重复的靶向、通量和基于MS/MS的置信度 平行反应监测（PRM）的定量可以与经典发现方法的能力相结合， 来定性检测成千上万的蛋白质。这些新方法基于系统收集的质量 光谱数据可以提供类似的定量品质因数，并且可以以类似的方式验证， 临床分析。 尽管蛋白质组学技术取得了进展，但大多数发现新CSF标志物的尝试要么 使用1）随机采样方法（例如，数据相关采集）， 性能，2）小样本队列，3）完全关注总CSF，4）忽略蛋白质加工，以及5） 没有考虑蛋白质的错误折叠或稳定性。本项目的目的是在合作研究 我们的计划是把我们的方法提升到另一个层次--把真正的定量方法应用到大油井上 特征化的队列，并将其扩展到功能相关的亚群。 我们有一种CSF检测方法，可以从完全未分级的材料中测量>1050种蛋白质， 日内/日间精密度、线性、LOD/LOQ等优点。此外，我们可以将该测定用于 CSF蛋白质组的子集，以评估神经生物学的功能相关方面，包括数量， 部分溶液或CSF颗粒、完整蛋白质MW和蛋白质稳定性。最后，我们有足够的吞吐量 应用这些分析的规模足以消除观察是由于异常的机会 亚群

Abstract Despite the association between the levels of CSF Aβ42, tau, phosphorylated tau and underlying AD pathology, measures of biomarker accuracy for clinical diagnosis vary widely between studies. Given that other neurodegenerative conditions can present with AD-like clinical symptoms, and individuals with AD frequently have comorbid pathologies, additional markers are needed that can aid in differential diagnosis and identify mixed pathologies. Over the last decade, many candidate biomarkers have been identified, reflecting a range of pathophysiological processes including cholesterol metabolism, neuroinflammation and amyloid processing. However, few, have been adopted in clinical practice or been validated in large independent cohorts1. The MacCoss lab and others have been pioneering the development of next generation proteomics methods as an alternative to the classic stochastic mass spectrometry-based methods. These new methods offer a hybrid between a targeted and global proteomics strategy. While mass spectrometry data is collected in an unbiased way, the data is analyzed in a targeted strategy where specific peptides, albeit 1000s are analyzed using prior information. Thus, the reproducible targeting, throughput, and confident MS/MS-based quantification of parallel reaction monitoring (PRM) can be combined with classical discovery methods' ability to qualitatively detect thousands of proteins. These new methods based on systematically collected mass spectrometry data can offer similar quantitative figures of merit and can be validated in analogous fashion to clinical assays. Despite advances in proteomics technologies, most attempts at discovering new CSF markers have either used 1) stochastic sampling methods (e.g. data dependent acquisition) with poorly characterized quantitative performance, 2) small sample cohorts, 3) focused entirely on total CSF, 4) ignored protein processing, and 5) did not consider protein misfolding or stability. The purpose of this project within the cooperative research program is to take our methods to another level – apply true quantitative methods to large well characterized cohorts and extend them to functionally relevant subpopulations. We have a CSF assay that can measure >1050 proteins from completely unfractionated material with figures of merit of within/between day precision, linearity, LOD/LOQ, etc... Furthermore, we can use this assay on subsets of the CSF proteome to assess functionally relevant aspects of the neurobiology including quantity as part of solution or CSF particles, intact protein MW, and protein stability. Finally, we have enough throughput to apply these analyses on a scale sufficient to eliminate the chance that an observation is due to an aberrant subpopulation.