DiLeu-enabled multiplexed quantitation for biomarker discovery and validation in Alzheimer’s disease

项目总结/摘要 阿尔茨海默病（Alzheimer's disease，AD）是老年人中最常见的痴呆形式，也是第六大病因 死亡在美国。尽管进行了广泛的研究，但目前还没有治疗方法可以减缓或阻止 AD的发展。随着AD病例数量预计在未来30年内增加两倍， 需要在临床前阶段早期诊断AD。而脑脊液中的几种肽和蛋白质生物标志物 尽管脑脊液（CSF）已被用于AD的诊断，但在AD的早期阶段仍缺乏明确的诊断。 也许更重要的是，发现和建立可靠的生物标志物， 认知障碍的进展和程度以及治疗的潜在疗效仍然是一个主要的问题， 挑战.此外，与CSF相比，血清样品为生物标志物发现提供了有吸引力的来源 和筛查，因为侵入性更小，更容易进入。然而，脑脊液和血液之间的相关性 蛋白质/肽生物标志物以及脑结构/功能和认知的变化在AD中并不好 确立了习为了应对这些挑战并填补现有的知识空白，我们建议采用 多方面的方法结合了一套基于质谱的技术， 多重标记策略、改进的采样和分离策略以及临床可用的措施 发现、鉴定和评价从无症状性AD患者获得的CSF/血清中AD的候选生物标志物， 认知健康的中年人、认知正常的老年人和轻度认知障碍患者 （1）AD和MCI。我们提出以下具体目标：具体目标1 -开发新的 用于提高糖蛋白组覆盖率的富集策略和互补分离模式， 对照受试者的成对CSF和血清样品中的翻译后修饰串扰分析， 临床前组、MCI组、AD组。具体目标2 -加强定量糖蛋白质组学分析， 通过创新的二甲基化亮氨酸（DiLeu）加强， BoxCar数据独立采集（DIA）策略沿着机器学习分类算法， 改善AD的诊断。具体目标3 -验证CSF和血清样本中的候选AD生物标志物 从MCI和痴呆患者中收集，使用靶向定量蛋白质组学方法， 通过同位素DiLeu标签和亲和珠辅助的MS免疫测定沿着与AD相关的 临床、认知和神经成像测量。该项目独特地整合了基于MS的先进技术 多路定量糖蛋白组学和生物信息学工具与神经成像和临床措施， 能够更全面地发现和验证AD中的CSF和血清生物标志物。这些生物标志物 对于提高我们对AD发病机制的理解，设计患者护理的治疗方法， 以及更有效的疾病改善疗法的临床试验。技术的进步和新的见解 将对转化医学产生广泛的影响。

PROJECT SUMMARY/ABSTRACT Alzheimer’s disease (AD) is the most common form of dementia in the elderly population and 6th leading cause of death in the US. Despite extensive research, there are currently no treatments that slow or stop the development of AD. With the number of AD cases expected to triple in the next 30 years, there is a pressing need to diagnose AD early in the preclinical stage. While several peptide and protein biomarkers in cerebrospinal fluid (CSF) have been used for AD diagnosis, an unequivocal diagnosis in the early phases of AD is still lacking. Perhaps more importantly, the discovery and establishment of reliable biomarkers capable of monitoring progression and degree of cognitive impairment as well as potential efficacy of therapy remains a major challenge. Furthermore, compared to CSF, serum sample provides an appealing source for biomarker discovery and screening due to less invasiveness and easier access. However, the correlation between CSF and blood protein/peptide biomarkers as well as changes in the brain structure/function and cognition in AD is not well established. In order to address these challenges and fill in existing knowledge gaps, we propose to employ a multi-faceted approach combining a suite of mass spectrometry-based technologies enabled by innovative multiplexed tagging strategies, improved sampling and separation strategies and clinically-available measures to discover, identify and evaluate candidate biomarkers of AD in CSF/serum obtained from asymptomatic cognitively-healthy middle-aged adults, older cognitively-normal adults, and patients with mild cognitive impairment (MCI) and AD. We propose the following specific aims: Specific Aim 1 – To develop novel enrichment strategies and complementary separation modalities for enhanced coverage of glycoproteome and posttranslational modification crosstalk analysis in paired CSF and serum samples from subjects in control, preclinical, MCI, AD groups, respectively. Specific Aim 2 – To enhance quantitative glycoproteomic analysis of low-abundance species in CSF and serum samples via innovative dimethylated leucine (DiLeu) boosting and BoxCar data-independent acquisition (DIA) strategies along with machine learning classification algorithms for improved diagnosis of AD. Specific Aim 3 – To validate candidate AD biomarkers, in CSF and serum samples collected from individuals with MCI and dementia, using targeted quantitative proteomics approaches enabled by isotopic DiLeu tags and affinity-bead assisted MS immunoassay along with association with AD-related clinical, cognitive and neuroimaging measures. This project uniquely integrates advances in MS-based multiplexed quantitative glycoproteomics and bioinformatics tools with neuroimaging and clinical measures to enable more comprehensive discovery and validation of CSF and serum biomarkers in AD. These biomarkers would be invaluable in improving our understanding of AD pathogenesis, designing therapeutics for patient care and more efficient clinical trials of disease modifying therapies. The advances in technology and new insights will have broad impact on translational medicine.