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

DiLeu 多重定量用于阿尔茨海默病生物标志物的发现和验证

• 批准号: 10586449
• 负责人: LINGJUN LI
• 金额: $ 56.71万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-15 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10586449
• 关键词: Acceleration; Address; Adult; Affect; Affinity; Age; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease therapeutic; Alzheimer’s disease biomarker; American; Amyloid beta-Protein; Autopsy; Biochemical Process; Biological Markers; Blood; Blood Proteins; Blood specimen; Brain; Cause of Death; Cerebrospinal Fluid; Chromatography; Classification; Clinical; Clinical Trials; Clinical assessments; Cognition; Cognitive; Cohort Studies; Coupled; Data; Defect; Dementia; Development; Diagnosis; Disease; Disease Progression; Early Diagnosis; Elderly; Emotional; Glycopeptides; Glycoproteins; Health; Immunoassay; Impaired cognition; Individual; Isotopes; Knowledge; Leucine; Mass Spectrum Analysis; Measures; Methods; Modality; Monitor; Neurofibrillary Tangles; Outcomes Research; Pathogenesis; Pathologic; Patient Care; Patients; Peptides; Persons; Pharmacologic Substance; Phase; Phosphopeptides; Population; Post-Translational Protein Processing; Proteins; Proteome; Proteomics; Reproducibility; Research; Risk; Sampling; Sensitivity and Specificity; Serum; Source; Specificity; Structure; Technology; Therapeutic; Treatment Efficacy; United States; Validation; bioinformatics tool; biomarker discovery; biomarker panel; biomarker validation; blood-based biomarker; candidate identification; candidate marker; candidate validation; classification algorithm; clinical practice; cost; data acquisition; design; differential expression; disease heterogeneity; glycoproteomics; glycosylation; improved; in vivo; individual patient; innovation; insight; instrumentation; machine learning classification; meetings; middle age; mild cognitive impairment; neuroimaging; novel; potential biomarker; pre-clinical; prevent; protein biomarkers; screening; tau Proteins; translational medicine

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.

项目概要/摘要 阿尔茨海默病 (AD) 是老年人中最常见的痴呆症，也是第六大病因 尽管进行了广泛的研究，但目前还没有任何治疗方法可以减缓或阻止死亡。 随着 AD 病例数量预计在未来 30 年内将增加两倍，迫切需要解决 AD 问题。 需要在临床前阶段早期诊断AD，而脑脊髓中的一些肽和蛋白质生物标志物。 脑脊液（CSF）已被用于 AD 诊断，但 AD 早期阶段仍缺乏明确的诊断。 也许更重要的是，发现和建立能够监测的可靠生物标志物 认知障碍的程度以及进展，因为治疗的潜在疗效仍然是一个主要因素 此外，与脑脊液相比，血清样本为生物标志物的发现提供了一个有吸引力的来源。 由于侵入性较小且更容易获取，因此可以进行筛查。然而，脑脊液和血液之间的相关性。 AD 中蛋白质/肽生物标志物以及大脑结构/功能和认知的变化情况不佳 为了应对这些挑战并填补现有的知识空白，我们建议采用一个 多方面的方法结合了一套基于质谱的技术，由创新技术支持 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、识别和评估从无症状患者获得的脑脊液/血清中的 AD 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 我们提出以下具体目标： 具体目标 1 – 开发新颖的产品。 富集策略和补充分离模式，以增强糖蛋白组的覆盖范围和 对对照受试者的配对脑脊液和血清样本进行翻译后修饰串扰分析， 分别针对临床前、MCI、AD 组。 具体目标 2 – 加强糖蛋白组的定量分析。 通过创新的二甲基化亮氨酸 (DiLeu) 增强和抑制脑脊液和血清样品中的低丰度物种 BoxCar 数据独立采集 (DIA) 策略以及机器学习分类算法 改进 AD 的诊断。具体目标 3 – 验证脑脊液和血清样本中的候选 AD 生物标志物。 使用有针对性的定量蛋白质组学方法从患有 MCI 和痴呆症的个体中收集 通过同位素 DiLeu 标签和亲和珠辅助 MS 免疫分析以及与 AD 相关的关联 该项目独特地整合了基于 MS 的进展。 多重定量糖蛋白组学和生物信息学工具以及神经影像学和临床测量 能够更全面地发现和验证 AD 中的脑脊液和血清生物标志物。 对于提高我们对 AD 发病机制的理解、设计患者护理疗法具有不可估量的价值 以及更有效的疾病修饰疗法的临床试验。 将对转化医学产生广泛影响。