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.

项目摘要/摘要 阿尔茨海默病(AD)是老年人群中最常见的痴呆形式，是第六大病因 在美国的死亡。尽管进行了广泛的研究，但目前还没有治疗方法可以延缓或阻止 AD的发展。随着AD病例的数量预计在未来30年内增加两倍，有一个紧迫的问题 需要在临床前期早期诊断AD。而脑脊液中的几种多肽和蛋白质生物标志物 脑脊液(CSF)已被用于AD的诊断，但在AD的早期阶段尚缺乏明确的诊断。 也许更重要的是，能够监测的可靠生物标志物的发现和建立 认知损害的进展和程度以及治疗的潜在疗效仍然是一个主要因素 挑战。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 和筛查，因为侵入性更小，更容易获得。然而，脑脊液与血液的相关性 阿尔茨海默病的蛋白质/多肽生物标志物以及脑结构/功能和认知功能的改变 已经成立了。为了应对这些挑战并填补现有的知识空白，我们建议采用 多方面方法结合了一套基于质谱学的技术，由创新技术支持 多路标记策略、改进的采样和分离策略和临床可用的措施 无症状患者脑脊液/血清中AD候选标志物的发现、鉴定和评价 认知健康的中年人、认知正常的老年人和轻度认知障碍的患者 损害(MCI)和AD。我们提出了以下具体目标：具体目标1--发展小说 增强糖蛋白质组和糖蛋白质组覆盖率的浓缩策略和互补分离模式 对照受试者脑脊液和血清样本翻译后修饰串扰分析 临床前组、MCI组、AD组。特定目标2--加强糖蛋白组学定量分析 脑脊液和血清样本中的低丰度物种通过创新的二甲基亮氨酸(DILEU)增强和 Boxcar数据独立获取(DIA)策略以及机器学习分类算法 改进了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 收集自MCI和痴呆症患者，使用靶向定量蛋白质组学方法 同位素Dileu标记和亲和珠联用MS免疫分析及其与AD相关性的研究 临床、认知和神经成像测量。该项目独一无二地集成了基于MS的先进技术 多重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患者的脑脊液和血清生物标志物。这些生物标志物 对于提高我们对阿尔茨海默病发病机制的理解，为患者护理设计治疗方法，将是非常宝贵的 以及更有效的疾病修饰疗法的临床试验。技术的进步和新的见解 将对转化医学产生广泛的影响。