Peptide Biomarkers for Alzheimer Disease
阿尔茨海默病的肽生物标志物
基本信息
- 批准号:9362936
- 负责人:
- 金额:$ 77.14万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-08-15 至 2022-04-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAffectAlzheimer disease detectionAlzheimer&aposs DiseaseAlzheimer&aposs disease riskAmericanAmyloid beta-ProteinAntibodiesAppearanceBiological AssayBiological MarkersBloodBody FluidsCaliforniaCellsCerebrospinal FluidCerebrospinal Fluid ProteinsClinicalCross-Sectional StudiesDataDementiaDevelopmentDiagnosisDifferential DiagnosisDiseaseDisease ProgressionEarly DiagnosisEconomicsGoalsHealthHealth SciencesHumanImageImmunoassayImpaired cognitionLeadLoop electrosurgical excision procedureMass Spectrum AnalysisMeasurementMonitorNeural Cell Adhesion Molecule L1NeuraxisOregonOrganParkinson DiseasePathogenesisPathogenicityPathologyPatientsPennsylvaniaPeptidesPerformancePharmaceutical PreparationsPilot ProjectsPlasmaPopulationProcessProteinsProteomicsReactionReproducibilityResearchResearch DesignResourcesSamplingSensitivity and SpecificitySeverity of illnessSocietiesSourceTechniquesTechnologyTestingUniversitiesValidationVariantWashingtonWorkalpha synucleinassay developmentbasebiomarker panelblood-based biomarkerbody systemcohortdesigndiagnostic accuracydisabilitydisease diagnosisdisorder controlexosomeimprovedinterestmicrovesiclesneuroimagingnovelnovel markerpre-clinicaltau Proteinstreatment effect
项目摘要
Summary
Significant progress has been made in using neuroimaging and cerebrospinal fluid (CSF) protein
measurements as Alzheimer disease (AD) biomarkers. However, there is still a critical need to
identify more reliable and reproducible biomarkers with further improved diagnostic accuracy,
especially to differentiate AD from other dementias, to track or monitor the disease progression
and to objectively evaluate drug effects. There is also a growing interest in developing novel
biomarkers that could reflect different aspects of AD pathology and accurately detect pathogenic
components of AD before appearance of significant cognitive decline, thereby assisting with AD
diagnosis at early symptomatic and even preclinical stages. This proposal is designed to meet
several major challenges of current biomarker research, specifically: 1) difficulties in development
of antibody-based, quantitative protein assays for most novel candidates identified by proteomic
profiling and significant variations associated with most existing immunoassays, 2) low sensitivity
and specificity of blood-based markers, and 3) detection of AD at early or even preclinical stages.
To address the problems of antibody-based assays, our strategy is development of targeted mass
spectrometry-based techniques, such as selected reaction monitoring (SRM), to identify unique
peptide markers derived from proteins either showing promise in previous proteomics profiling, or
known to be critical to AD pathogenesis in human cerebrospinal fluid (CSF). To facilitate discovery
and validation of blood based biomarkers, a specific population of central nervous system derived
plasma exosomes, the cargo-carrying microvesicles recognized recently to transport biomolecules
among different cells or organ systems, will be isolated before SRM analysis. The unique peptide
markers will be tested in several large, well-established cohorts, e.g., Alzheimer's Disease
Research Centers (ADRCs) affiliated with the University of Washington, Oregon Health and
Science University, University of California at San Diego, and University of Pennsylvania, and
ADNI (Alzheimer's Disease Neuroimaging Initiative), with cross-sectional and longitudinal samples
collected, along with extensive clinical characterization. Finally, to improve early diagnosis, we will
make use of a very early MCI cohort consisting of subjects at elevated risk for AD, with the goal of
discovering biomarkers capable of identifying subjects with early or preclinical AD. The studies
designed for this project, if successful, have the potential to result in a panel(s) of biomarkers that
are robust, with less variation than can currently be achieved, and in a body fluid that is readily
accessible in a regular clinical setting. Markers for early diagnosis and progression of AD are critical
in understanding how to arrest or slow AD progression.
概括
神经影像学和脑脊液(CSF)蛋白的使用取得了重大进展
测量作为阿尔茨海默病(AD)生物标志物。然而,仍然迫切需要
识别更可靠和可重复的生物标志物,进一步提高诊断准确性,
特别是区分 AD 和其他痴呆症,跟踪或监测疾病进展
并客观评价药物效果。人们对开发新颖的兴趣也越来越大
可以反映 AD 病理学不同方面并准确检测致病菌的生物标志物
在出现显着认知能力下降之前识别 AD 的组成部分,从而帮助治疗 AD
在早期症状甚至临床前阶段进行诊断。该提案旨在满足
当前生物标志物研究面临的几大挑战,具体来说:1)开发困难
针对蛋白质组学鉴定的大多数新型候选物进行基于抗体的定量蛋白质测定
与大多数现有免疫测定相关的分析和显着变化,2) 低灵敏度
和血液标记物的特异性,3) 在早期甚至临床前阶段检测 AD。
为了解决基于抗体的检测的问题,我们的策略是开发目标质量
基于光谱测定的技术,例如选择反应监测 (SRM),可识别独特的
源自蛋白质的肽标记物在之前的蛋白质组学分析中显示出前景,或者
已知对人脑脊液 (CSF) 中的 AD 发病机制至关重要。为了方便发现
和基于血液的生物标志物的验证,源自中枢神经系统的特定人群
血浆外泌体,最近被认为可以运输生物分子的载货微泡
在SRM分析之前,将在不同的细胞或器官系统之间进行分离。独特的肽
标记物将在几个大型、成熟的队列中进行测试,例如阿尔茨海默病
俄勒冈州华盛顿大学附属研究中心 (ADRC)
科学大学、加州大学圣地亚哥分校和宾夕法尼亚大学,以及
ADNI(阿尔茨海默病神经影像倡议),具有横截面和纵向样本
收集,以及广泛的临床特征。最后,为了改善早期诊断,我们将
利用由 AD 风险较高的受试者组成的非常早期的 MCI 队列,目标是
发现能够识别早期或临床前 AD 受试者的生物标志物。研究
为本项目设计的,如果成功的话,有可能产生一组生物标记物,
鲁棒性强,变化比目前所能实现的要小,并且在体液中很容易
可在常规临床环境中使用。 AD 早期诊断和进展的标志物至关重要
了解如何阻止或减缓 AD 的进展。
项目成果
期刊论文数量(0)
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{{ truncateString('Jing Zhang', 18)}}的其他基金
Exosomal transport of brain-derived proteins to the blood in Alzheimer disease
阿尔茨海默病中脑源性蛋白质的外泌体转运至血液
- 批准号:
9564296 - 财政年份:2017
- 资助金额:
$ 77.14万 - 项目类别:
Functional Genomics and Proteomics Facility Core
功能基因组学和蛋白质组学设施核心
- 批准号:
8830356 - 财政年份:2015
- 资助金额:
$ 77.14万 - 项目类别:
Functional Genomics and Proteomics Facility Core
功能基因组学和蛋白质组学设施核心
- 批准号:
8650854 - 财政年份:2014
- 资助金额:
$ 77.14万 - 项目类别:
Project 3: Plasma Biomarkers for Parkinsonism in Welders
项目 3:焊工帕金森病的血浆生物标志物
- 批准号:
8845298 - 财政年份:2014
- 资助金额:
$ 77.14万 - 项目类别:
Dose-dependent Activation of the MEK/ERK Pathway in Hematopoiesis
造血过程中 MEK/ERK 通路的剂量依赖性激活
- 批准号:
8504631 - 财政年份:2013
- 资助金额:
$ 77.14万 - 项目类别:
Dose-dependent Activation of the MEK/ERK Pathway in Hematopoiesis
造血过程中 MEK/ERK 通路的剂量依赖性激活
- 批准号:
8666589 - 财政年份:2013
- 资助金额:
$ 77.14万 - 项目类别:
Large Scale Biomarker Discovery and Validation for Parkinsons Disease
帕金森病的大规模生物标志物发现和验证
- 批准号:
8473013 - 财政年份:2012
- 资助金额:
$ 77.14万 - 项目类别:
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