Biomarker Discovery and Validation in Parkinson's Disease

帕金森病生物标志物的发现和验证

• 批准号: 9269667
• 负责人: Ted M. Dawson
• 金额: $ 66.04万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9269667
• 关键词: Affect; Algorithms; Alzheimer' s Disease; American; Area; Biochemical Process; Bioinformatics; Biological; Biological Assay; Biological Markers; Blinded; Brain; Brain region; Cell Death; Cells; Cerebrospinal Fluid; Cerebrospinal Fluid Proteins; Clinical; Complex; Data; Data Discovery; Diagnosis; Diagnostic; Diagnostic tests; Disease; Disease Progression; Ensure; Evaluation; Exhibits; Fourier Transform; Functional disorder; Goals; Individual; Label; Lewy Bodies; Mass Spectrum Analysis; Mediating; Medical History; Metabolic; Methods; Monitor; Motor; Neurodegenerative Disorders; Neurons; Onset of illness; Parkinson Disease; Parkinsonian Disorders; Pathogenesis; Pathologic; Pathway interactions; Patients; Performance; Pharmacotherapy; Proteins; Proteome; Proteomics; Reaction; Reproducibility; Resolution; Resources; Sampling; Set protein; Substantia nigra structure; Techniques; Technology; Testing; Universities; Validation; base; biomarker discovery; candidate marker; candidate validation; clinical practice; cohort; cost; diagnostic biomarker; differential expression; disorder control; experimental study; nervous system disorder; neuroimaging; programs; protein biomarkers; proteomic signature; response; validation studies

ABSTRACT Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder after Alzheimer's disease. Although PD is associated with Lewy body formation in the substantia nigra and other regions of the brain, the pathologic and metabolic alterations occurring during the onset and progression of PD have not been clearly defined. Despite a critical need for a reliable diagnostic marker for PD, there is currently no such biomarker that can be used accurately in clinical practice for establishing a definitive diagnosis of PD. The difficulty of identifying reliable biomarkers can be attributed to the variability of clinical samples, low abundance of proteins that are involved in PD pathogenesis and the lack of reproducibility in validating biomarker candidates. To overcome these limitations, we propose use of a large cerebrospinal fluid (CSF) cohort with greater statistical power for true discovery and deep proteome analysis to discover PD biomarkers that are involved in PD pathogenesis, but are present at low abundance. In addition, multiplexed sample analysis by isobaric tandem mass tagging (TMT) with a common reference for data normalization will ensure robust analytical precision of quantitative proteomic data for discovery from a larger set of samples. Moreover, additional proteomic analysis of substantia nigra will be used to select those biomarkers that show differential expression in CSF as well as substantia nigra. These discovery platforms will use a bioinformatics approach to select the most plausible candidates for targeted validation studies followed by an intensive validation of the discovered biomarker candidates. To achieve these goals, we propose three aims: Specific Aim 1: To discover proteins that are differentially expressed in patients with Parkinson's disease. We plan to carry out a quantitative proteomic analysis of CSF and substantia nigra samples from patients with PD and from controls by employing TMT-based multiplexing technology. With this approach, we expect to obtain a more comprehensive coverage of a larger number of proteins quantified across the analyzed samples. Specific Aim 2: To prioritize candidates based on an integrative analysis of alterations in CSF and substantia nigra. By integrating the expression changes in CSF and substantia nigra with a network approach that takes advantage of the known biological pathways that have been described in PD, our approach should be able to select reliable PD biomarker candidates for validation by targeted PRM experiments. Specific Aim 3: To validate candidate protein biomarkers in a larger cohort using targeted parallel reaction monitoring (PRM) mass spectrometry using CSF samples from a PD cohort at Johns Hopkins. Biomarkers that are selected by selection algorithms based on these PRM experiments will finally be confirmed with blinded PDBP CSF samples. Through the approaches outlined above, we expect to discover and validate reliable PD biomarkers in a reproducible fashion.

摘要