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.

抽象的 帕金森病 (PD) 是继帕金森病之后第二常见的进行性神经退行性疾病 阿尔茨海默病。尽管 PD 与黑质和其他部位的路易体形成有关 大脑区域、PD 发病和进展过程中发生的病理和代谢变化 尚未明确定义。尽管迫切需要可靠的 PD 诊断标记物，但目前 没有这样的生物标志物可以在临床实践中准确地用于建立 PD 的明确诊断。 识别可靠生物标志物的困难可归因于临床样本的变异性、低 参与 PD 发病机制的蛋白质丰富，且验证缺乏可重复性 生物标志物候选者。为了克服这些限制，我们建议使用大量脑脊液 (CSF) 具有更强统计能力的队列，可以进行真正的发现和深入的蛋白质组分析，以发现 PD 生物标志物 参与 PD 发病机制，但丰度较低。此外，多重样本 通过同量异位串联质量标记 (TMT) 和数据标准化的共同参考进行分析将确保 定量蛋白质组数据的强大分析精度，可从大量样品中发现。而且， 黑质的额外蛋白质组学分析将用于选择那些显示差异的生物标志物 在脑脊液和黑质中表达。这些发现平台将使用生物信息学方法 选择最合理的候选者进行有针对性的验证研究，然后对 发现了候选生物标志物。为了实现这些目标，我们提出三个目标： 具体目标 1： 发现帕金森病患者差异表达的蛋白质。我们计划开展一项 对 PD 患者和对照的脑脊液和黑质样本进行定量蛋白质组学分析 采用基于TMT的复用技术。通过这种方法，我们期望获得更多 全面覆盖分析样品中定量的大量蛋白质。具体目标 2：根据脑脊液和黑质变化的综合分析对候选者进行优先排序。经过 将脑脊液和黑质的表达变化与利用优势的网络方法相结合 在 PD 中描述的已知生物学途径中，我们的方法应该能够选择 可靠的 PD 生物标志物候选物，可通过靶向 PRM 实验进行验证。具体目标 3：验证 使用靶向平行反应监测 (PRM) 质量在更大的队列中筛选候选蛋白质生物标志物 使用来自约翰·霍普金斯大学 PD 队列的 CSF 样本进行光谱测定。选择的生物标志物 基于这些 PRM 实验的选择算法最终将通过盲态 PDBP CSF 得到确认 样品。通过上述方法，我们期望发现并验证可靠的 PD 生物标志物 以可复制的方式。