Proteomic Pathway Discovery in Cardiovascular Disease

心血管疾病中蛋白质组通路的发现

• 批准号: 9301638
• 负责人: ROBERT E GERSZTEN
• 金额: $ 85.28万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9301638
• 关键词: Ablation; Address; Alleles; Antibodies; Avidity; Binding; Bioinformatics; Biological Assay; Biological Markers; Blood Pressure; Blood Proteins; British; Cardiac; Cardiac health; Cardiovascular Diseases; Chemicals; Clinical; Cohort Studies; Communities; Complement; Cross-Sectional Studies; DNA; Data; Diabetes Mellitus; Disease; Disease Pathway; Epidemiology; Event; Exercise stress test; Follow-Up Studies; Framingham Heart Study; Future; Genetic; Genetic Determinism; Goals; Heart Diseases; High Density Lipoprotein Cholesterol; Human; Hypertrophic Cardiomyopathy; Individual; Injury; Institutes; Interdisciplinary Study; Knowledge; Laboratories; Mass Spectrum Analysis; Measures; Methods; Myocardial; Myocardial Infarction; Natural experiment; Pathway interactions; Patients; Phenotype; Plant Roots; Plasma; Population; Preventive Intervention; Proteins; Proteomics; Randomized; Reader; Reproducibility; Research Personnel; Resources; Risk; Sampling; Scanning; Single-Stranded DNA; Smoking; Techniques; Technology; Testing; Time; Troponin; Validation; Woman; Work; aptamer; base; cardiovascular risk factor; cohort; diet and cancer; experience; follow-up; genetic variant; liquid chromatography mass spectrometry; metabolomics; new technology; novel; novel marker; phenotypic data; population based; potential biomarker; predictive marker; prospective; protein biomarkers; public health relevance; rare variant; targeted biomarker; trait

 DESCRIPTION (provided by applicant): Although dozens of protein biomarkers have been associated individually or in panels with cardiovascular risk, their incremental utility has been modest. For new biomarkers to add incremental utility, they must provide non-overlapping information. However, new biomarkers typically emerge from well-studied pathways that are already covered by existing biomarkers. Thus, it is necessary to consider alternative approaches to identifying protein biomarkers of cardiovascular disease (CVD) ─ to provide novel biologic information and to ultimately enable more efficient targeting of preventive interventions. Emerging proteomic technologies are beginning to permit the systematic, unbiased characterization of human plasma samples, though few data exist in population-based cohort studies. To address limitations of prior studies, we have established a high-throughput proteomic platform in our laboratory that measures 1129 proteins using chemically modified single-stranded DNA aptamers. We have rigorously addressed intra- and inter-assay variability, acquiring data >10-fold faster than mass spectrometry based methods. In pilot analyses in the Framingham Heart Study (FHS), we confirmed established correlations of known biomarkers with the Framingham Risk Score and discovered many new associations. We therefore propose to integrate novel aptamer based proteomic analyses with the rich phenotypic data in FHS, as well as genetic scans for common and rare variants. We will test the hypothesis that proteomic profiling in well-phenotyped populations will illuminate additional disease pathways apart from those already described. In Specific Aim 1, we will identify novel proteomic biomarkers of cardiovascular risk factors (BMI, systolic blood pressure, total/HDL cholesterol, diabetes, smoking and the Framingham Risk Score) in cross-sectional analyses. In Specific Aim 2, we will assess whether novel proteomic biomarkers predict the risk of future CVD events in prospective analyses. In Specific Aim 3, we will characterize the genetic determinants of proteins associated with cardiovascular risk. We will analyze the genetic determinants of proteins identified in Aims 1 and 2, and examine whether genetic variants that determine protein levels are in turn associated with clinical traits. All of the primary data generated by this multi-omics proposal wil be made broadly available in real time to the scientific community.

 描述（由申请人提供）：尽管数十种蛋白质生物标志物已单独或在小组中与心血管风险相关，但其增量效用一直不大。新的生物标志物要增加效用，它们必须提供非重叠的信息。然而，新的生物标志物通常来自已经被现有生物标志物覆盖的经过充分研究的途径。因此，有必要考虑其他方法来鉴定心血管疾病（CVD）的蛋白质生物标志物，以提供新的生物信息，并最终实现更有效的预防干预措施。新兴的蛋白质组学技术开始允许对人血浆样本进行系统的、无偏倚的表征，尽管在基于人群的队列研究中存在很少的数据。为了解决先前研究的局限性，我们在实验室建立了一个高通量蛋白质组学平台，使用化学修饰的单链DNA适体测量1129种蛋白质。我们严格解决了检测内和检测间的变异性，获得数据的速度比基于质谱的方法快10倍以上。在心脏病研究（FHS）的初步分析中，我们证实了已知生物标志物与心脏病风险评分的相关性，并发现了许多新的关联。因此，我们建议将新的基于适体的蛋白质组学分析与FHS中丰富的表型数据以及常见和罕见变体的遗传扫描相结合。我们将检验这一假设，即在表型良好的人群中进行蛋白质组学分析将阐明除了已经描述的疾病途径之外的其他疾病途径。在具体目标1中，我们将在横断面分析中确定心血管风险因素（BMI，收缩压，总/HDL胆固醇，糖尿病，吸烟和Fragrance风险评分）的新蛋白质组学生物标志物。在特定目标2中，我们将评估新型蛋白质组生物标志物是否可以在前瞻性分析中预测未来心血管疾病事件的风险。在具体目标3中，我们将描述与心血管风险相关的蛋白质的遗传决定因素。我们将分析目标1和2中确定的蛋白质的遗传决定因素，并检查决定蛋白质水平的遗传变异是否与临床特征相关。这个多组学提议产生的所有原始数据将在真实的时间内广泛提供给科学界。