BiospecimenIntegrity: Assessing Quality and Influence on -Omics-based Analyses

生物样本完整性：评估基于组学的分析的质量和影响

• 批准号: 8646992
• 负责人: BRUCE S KRISTAL
• 金额: $ 43.73万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-02 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8646992
• 关键词: Address; Affect; Agreement; Biochemical; Bioinformatics; Biological Assay; Biological Markers; Blinded; Blood Platelets; Blood specimen; Classification; Clinical; Clinical Trials; Computational algorithm; Computer software; Coupled; Data; Data Set; Detection; Diet; Disease; Energy Intake; Epidemiologic Studies; Epidemiology; Erythrocytes; Exclusion; Floor; Food; Frequencies; Funding; Grant; High Pressure Liquid Chromatography; Human; Individual; Informatics; Investigation; Leukocytes; Link; Metabolic; Modeling; Morphologic artifacts; Noise; Non-Insulin-Dependent Diabetes Mellitus; Nurses' Health Study; Odds Ratio; Outcome; Outcome Measure; Oxidation-Reduction; Pattern Recognition; Peptides; Plasma; Population; Process; Proteomics; Public Health; Publishing; Questionnaires; Rattus; Relative Risks; Resources; Risk; Sampling; Serotyping; Shipping; Ships; Signal Transduction; Site; Time; Training; United States National Institutes of Health; Ursidae Family; base; cancer type; candidate marker; case control; cell type; cohort; cost; feeding; interest; malignant breast neoplasm; metabolomics; protein metabolite; repository; small molecule

DESCRIPTION (provided by applicant): We will address the issue of assessing plasma biospecimen integrity and its effect on downstream analyses and outcome measures such as risk prediction. We hypothesize that identifying and enabling correction of post-draw, pre-analytical variability at both the sample and variable level should engender increased signal to noise and thus increased power and precision of many biomarker studies being performed on samples in well-characterized human populations. Our approach will give us the ability to leverage the resources (data, expertise, platforms) established in six past and ongoing NIH- funded biochemical profiling studies to bear on this problem at comparatively lower cost. We already have candidate markers for red cell contamination as well as for sample degradation due to delayed processing as is inherent in studies using central processing. These approaches are very closely related to those needed to address the remaining two pieces, on white blood cell and platelet contamination, and we can expand the quantitation approaches that yielded our initial markers by ~10-fold in coverage due to recent software advances. The Aims: Aim 1: To utilize established metabolomics, proteomics, and informatics approaches to identify biomarkers of sample degradation, and, separately, biomarkers of contamination of plasma with constituents of red blood cells, white blood cells, or platelets. Aim 2: To mathematically re-analyze pre-existing metabolomics (HPLC-Coularray-based) and proteomics data (UPLC-LTQ-Orbitrap-based) from samples nested within the Nurses' Health Study (NHS) and within the OMNIHEART and CALERIE Clinical Trials so as: (i) to cross-validate the metabolomics and proteomics data to determine inter-assay agreement concerning sample quality, and; (ii) to assess the extent and distribution of sample degradation and distribution of levels of contamination of plasma with constituents of red blood cells, white blood cells, or platelets across these studies Aim 3: To determine the effect of variable and/or observation exclusion for cause (ie, red blood cell contamination) with incremented cut-points (eg, ...0.01%, 0.03%, 0.1%, 0.3%... etc) on the results of a study of pre-identified biomarkers of caloric intake to predict rik for breast cancer and type II diabetes (750/1000 paired case-control pairs nested within NHS), and thus to determine the influence of biospecimen integrity directly on both exposure classification (ie, diet) and end product prediction. Aim 4: To structurally identify metabolomics and proteomics biomarkers markers of interest to enable marker propagation to other groups and to electronically publish biomarker signatures.

描述（由申请人提供）：我们将解决评估等离子体生物测量完整性及其对下游分析和结果指标（例如风险预测）的影响的问题。我们假设，在样本和可变水平上识别和启用校正后，分析前的变异性，应导致信号增加对噪声，从而提高对良好特征的人群中样品进行的许多生物标志物研究的功率和精度。我们的方法将使我们能够利用在过去和正在进行的NIH资助的生化分析研究中建立的资源（数据，专业，平台），以相对较低的成本来解决这个问题。我们已经有针对红细胞污染的候选标记以及由于处理延迟的处理而导致样品降解，这是使用中央处理的研究所固有的。这些方法与在白色血细胞和血小板污染上解决其余两块所需的方法密切相关，我们可以扩大由于最近的软件进展，使我们的初始标记的覆盖率提高了约10倍。目的：目标1：利用已建立的代谢组学，蛋白质组学和信息学方法来鉴定样品降解的生物标志物，并分别使用红细胞，白细胞或血小板组成的血浆污染物的生物标志物。目的2：从数学上重新分析了先前存在的代谢组学（基于HPLC-Coularray）和蛋白质组学数据（基于uplc-ltq-orbitrap），从巢穴中嵌套的样品（NHS）中嵌套的样品（NHS）以及Omniheart和Calerie临床试验中的数据，以确定与跨性别的数据，以确定相互依存的数据，以确定相互作用和蛋白研究，并确定相互作用的概况和蛋白研究。关于样本质量，以及； （ii）评估这些研究中的样本降解和分布的血浆污染水平和血浆污染水平的分布的程度和分布。预识别的热量摄入生物标志物可以预测RIK的乳腺癌和II型糖尿病（750/1000配对的案例 - control对NHS中的疾病），因此可以直接确定生物测得完整性对暴露分类（IE，饮食）和最终产品的影响。目标4：在结构上识别感兴趣的代谢组学和蛋白质组学生物标志物标记，以使标记物传播到其他群体并电子发表生物标志物特征。