MS based approaches for diabetes biomarker discovery
MS based approaches for diabetes biomarker discovery
批准号:
7617578
负责人:
Urban A Kiernan
金额:
$26.19万
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-06-01 至 2010-09-30
关键词:
AffinityBiologicalBiological AssayBiological MarkersBioprobeCharacteristicsClinicalComplexDataDetectionDiabetes MellitusDigestionEventFigs - dietaryFrequenciesGoalsIndividualLigandsLinkMalignant neoplasm of pancreasMass Spectrum AnalysisMetalsMethodologyMethodsMonoclonal AntibodiesNational Institute of Diabetes and Digestive and Kidney DiseasesNon-Insulin-Dependent Diabetes MellitusOGTTPhasePlasma CellsPost-Translational Protein ProcessingPrediabetes syndromeProcessProteinsProteomicsRelative (related person)Request for ApplicationsResearchRoboticsSamplingScreening procedureSolutionsSpecificityStatistical MethodsStudy SectionSurfaceTechnologyValidationVariantbaseclinical applicationcohortdiabeticdisease diagnosisnovelprogramsprotein profilingvalidation studies
中文摘要
描述(由申请人提供):本提案的目的是应用新型亲和质谱(AMS)技术来鉴定糖尿病前期或2型糖尿病的蛋白质生物标志物。所使用的方法结合了从复杂生物溶液中捕获微亲和蛋白与质谱检测。在第一阶段(R21),我们将筛选提供的血浆和血细胞样本,以确定候选蛋白质和蛋白质谱,这些候选蛋白质和蛋白质谱可以适当地区分样品来自3组中的1组(正常、糖尿病前期和糖尿病;通过口服葡萄糖耐量试验确定)。血浆和血细胞样品将用多克隆和单克隆抗体衍生的亲和移液管进行分析,用于特定蛋白质目标分析。此外,蛋白质组将通过亲疏水配体、金属螯合配体和其他宽特异性亲和表面进行分析。每一种配体表面都具有特定的亲和力特征,这将导致捕获和纯化单个或整个蛋白质群。由于定性和/或定量差异而观察到的蛋白质变异,具有统计显著性并根据其来源正确分组样品,将被视为潜在的生物标志物。在第二(验证)阶段(R33),我们将通过使用高通量并行机器人处理,通过将相同的方法和方法应用于更大的样本队列来验证发现的生物标志物。如果多种蛋白质生物标志物得到验证,将开发用于糖尿病的AMS面板。这将通过构建多分析物亲和移液管来实现,该移液管将选择性地检索区分健康和患病状态的目标生物标志物。这些面板也将受到其每个组件所经受的相同验证过程的约束。这项研究的最终结果将是验证2型糖尿病前期和2型糖尿病的蛋白质生物标志物,以及为该疾病的临床筛查和诊断做好准备的技术。
英文摘要
DESCRIPTION (provided by applicant): The objective of this proposal is to apply novel affinity mass spectrometry (AMS) technologies to identify protein biomarkers for pre-diabetes or type 2 diabetes. The methodology used combines micro-affinity protein capture from complex biological solutions with mass spectrometric detection. In this first phase (R21), we will screen the provided plasma and blood cell samples to identify candidate proteins, and protein profiles, that can appropriately differentiate sample origin from 1 of the 3 groups (normal, pre-diabetic and diabetic; as determined by the administration of an oral glucose tolerance test). Both plasma and blood cell samples will be assayed with affinity pipettes derivatized with poly- and monoclonal antibodies for specific protein target analysis. Additionally, groups of proteins will be analyzed via hydrophilic and hydrophobic ligands, metal chelating ligands, and other wide-specificity affinity surfaces. Each of these ligand surfaces possesses specific affinity characteristics that will result in the capture and purification of individual or whole groups of proteins. Protein variations observed as a result of qualitative and/or quantitative differences, that have statistical significance and correctly group samples according to their origin, will be viewed as potential biomarkers. In the second (validation) phase (R33), we will validate the discovered biomarker(s) via the application of the same methods and approaches to a larger group of sample cohorts through the use of high throughput parallel robotic processing. In the event that multiple protein biomarkers are validated, AMS panels for diabetes will be developed. This will be achieved through the construction of multi-analyte affinity pipettes that will selectively retrieve the targeted biomarkers that differentiate healthy from diseased states. Such panels will also be subject to the same validation process that each of its components endured. The ultimate result of this research will be validated protein biomarkers for pre-and type 2 diabetes and technology that are ready for clinical screening and diagnosis of the disease.
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会议论文
Computational Development of Novel Dyslipidemia Therapeutic Candidates to Disrupt ApoC-III Conformation
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批准号:10760187
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项目类别:
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资助金额:$28.31万
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财政年份:2023
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负责人:Urban A Kiernan
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依托单位:
MS based approaches for diabetes biomarker discovery
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批准号:7500061
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项目类别:
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资助金额:$63.17万
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财政年份:2005
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负责人:Urban A Kiernan
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依托单位:
海外基金