Prognostic markers in postoperative acute kidney injury

术后急性肾损伤的预后标志物

• 批准号: 7629048
• 负责人: JOHN M. ARTHUR
• 金额: $ 37.37万
• 依托单位: MEDICAL UNIVERSITY OF SOUTH CAROLINA
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2012-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7629048
• 关键词: Acute Kidney Failure; Acute Renal Failure with Renal Papillary Necrosis; Affect; Algorithms; Animal Model; Biological Assay; Biological Markers; Biological Markers; Brush Border; CCL2 gene; Cardiac Surgery procedures; Cell Death Process; Cessation of life; Clinical; Collaborations; Coronary Artery Bypass; Data; Development; Diagnostic; Dialysis procedure; Disease; Electrophoresis; Enzymes; Functional disorder; Glycoproteins; Goals; Human; Immune response; Incidence; Inflammatory; Inflammatory Response; Informatics; Injury; Intercellular adhesion molecule 1; Interleukin-18; Interleukin-6; Ischemia; Kidney; Kidney Failure; Knowledge; LIF gene; Length; Literature; Marker Discovery; Measurable; Measurement; Measures; Methodology; Methods; Natural regeneration; Nature; Nephrons; Operative Surgical Procedures; Outcome; Outcomes Research; Output; Patients; Pattern; Peptides; Plasma; Plasma Proteins; Postoperative Period; Process; Prognostic Marker; Protein Fragment; Proteins; Proteomics; Publishing; Recovery of Function; Renal Replacement Therapy; Retinol Binding Proteins; Risk; Risk Factors; Sampling; Severities; Site; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Surrogate Markers; Techniques; Testing; Time; Tubular formation; Two-Dimensional Gel Electrophoresis; UMOD gene; Urine; Zinc; alpha 1-Antitrypsin; alpha-1-microglobulin; base; candidate marker; cytokine; effective therapy; experience; high risk; improved; insight; mortality; novel marker; outcome forecast; polypeptide; primary outcome; prognostic; regenerative; response; response to injury; secondary outcome; urinary

DESCRIPTION (provided by applicant): Acute kidney injury (AKI) after cardiac surgery is associated with a 20 fold increase in mortality. Among patients who require dialysis, the risk of death is increased 70-fold. The magnitude of renal injury is variable and difficult to predict. Risk factors for kidney injury have been described but they do not predict if a given patient will develop renal failure. No accurate biomarkers currently exist to predict the prognosis of patients with kidney injury. The absence of predictive biomarkers is an impediment to studies of new therapies for AKI. Prognostic markers could identify the subset of patients in whom testing of new therapies should be performed. A significant effort is being made to identify diagnostic and early biomarkers. However, little progress has been achieved in identifying markers that predict the magnitude and course of the disease in AKI. The goal of this project is to identify biomarkers for prognosis in AKI after cardiac surgery. We have established a team of experts in AKI that will collect samples from patients at four sites. The proteomic, statistical and informatic collaborators have established collaborations with each other in which they have previously identified biomarkers. Urine will be collected from patients who develop AKI after cardiac surgery at four centers. The primary outcome variable is the requirement for renal replacement therapy. We will predict secondary outcomes that are either clinically useful or meaningful research outcomes. In the first aim we will measure candidate markers. The markers were chosen based on published literature and our own preliminary data. They include candidate markers for tubular injury, inflammatory response, tubular function, recovery of function, and progression to dialysis. In the second aim we will use two proteomic techniques, 2D electrophoresis with DIGE and MALDI polypeptide analysis to identify novel markers. The goal of these discovery studies is to find new markers that can be used in combination with the best markers from aim 1. We provide preliminary data with both techniques in which we have identified biomarkers. In the third aim we will select the candidate markers to be combined in a final assay using a second set of patients that is independent of the set used in the first two aims. Finally, we will validate the markers and the algorithm used to identify them in a third set consisting of 590 new patients. These studies will use a combination of hypothesis-driven and discovery based approaches to find the best combination of biomarkers to predict the course of acute kidney injury.

描述（由申请人提供）：心脏手术后急性肾损伤 (AKI) 与死亡率增加 20 倍相关。在需要透析的患者中，死亡风险增加了 70 倍。肾损伤的严重程度是可变的且难以预测。已经描述了肾损伤的危险因素，但它们并不能预测特定患者是否会发生肾衰竭。目前尚无准确的生物标志物来预测肾损伤患者的预后。缺乏预测性生物标志物是 AKI 新疗法研究的障碍。预后标志物可以识别应进行新疗法测试的患者子集。人们正在付出巨大的努力来识别诊断和早期生物标志物。然而，在识别预测 AKI 疾病严重程度和病程的标记物方面进展甚微。该项目的目标是确定心脏手术后 AKI 预后的生物标志物。我们建立了 AKI 专家团队，将从四个地点的患者身上收集样本。蛋白质组学、统计学和信息学合作者已经相互建立了合作，他们之前已经鉴定了生物标志物。四个中心将收集心脏手术后出现 AKI 的患者的尿液。主要结果变量是肾脏替代治疗的需求。我们将预测具有临床用途或有意义的研究结果的次要结果。在第一个目标中，我们将测量候选标记。这些标记是根据已发表的文献和我们自己的初步数据选择的。它们包括肾小管损伤、炎症反应、肾小管功能、功能恢复和透析进展的候选标志物。在第二个目标中，我们将使用两种蛋白质组技术、DIGE 二维电泳和 MALDI 多肽分析来鉴定新标记。这些发现研究的目标是寻找可与目标 1 中的最佳标记结合使用的新标记。我们使用已鉴定生物标记的两种技术提供初步数据。在第三个目标中，我们将使用独立于前两个目标中使用的组的第二组患者来选择要在最终测定中组合的候选标记物。最后，我们将在由 590 名新患者组成的第三组中验证标记物和用于识别它们的算法。这些研究将结合假设驱动和基于发现的方法来寻找生物标志物的最佳组合来预测急性肾损伤的病程。