Noninvasive Biomarkers of Microcirculatory Injury in the Human Kidney Allograft

 描述（由申请人提供）：肾移植随着时间的推移而失败。由于靶向移植肾内血管细胞（微循环内皮细胞）的抗体造成的损伤是移植失败的主要原因。目前还没有预测这种损伤的临床工具。血液中的microRNA可以作为损伤的标志物。我们建议开发基于microRNA（miRNA）的血液检测用于诊断抗体介导的微循环炎症/损伤。我们在我院精心挑选了180名肾移植受者，他们在接受同种异体移植活检时采集了血清样本并储存在我们的实验室中。AMI组（n=60）包括来自60名肾移植受者的60份血清样本，活检诊断为抗体介导的微循环炎症。无AMI组（n=120）由来自120名肾移植受者的120份血清样本组成，这些受者的活检没有此类炎症。该组包括活检诊断为急性细胞排斥、急性肾小管损伤和正常同种异体移植物活检的患者（各n=40）。具体目标是：（1）鉴定肾移植受体血清中可诊断肾移植物中AMI的循环细胞外miRNA，（2）开发诊断肾移植物中AMI的统计学模型（特征），（3）验证肾移植受体血清中的循环细胞外miRNA。 在从肾移植受者的独立外部队列获得的血清样品中的诊断模型。我们将使用高通量条形码深度测序来表征血清miRNA转录组。我们将使用miRNA-specific qPCR检测来准确定量选择的单个miRNAs，以便将其快速翻译到临床上。我们将比较两组（AMI与非AMI）的血清miRNA转录组，并鉴定两者之间不同的miRNA。然后，我们将开发PCR检测方法来准确定量所选的miRNA。我们将开发由最佳预测诊断的miRNAs组合组成的统计模型。我们将从统计学上确定使用这种模型诊断AMI的临床益处。为了确保统计模型适用于不同的患者群体，我们将 在另一组来自不同医院的105名肾移植受者（35名AMI和70名非AMI）中进行PCR分析并测试统计模型（签名）。

 DESCRIPTION (provided by applicant): Kidney transplants fail over time. Injury due to antibodies that target cells of the blood vessels within the transplant kidney (microcirculatory endothelium) is a major reason why the transplants fail. Clinical tools to predict this injury are not available. MicroRNAs in the blood could serve as markers of injury. We propose to develop microRNA (miRNA)-based blood tests for the diagnosis of antibody-mediated microcirculatory inflammation/injury. We have carefully selected a group of 180 kidney transplant recipients at our hospital who had serum samples collected and stored in our laboratory at the time of undergoing an allograft biopsy. The AMI group (n=60) consists of 60 serum samples from 60 kidney transplant recipients with biopsy diagnosis of antibody-mediated microcirculatory inflammation. The No AMI group (n=120) consists of 120 serum samples from 120 kidney transplant recipients whose biopsy did not have such inflammation. This group consists of patients with biopsy diagnosis of acute cellular rejection, acute tubular injury, and normal allograft biopsy (n=40 each). The Specific Aims are to: (1) Identify circulating extracellular miRNAs in serum of kidney graft recipients that are diagnostic of AMI in the kidney allograft, (2) Develop a statistical model (signature) diagnostic of AMI in the kidney allograft, (3) Validate the diagnostic model in serum samples obtained from an independent external cohort of kidney transplant recipients. We will use high throughput barcoded deep sequencing to characterize the serum miRNA transcriptome. We will use miRNA-specific qPCR assay to accurately quantify selected individual miRNAs, for their quick translation to the clinic. We will compare the serum miRNA transcriptome from the two groups (AMI vs. No AMI) and identify miRNAs that are different between the two. We will then develop PCR assays to accurately quantify the selected miRNAs. We will develop statistical models consisting of combination of miRNAs that best predict the diagnosis. We will statistically determine the clinical benefit of using such a model fr diagnosing AMI. To ensure that the statistical model works in different groups of patients, we will do PCR assays and test the statistical model (signature) in another group of 105 kidney transplant recipients (35 AMI and 70 No AMI) from a different hospital.