Differential Gene Expression

尽管近年来急性排斥反应的发生率有所降低，但慢性移植物肾病和 免疫抑制药物副作用仍然是移植物损失和患者发病的主要原因。在这 在这种背景下，必须提高我们对免疫反应和免疫系统反应的理解。 移植器官的免疫和非免疫损伤机制。基因表达分析是一种 这意味着识别参与移植生物学的分子途径。项目1的目标是 使用高密度微阵列技术测量肾活检中的差异基因表达， 具有明确表型的患者的外周血：急性排斥反应、慢性移植物肾病和 在12至24个月时根据方案进行活检的肾移植功能良好的患者。我们的初步 基于近100名受试者的研究数据表明，活检中的特征性基因表达谱 和外周血淋巴细胞，与移植免疫抑制以及急性 排斥反应使用个体基因表达信号的统计分析，然后进行分层聚类 和类别预测分析，我们可以证明活检的基因谱的显着差异， PBL定义这些临床组。我们的第一个具体目标是确定基因表达谱， 移植活检和PBL的患者在3个完善的临床分类。成功完成本 Aim将创建一个全面的，统计学上可靠的数据集，用于两种移植物的基因表达谱， 包括许多目前未知的可能与临床事件相关的基因 肾移植后。我们的第二个具体目标是建立单个基因的模式 表达与临床事件和结果相关。成功实现这一目标将决定 候选基因集，可以与平行研究ofproteomics（项目2）和复杂性状 遗传学（项目3）。我们将使用硅胶工具来识别基因功能和连接，揭示新的 移植生物学中的途径，特别是供体肾对移植的反应， 组织损伤、修复和慢性移植物肾病。

Despite recent reductions in the incidence of acute rejection, chronic allograft nephropathy and immunosuppressive drug side effects are still major causes of graft loss and patient morbidity. In this context, it is essential to advance our understanding of the immune response and the responses of the transplanted organ to both immune and non-immune injury mechanisms. Analysis of gene expression is one means to identify molecular pathways involved in transplantation biology. The objective of Project 1 is to use high-density microarray technology to measure differential gene expression in kidney biopsies and peripheral blood of patients with well-defined phenotypes: acute rejection, chronic allograft nephropathy and patients biopsied by protocol at 12 to 24 months with well-functioning kidney transplants. Our preliminary data based on studies of almost 100 subjects demonstrates characteristic gene expression profiles in biopsies and peripheral blood lymphocytes that correlate with transplant immunosuppression as welt as with acute rejection. Using statistical analysis of individual gene expression signals followed by hierarchical clustering and class prediction analysis we can demonstrate significant differences in the gene profiles of biopsies and PBL that define these clinical groups. Our first Specific Aim is to determine the gene expression profiles in transplant biopsies and PBL of patients in 3 well-established clinical classes. Successful completion of this Aim will create a comprehensive, statistically robust data set for gene expression profiles of both transplant biopsies and PBL including many presently unknown genes that can be correlated with clinical events following kidney transplantation. Our second Specific Aim is to establish the patterns for individual gene expression correlated with clinical events and outcomes. Successful completion of this Aim will define candidate gene sets that can be integrated with the parallel studies ofproteomics (Project 2) and complex trait genetics (Project 3). We will use in silica tools to identify gene functions and connections that reveal novel pathways in transplant biology particularly the response of the donor kidney to transplantation in the context of tissue injury, repair and chronic allograft nephropathy.