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微阵列在肾脏病学中的应用,特别关注移植方面。

Microarray applications in nephrology with special focus on transplantation.

机构信息

Division of Nephrology and Transplant Immunology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.

出版信息

J Nephrol. 2012 Sep-Oct;25(5):589-602. doi: 10.5301/jn.5000205.

Abstract

The increase in progressive kidney disease, rising numbers of patients with end-stage renal disease, organ shortages for kidney transplants and poor long-term graft survival rates underline the need for better strategies to diagnose, prevent and treat renal disease. Histological analysis, based on renal biopsies and readings of morphology, has limitations as key information for the management of the individual patient, and complementary technologies are needed. The sequencing of the human genome has provided the platform for applied molecular phenotyping. Microarray technology has become a routine method for robust high-throughput measurements of genome-wide transcriptome levels. This review will give examples of transcriptome profiling in nephrology and focus on lessons learned from studies in kidney transplantation. Molecular profiling detects changes not seen by morphology or captured by clinical markers. Gene expression signatures provide quantitative measurements of inflammatory burden and immune activation or metabolism, and reflect coordinated changes in pathways associated with injury and repair. Transcriptome profiling has the potential to improve our understanding of disease mechanisms, may provide tools to reclassify disease entities and be potentially helpful in individualizing therapies and predicting outcomes. However, description of transcriptome patterns is not an end in itself. The identification of predictive gene sets and the application to an individualized patient management requires integration of clinical and pathology-based variables as well as more objective reference markers and hard end points.

摘要

进行性肾脏疾病的增加、终末期肾病患者数量的上升、肾脏移植器官短缺以及长期移植物存活率低,都强调了需要更好的策略来诊断、预防和治疗肾脏疾病。基于肾脏活检和形态学读数的组织学分析具有局限性,因为它不能为患者的个体化管理提供关键信息,因此需要补充其他技术。人类基因组测序为应用分子表型提供了平台。微阵列技术已成为全基因组转录组水平进行稳健高通量测量的常规方法。本文将举例说明肾脏病学中的转录组分析,并重点介绍肾脏移植研究中的经验教训。分子分析可检测到形态学或临床标志物无法捕捉到的变化。基因表达谱提供了炎症负担和免疫激活或代谢的定量测量,并反映了与损伤和修复相关的途径的协调变化。转录组分析有可能增进我们对疾病机制的理解,为重新分类疾病实体提供工具,并可能有助于个体化治疗和预测结果。然而,描述转录组模式本身并不是目的。识别预测性基因集并将其应用于个体化患者管理需要整合临床和基于病理学的变量,以及更客观的参考标志物和硬性终点。

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