Rovin Brad H, Birmingham Daniel J, Nagaraja Haikady N, Yu C Yung, Hebert Lee A
Division of Nephrology, Ohio State University College of Medicine, and Columbus Children's Hospital Research Center 43210, USA.
Bull NYU Hosp Jt Dis. 2007;65(3):187-93.
The treatment of systemic lupus erythematosus (SLE) nephritis, while effective, is associated with significant morbidity and mortality. These side effects could be mitigated if the onset, severity, and response of renal flare could be predicted, and therapy modified accordingly. In this review, an approach to derive prediction equations of SLE nephritis flare is discussed. Integral to generating such prediction equations is the identification of biomarkers of lupus nephritis that can serve as input variables for modeling flare. The use of urine as a source of SLE nephritis biomarkers is described, and the results of urine biomarker discovery studies using candidate and proteomic approaches are presented.
系统性红斑狼疮(SLE)肾炎的治疗虽有成效,但却伴随着显著的发病率和死亡率。如果能够预测肾脏炎症发作的起始、严重程度及反应,并据此调整治疗方案,这些副作用或许可以减轻。在本综述中,我们将探讨一种推导SLE肾炎炎症发作预测方程的方法。生成此类预测方程的关键在于识别狼疮肾炎的生物标志物,这些标志物可作为炎症发作建模的输入变量。本文描述了将尿液作为SLE肾炎生物标志物来源的应用,并展示了使用候选方法和蛋白质组学方法进行尿液生物标志物发现研究的结果。