Urine biomarkers predict the cause of glomerular disease
Urine biomarkers predict the cause of glomerular disease
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DOI：
10.1681/asn.2006070767
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发表时间：
2007-03-01
影响因子：
13.6
通讯作者：
Arthur, John M.
中科院分区：
文献类型：
--
作者：
Varghese, Sanju A.;Powell, T. Brian;Arthur, John M.
诊断引起肾病综合征的肾小球疾病的类型对于适当的治疗是必要的，通常需要肾活检。本研究的目的是确定诊断肾小球疾病的候选蛋白质生物标志物。蛋白质组学方法和信息学分析用于确定尿蛋白的模式是疾病的特征。对32例FSGS、狼疮性肾炎、膜性肾病、糖尿病肾病患者的尿蛋白进行了双向电泳分离。来自16名患者的蛋白质丰度被用来训练人工神经网络来创建预测算法。其余16例患者作为外部验证集，检验预测算法的准确性。在验证集中，该模型预测疾病存在的敏感性在75 - 86%之间，特异性在92 - 67%之间。在小说集合中偶然获得这些结果的概率是5 X 10（-8）。21个凝胶点对疾病的鉴别最重要。从凝胶上切下斑点，用质谱法鉴定出20个为11种血浆蛋白的电荷形式：类Orosomucoid、转铁蛋白、α -1微球蛋白、锌α -2糖蛋白、α -1抗胰蛋白酶、补体因子B、触珠蛋白、转甲状腺素、血浆视黄醇结合蛋白、白蛋白和血凝素。这些数据表明引起肾病综合征的疾病以特征性模式改变肾小球蛋白通透性。尿蛋白电荷形态指纹鉴别肾小球疾病。鉴定的蛋白质是候选的生物标志物，可以在更适合临床测试的分析中进行测试。
Diagnosis of the type of glomerular disease that causes the nephrotic syndrome is necessary for appropriate treatment and typically requires a renal biopsy. The goal of this study was to identify candidate protein biomarkers to diagnose glomerular diseases. Proteomic methods and informatic analysis were used to identify patterns of urine proteins that are characteristic of the diseases. Urine proteins were separated by two-dimensional electrophoresis in 32 patients with FSGS, lupus nephritis, membranous nephropathy, or diabetic nephropathy. Protein abundances from 16 patients were used to train an artificial neural network to create a prediction algorithm. The remaining 16 patients were used as an external validation set to test the accuracy of the prediction algorithm. In the validation set, the model predicted the presence of the diseases with sensitivities between 75 and 86% and specificities from 92 to 67%. The probability of obtaining these results in the novel set by chance is 5 X 10(-8). Twenty-one gel spots were most important for the differentiation of the diseases. The spots were cut from the gel, and 20 were identified by mass spectrometry as charge forms of 11 plasma proteins: Orosomucoid, transferrin, alpha-1 microglobulin, zinc alpha-2 glycoprotein, alpha-1 antitrypsin, complement factor B, haptoglobin, transthyretin, plasma retinol binding protein, albumin, and hemopexin. These data show that diseases that cause nephrotic syndrome change glomerular protein permeability in characteristic patterns. The fingerprint of urine protein charge forms identifies the glomerular disease. The identified proteins are candidate biomarkers that can be tested in assays that are more amenable to clinical testing.