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Urine Biomarkers Predict the Cause of Glomerular Disease

Sanju A. Varghese^*, T. Brian Powell^*, Milos N. Budisavljevic^*,, Jim C. Oates^*, John R. Raymond^*,, Jonas S. Almeida and John M. Arthur^*,

^* Department of Medicine, Medical University of South Carolina, and Department of Medicine, Ralph H. Johnson VA Medical Center, Charleston, South Carolina; and Department of Biostatistics and Applied Mathematics, University of Texas MD Anderson Cancer Center, Houston, Texas

Address correspondence to: Dr. John M. Arthur, Department of Medicine, Division of Nephrology, Medical University of South Carolina, 96 Jonathan Lucas Street, P.O. Box 250623, Charleston, SC 29425. Phone: 843-792-4123; Fax: 843-792-8399; E-mail: arthurj{at}musc.edu

Received for publication July 21, 2006. Accepted for publication December 26, 2006.

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, -1 microglobulin, zinc -2 glycoprotein, -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.

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