Faculty Collaboration Database

Urine biomarkers predict the cause of glomerular disease. J Am Soc Nephrol 2007 Mar;18(3):913-22

Date

02/16/2007

Pubmed ID

17301191

Pubmed Central ID

PMC2733832

DOI

10.1681/ASN.2006070767

Scopus ID

2-s2.0-33947270262 (requires institutional sign-in at Scopus site)   206 Citations

Abstract

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.

Author List

Varghese SA, Powell TB, Budisavljevic MN, Oates JC, Raymond JR, Almeida JS, Arthur JM

Author

John R. Raymond MD President, CEO, Professor in the President department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Adult
Aged
Algorithms
Biomarkers
Cluster Analysis
Creatinine
Diabetic Nephropathies
Female
Glomerulonephritis, Membranous
Glomerulosclerosis, Focal Segmental
Humans
Lupus Nephritis
Male
Middle Aged
Predictive Value of Tests
Proteinuria
Reproducibility of Results