| Literature DB >> 16763371 |
Robert P Woroniecki1, Tatyana N Orlova, Natasha Mendelev, Ibrahim F Shatat, Susan M Hailpern, Frederick J Kaskel, Michael S Goligorsky, Edmond O'Riordan.
Abstract
The response to steroid therapy is used to characterize the idiopathic nephrotic syndrome (INS) of childhood as either steroid-sensitive (SSNS) or steroid-resistant (SRNS), a classification with a better prognostic capability than renal biopsy. The majority (approximately 80%) of INS is due to minimal change disease but the percentage of focal and segmental glomerulosclerosis is increasing. We applied a new technological platform to examine the urine proteome to determine if different urinary protein excretion profiles could differentiate patients with SSNS from those with SRNS. Twenty-five patients with INS and 17 control patients were studied. Mid-stream urines were analyzed using surface enhanced laser desorption and ionization mass spectrometry(SELDI-MS). Data were analyzed using multiple bioinformatic techniques. Patient classification was performed using Biomarker Pattern Software and a generalized form of Adaboost and predictive models were generated using a supervised algorithm with cross-validation. Urinary proteomic data distinguished INS patients from control patients, irrespective of steroid response, with a sensitivity of 92.3%, specificity of 93.7%, positive predictive value of 96% and a negative predictive value of 88.2%. Classification of patients as SSNS or SRNS was 100%. A protein of mass 4,144 daltons was identified as the single most important classifier in distinguishing SSNS from SRNS. SELDI-MS combined with bioinformatics can identify different proteomic patterns in INS. Characterization of the proteins of interest identified by this proteomic approach with prospective clinical validation may yield a valuable clinical tool for the non-invasive prediction of treatment response and prognosis. Copyright 2006 S. Karger AG, Basel.Entities:
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Year: 2006 PMID: 16763371 DOI: 10.1159/000093814
Source DB: PubMed Journal: Am J Nephrol ISSN: 0250-8095 Impact factor: 3.754