Literature DB >> 16763371

Urinary proteome of steroid-sensitive and steroid-resistant idiopathic nephrotic syndrome of childhood.

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.

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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


  21 in total

1.  Urine proteomics for profiling of human disease using high accuracy mass spectrometry.

Authors:  Alex Kentsis; Flavio Monigatti; Kevin Dorff; Fabien Campagne; Richard Bachur; Hanno Steen
Journal:  Proteomics Clin Appl       Date:  2009-09-01       Impact factor: 3.494

2.  A method for isolation and identification of urinary biomarkers in patients with diabetic nephropathy.

Authors:  Wayne G Fisher; Jessica E Lucas; Uzma F Mehdi; Danna W Qunibi; Harold R Garner; Kevin P Rosenblatt; Robert D Toto
Journal:  Proteomics Clin Appl       Date:  2011-12       Impact factor: 3.494

Review 3.  Application of proteomic analysis to the study of renal diseases.

Authors:  Matthew P Welberry Smith; Rosamonde E Banks; Steven L Wood; Andrew J P Lewington; Peter J Selby
Journal:  Nat Rev Nephrol       Date:  2009-10-27       Impact factor: 28.314

Review 4.  The nephrologist of tomorrow: towards a kidney-omic future.

Authors:  Mina H Hanna; Alessandra Dalla Gassa; Gert Mayer; Gianluigi Zaza; Patrick D Brophy; Loreto Gesualdo; Francesco Pesce
Journal:  Pediatr Nephrol       Date:  2016-03-09       Impact factor: 3.714

5.  Urinary N-acetyl-beta-D glucosaminidase (NAG) level in idiopathic nephrotic syndrome.

Authors:  Om P Mishra; Priyanka Jain; Pradeep Srivastava; Rajniti Prasad
Journal:  Pediatr Nephrol       Date:  2011-11-05       Impact factor: 3.714

6.  NGAL distinguishes steroid sensitivity in idiopathic nephrotic syndrome.

Authors:  Michael R Bennett; Nuntawan Piyaphanee; Kimberly Czech; Mark Mitsnefes; Prasad Devarajan
Journal:  Pediatr Nephrol       Date:  2011-12-27       Impact factor: 3.714

7.  Urine proteomics to detect biomarkers for chronic allograft dysfunction.

Authors:  Luís F Quintana; Amanda Solé-Gonzalez; Susana G Kalko; Elisenda Bañon-Maneus; Manel Solé; Fritz Diekmann; Alex Gutierrez-Dalmau; Joaquin Abian; Josep M Campistol
Journal:  J Am Soc Nephrol       Date:  2008-12-03       Impact factor: 10.121

Review 8.  Adapting mass spectrometry-based platforms for clinical proteomics applications: The capillary electrophoresis coupled mass spectrometry paradigm.

Authors:  Jochen Metzger; Peter B Luppa; David M Good; Harald Mischak
Journal:  Crit Rev Clin Lab Sci       Date:  2009       Impact factor: 6.250

9.  Non-invasive markers of ureteropelvic junction obstruction.

Authors:  Stephane Decramer; Jean-Loup Bascands; Joost P Schanstra
Journal:  World J Urol       Date:  2007-08-14       Impact factor: 4.226

Review 10.  Defining nephrotic syndrome from an integrative genomics perspective.

Authors:  Matthew G Sampson; Jeffrey B Hodgin; Matthias Kretzler
Journal:  Pediatr Nephrol       Date:  2014-06-03       Impact factor: 3.714

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