Literature DB >> 16527560

Prediction of renal allograft rejection by urinary protein analysis using ProteinChip Arrays (surface-enhanced laser desorption/ionization time-of-flight mass spectrometry).

Olaf Reichelt1, Jörg Müller, Ferdinand von Eggeling, Dominik Driesch, Heiko Wunderlich, Jörg Schubert, Hermann-Josef Gröne, Günther Stein, Undine Ott, Kerstin Junker.   

Abstract

OBJECTIVES: To develop a noninvasive method for the detection of renal transplant rejection using ProteinChip Arrays (surface-enhanced laser desorption/ionization time-of-flight mass spectrometry).
METHODS: A total of 23 urine samples were collected from 13 patients showing biopsy-proven renal allograft rejection and from 10 patients without histologic signs of rejection. All 23 patients had clinical symptoms and signs of acute allograft rejection and underwent renal biopsy. Samples were centrifuged, and supernatants were directly spotted onto the ProteinChip arrays with different chromatographic surfaces. The obtained spectra in a range from 2 to 200 kDa were subjected to bioinformatic analysis using the method of Fuzzy c-means, followed by the establishment of rule bases and evaluation using the relevance index according to Kiendl.
RESULTS: Several protein peaks were identified allowing differentiation between rejection and no rejection. Using two different ProteinChip surfaces, we found two biomarkers at 25.71 kDa and 28.13 kDa that gave a diagnostic sensitivity of 90% and 93% and a specificity of 80% (SAX2) and 85% (CM10), respectively.
CONCLUSIONS: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry appears to be a promising new diagnostic tool for distinguishing renal transplant patients with no rejection from those with acute rejection.

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Year:  2006        PMID: 16527560     DOI: 10.1016/j.urology.2005.09.038

Source DB:  PubMed          Journal:  Urology        ISSN: 0090-4295            Impact factor:   2.649


  9 in total

Review 1.  Proteomics for rejection diagnosis in renal transplant patients: Where are we now?

Authors:  Wilfried Gwinner; Jochen Metzger; Holger Husi; David Marx
Journal:  World J Transplant       Date:  2016-03-24

2.  Shotgun proteomics identifies proteins specific for acute renal transplant rejection.

Authors:  Tara K Sigdel; Amit Kaushal; Marina Gritsenko; Angela D Norbeck; Wei-Jun Qian; Wenzhong Xiao; David G Camp; Richard D Smith; Minnie M Sarwal
Journal:  Proteomics Clin Appl       Date:  2010-01       Impact factor: 3.494

Review 3.  Profiling the proteome in renal transplantation.

Authors:  Tara K Sigdel; Sangho Lee; Minnie M Sarwal
Journal:  Proteomics Clin Appl       Date:  2011-04-26       Impact factor: 3.494

4.  Urine protein profiling identified alpha-1-microglobulin and haptoglobin as biomarkers for early diagnosis of acute allograft rejection following kidney transplantation.

Authors:  Beatrice Stubendorff; Stephanie Finke; Martina Walter; Olaf Kniemeyer; Ferdinand von Eggeling; Torsten Gruschwitz; Thomas Steiner; Undine Ott; Gunter Wolf; Heiko Wunderlich; Kerstin Junker
Journal:  World J Urol       Date:  2014-02-19       Impact factor: 4.226

Review 5.  The proteogenomic path towards biomarker discovery.

Authors:  Tara K Sigdel; Minnie M Sarwal
Journal:  Pediatr Transplant       Date:  2008-08-22

Review 6.  Deconvoluting the 'omics' for organ transplantation.

Authors:  Minnie M Sarwal
Journal:  Curr Opin Organ Transplant       Date:  2009-10       Impact factor: 2.640

7.  Current literature in mass spectrometry.

Authors: 
Journal:  J Mass Spectrom       Date:  2007-01       Impact factor: 1.982

8.  Urinary proteomic shotgun approach for identification of potential acute rejection biomarkers in renal transplant recipients.

Authors:  Håvard Loftheim; Karsten Midtvedt; Anders Hartmann; Anna V Reisæter; Pål Falck; Hallvard Holdaas; Trond Jenssen; Leon Reubsaet; Anders Asberg
Journal:  Transplant Res       Date:  2012-08-31

9.  Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation.

Authors:  Dirk Woetzel; Rene Huber; Peter Kupfer; Dirk Pohlers; Michael Pfaff; Dominik Driesch; Thomas Häupl; Dirk Koczan; Peter Stiehl; Reinhard Guthke; Raimund W Kinne
Journal:  Arthritis Res Ther       Date:  2014-04-01       Impact factor: 5.156

  9 in total

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