Literature DB >> 19056874

Urine proteomics to detect biomarkers for chronic allograft dysfunction.

Luís F Quintana1, Amanda Solé-Gonzalez, Susana G Kalko, Elisenda Bañon-Maneus, Manel Solé, Fritz Diekmann, Alex Gutierrez-Dalmau, Joaquin Abian, Josep M Campistol.   

Abstract

Despite optimal immunosuppressive therapy, more than 50% of kidney transplants fail because of chronic allograft dysfunction. A noninvasive means to diagnose chronic allograft dysfunction may allow earlier interventions that could improve graft half-life. In this proof-of-concept study, we used mass spectrometry to analyze differences in the urinary polypeptide patterns of 32 patients with chronic allograft dysfunction (14 with pure interstitial fibrosis and tubular atrophy and 18 with chronic active antibody-mediated rejection) and 18 control subjects (eight stable recipients and 10 healthy control subjects). Unsupervised hierarchical clustering showed good segregation of samples in groups corresponding mainly to the four biomedical conditions. Moreover, the composition of the proteome of the pure interstitial fibrosis and tubular atrophy group differed from that of the chronic active antibody-mediated rejection group, and an independent validation set confirmed these results. The 14 protein ions that best discriminated between these two groups correctly identified 100% of the patients with pure interstitial fibrosis and tubular atrophy and 100% of the patients with chronic active antibody-mediated rejection. In summary, this study establishes a pattern for two histologic lesions associated with distinct graft outcomes and constitutes a first step to designing a specific, noninvasive diagnostic tool for chronic allograft dysfunction.

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Year:  2008        PMID: 19056874      PMCID: PMC2637047          DOI: 10.1681/ASN.2007101137

Source DB:  PubMed          Journal:  J Am Soc Nephrol        ISSN: 1046-6673            Impact factor:   10.121


  31 in total

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3.  Excerpts from the United States Renal Data System 2003 Annual Data Report: atlas of end-stage renal disease in the United States.

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Journal:  Am J Kidney Dis       Date:  2003-12       Impact factor: 8.860

4.  Characterization of renal allograft rejection by urinary proteomic analysis.

Authors:  William Clarke; Benjamin C Silverman; Zhen Zhang; Daniel W Chan; Andrew S Klein; Ernesto P Molmenti
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Authors:  Bruce Kaplan; Herwig-Ulf Meier-Kriesche
Journal:  Am J Transplant       Date:  2002-11       Impact factor: 8.086

6.  The natural history of chronic allograft nephropathy.

Authors:  Brian J Nankivell; Richard J Borrows; Caroline L-S Fung; Philip J O'Connell; Richard D M Allen; Jeremy R Chapman
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7.  Peritubular capillary changes and C4d deposits are associated with transplant glomerulopathy but not IgA nephropathy.

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Journal:  Am J Transplant       Date:  2004-01       Impact factor: 8.086

8.  Antibody-mediated rejection criteria - an addition to the Banff 97 classification of renal allograft rejection.

Authors:  Lorraine C Racusen; Robert B Colvin; Kim Solez; Michael J Mihatsch; Philip F Halloran; Patricia M Campbell; Michael J Cecka; Jean-Pierre Cosyns; Anthony J Demetris; Michael C Fishbein; Agnes Fogo; Peter Furness; Ian W Gibson; Denis Glotz; Pekka Hayry; Lawrence Hunsickern; Michael Kashgarian; Ronald Kerman; Alex J Magil; Robert Montgomery; Kunio Morozumi; Volker Nickeleit; Parmjeet Randhawa; Heinz Regele; Daniel Seron; Surya Seshan; Stale Sund; Kiril Trpkov
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9.  Proteomic patterns of tumour subsets in non-small-cell lung cancer.

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10.  Proteomic-based detection of urine proteins associated with acute renal allograft rejection.

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Journal:  J Am Soc Nephrol       Date:  2004-01       Impact factor: 10.121

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  22 in total

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Journal:  Proteomics Clin Appl       Date:  2012-06       Impact factor: 3.494

Review 2.  Molecular diagnostics in transplantation.

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3.  Proteomic profiling of renal allograft rejection in serum using magnetic bead-based sample fractionation and MALDI-TOF MS.

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4.  Application of label-free quantitative peptidomics for the identification of urinary biomarkers of kidney chronic allograft dysfunction.

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Journal:  Mol Cell Proteomics       Date:  2009-04-07       Impact factor: 5.911

Review 5.  Application of proteomic analysis to the study of renal diseases.

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Review 6.  Detecting adaptive immunity: applications in transplantation monitoring.

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Review 7.  Urinary proteomics as a novel tool for biomarker discovery in kidney diseases.

Authors:  Jing Wu; Yi-ding Chen; Wei Gu
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Review 8.  Biomarkers and Pharmacogenomics in Kidney Transplantation.

Authors:  L E Crowley; M Mekki; S Chand
Journal:  Mol Diagn Ther       Date:  2018-10       Impact factor: 4.074

Review 9.  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

10.  A LASSO Method to Identify Protein Signature Predicting Post-transplant Renal Graft Survival.

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Journal:  Stat Biosci       Date:  2016-10-03
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