Literature DB >> 24549629

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

Beatrice Stubendorff1, Stephanie Finke, Martina Walter, Olaf Kniemeyer, Ferdinand von Eggeling, Torsten Gruschwitz, Thomas Steiner, Undine Ott, Gunter Wolf, Heiko Wunderlich, Kerstin Junker.   

Abstract

PURPOSE: Early diagnosis of acute rejection and effective immunosuppressive therapy lead to improvement in graft survival following kidney transplantation. In this study, we aimed to establish a urinary protein profile suitable to distinguish between patients with rejection and stable graft function and to predict acute rejection based on postoperatively collected urine samples. A further objective was to identify candidate proteins for the use as biomarkers in clinical practice.
METHODS: Urine samples of 116 kidney recipients were included. Rejection was proven by biopsy (n = 58), and stable transplant function was monitored for at least 2 years (n = 58). Postoperative urine samples were collected between 3rd and 10th day following transplantation. Urinary protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Protein identification and validation were performed using multiplex fluorescence 2DE, peptide mass fingerprinting and enzyme-linked immunosorbent assay.
RESULTS: A protein profile including four mass peaks differentiated acute rejection from stable transplants at the time point of rejection and at the postoperative state with 73 % sensitivity and 88 % specificity. Alpha-1-microglobulin (A1MG) and Haptoglobin (Hp) were identified as putative rejection biomarkers. Protein levels were significantly higher in postoperative urine from patients with rejection (A1MG 29.13 vs. 22.06 μg/ml, p = 0.001; Hp 628.34 vs. 248.57 ng/ml, p = 0.003). The combination of both proteins enabled the diagnosis of early rejection with 85 % sensitivity and 80 % specificity.
CONCLUSION: Protein profiling using mass spectrometry is suitable for noninvasive detection of rejection-specific changes following kidney transplantation. A specific protein profile enables the prediction of early acute allograft rejection in the immediate postoperative period. A1MG and Hp appear to be reliable rejection biomarkers.

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Year:  2014        PMID: 24549629     DOI: 10.1007/s00345-014-1263-z

Source DB:  PubMed          Journal:  World J Urol        ISSN: 0724-4983            Impact factor:   4.226


  19 in total

1.  Noninvasive diagnosis of renal-allograft rejection by measurement of messenger RNA for perforin and granzyme B in urine.

Authors:  B Li; C Hartono; R Ding; V K Sharma; R Ramaswamy; B Qian; D Serur; J Mouradian; J E Schwartz; M Suthanthiran
Journal:  N Engl J Med       Date:  2001-03-29       Impact factor: 91.245

2.  Long-term renal allograft survival: have we made significant progress or is it time to rethink our analytic and therapeutic strategies?

Authors:  Herwig-Ulf Meier-Kriesche; Jesse D Schold; Bruce Kaplan
Journal:  Am J Transplant       Date:  2004-08       Impact factor: 8.086

3.  Systematic evaluation of sample preparation methods for gel-based human urinary proteomics: quantity, quality, and variability.

Authors:  Visith Thongboonkerd; Somchai Chutipongtanate; Rattiyaporn Kanlaya
Journal:  J Proteome Res       Date:  2006-01       Impact factor: 4.466

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

Authors:  Olaf Reichelt; Jörg Müller; Ferdinand von Eggeling; Dominik Driesch; Heiko Wunderlich; Jörg Schubert; Hermann-Josef Gröne; Günther Stein; Undine Ott; Kerstin Junker
Journal:  Urology       Date:  2006-03       Impact factor: 2.649

5.  Causes of long-term graft failure in renal transplantation.

Authors:  K Tanabe; K Takahashi; H Toma
Journal:  World J Urol       Date:  1996       Impact factor: 4.226

6.  Femtomole sequencing of proteins from polyacrylamide gels by nano-electrospray mass spectrometry.

Authors:  M Wilm; A Shevchenko; T Houthaeve; S Breit; L Schweigerer; T Fotsis; M Mann
Journal:  Nature       Date:  1996-02-01       Impact factor: 49.962

7.  Serum levels of alpha-1 microglobulin in recipients of renal allografts.

Authors:  L Bäckman; O Ringdén; F Dati
Journal:  Transpl Int       Date:  1989-04       Impact factor: 3.782

8.  Serial evaluation of cell surface markers for immune activation after acute renal allograft rejection by urine flow cytometry--correlation with clinical outcome.

Authors:  I Roberti; L Reisman
Journal:  Transplantation       Date:  2001-05-15       Impact factor: 4.939

9.  Bioinformatic analysis of the urine proteome of acute allograft rejection.

Authors:  Edmond O'Riordan; Tatyana N Orlova; Jianfeng Mei J; Khalid Butt; Praveen M Chander; Shafiq Rahman; Muong Mya; Rena Hu; Jahangir Momin; Elizabeth W Eng; Dierk J Hampel; Bertram Hartman; Matthias Kretzler; Veronica Delaney; Michael S Goligorsky
Journal:  J Am Soc Nephrol       Date:  2004-12       Impact factor: 10.121

10.  Kidney graft survival in Europe and the United States: strikingly different long-term outcomes.

Authors:  Adam Gondos; Bernd Döhler; Hermann Brenner; Gerhard Opelz
Journal:  Transplantation       Date:  2013-01-27       Impact factor: 4.939

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  7 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

Review 2.  Detection of inflammatory biomarkers in saliva and urine: Potential in diagnosis, prevention, and treatment for chronic diseases.

Authors:  Sahdeo Prasad; Amit K Tyagi; Bharat B Aggarwal
Journal:  Exp Biol Med (Maywood)       Date:  2016-03-24

3.  Mesangial cells, specialized renal pericytes and cytomegalovirus infectivity: Implications for HCMV pathology in the glomerular vascular unit and post-transplant renal disease.

Authors:  Waldemar Popik; Hernan Correa; Atanu Khatua; David M Aronoff; Donald J Alcendor
Journal:  J Transl Sci       Date:  2018-05-24

Review 4.  Update on the human and mouse lipocalin (LCN) gene family, including evidence the mouse Mup cluster is result of an "evolutionary bloom".

Authors:  Georgia Charkoftaki; Yewei Wang; Monica McAndrews; Elspeth A Bruford; David C Thompson; Vasilis Vasiliou; Daniel W Nebert
Journal:  Hum Genomics       Date:  2019-02-19       Impact factor: 4.639

Review 5.  Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection.

Authors:  Luís M Ramalhete; Rúben Araújo; Aníbal Ferreira; Cecília R C Calado
Journal:  Proteomes       Date:  2022-07-02

6.  iTRAQ plasma proteomics analysis for candidate biomarkers of type 2 incipient diabetic nephropathy.

Authors:  Hongmei Lu; Shaodong Deng; Minghui Zheng; Kunhua Hu
Journal:  Clin Proteomics       Date:  2019-07-31       Impact factor: 3.988

7.  The Amniotic Fluid Proteome Differs Significantly between Donor and Recipient Fetuses in Pregnancies Complicated by Twin-to-Twin Transfusion Syndrome.

Authors:  Sun Min Kim; Byoung Kyu Cho; Byoung Jae Kim; Ha Yun Lee; Errol R Norwitz; Min Jueng Kang; Seung Mi Lee; Chan Wook Park; Jong Kwan Jun; Eugene C Yi; Joong Shin Park
Journal:  J Korean Med Sci       Date:  2020-03-16       Impact factor: 2.153

  7 in total

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