Literature DB >> 22592886

Discovery and validation of a molecular signature for the noninvasive diagnosis of human renal allograft fibrosis.

Dany Anglicheau1, Thangamani Muthukumar, Aurélie Hummel, Ruchuang Ding, Vijay K Sharma, Darshana Dadhania, Surya V Seshan, Joseph E Schwartz, Manikkam Suthanthiran.   

Abstract

BACKGROUND: Tubulointerstitial fibrosis (fibrosis), a histologic feature associated with a failing kidney allograft, is diagnosed using the invasive allograft biopsy. A noninvasive diagnostic test for fibrosis may help improve allograft outcome.
METHODS: We obtained 114 urine specimens from 114 renal allograft recipients: 48 from 48 recipients with fibrosis in their biopsy results and 66 from 66 recipients with normal biopsy results. Levels of messenger RNAs (mRNAs) in urinary cells were measured using kinetic, quantitative polymerase chain reaction assays, and the levels were related to allograft diagnosis. A discovery set of 76 recipients (32 with allograft fibrosis and 44 with normal biopsy results) was used to develop a diagnostic signature, and an independent validation set of 38 recipients (16 with allograft fibrosis and 22 with normal biopsy results) was used to validate the signature.
RESULTS: In the discovery set, urinary cell levels of the following mRNAs were significantly associated with the presence of allograft fibrosis: vimentin (P<0.0001, logistic regression model), hepatocyte growth factor (P<0.0001), α-smooth muscle actin (P<0.0001), fibronectin 1 (P<0.0001), perforin (P=0.0002), plasminogen activator inhibitor 1 (P=0.0002), transforming growth factor β1 (P=0.0004), tissue inhibitor of metalloproteinase 1 (P=0.0009), granzyme B (P=0.0009), fibroblast-specific protein 1 (P=0.006), CD103 (P=0.02), and collagen 1A1 (P=0.04). A four-gene model composed of the levels of mRNA for vimentin, NKCC2, and E-cadherin and of 18S ribosomal RNA provided the most accurate, parsimonious diagnostic model of allograft fibrosis with a sensitivity of 93.8% and a specificity of 84.1% (P<0.0001). In the independent validation set, this same model predicted the presence of allograft fibrosis with a sensitivity of 77.3% and a specificity of 87.5% (P<0.0001).
CONCLUSIONS: Measurement of mRNAs in urinary cells may offer a noninvasive means of diagnosing fibrosis in human renal allografts.

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Year:  2012        PMID: 22592886      PMCID: PMC3377557          DOI: 10.1097/TP.0b013e31824ef181

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  45 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

Review 2.  Mechanisms of tubulointerstitial fibrosis.

Authors:  Michael Zeisberg; Eric G Neilson
Journal:  J Am Soc Nephrol       Date:  2010-09-23       Impact factor: 10.121

3.  Epithelial Notch signaling regulates interstitial fibrosis development in the kidneys of mice and humans.

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Journal:  J Clin Invest       Date:  2010-10-18       Impact factor: 14.808

Review 4.  Hepatocyte growth factor and the kidney.

Authors:  Youhua Liu
Journal:  Curr Opin Nephrol Hypertens       Date:  2002-01       Impact factor: 2.894

Review 5.  Chronic renal allograft damage: existing challenges.

Authors:  Manuel Arias; Daniel Serón; Francesc Moreso; Oriol Bestard; Manuel Praga
Journal:  Transplantation       Date:  2011-05-15       Impact factor: 4.939

6.  Hepatocyte growth factor suppresses interstitial fibrosis in a mouse model of obstructive nephropathy.

Authors:  S Mizuno; K Matsumoto; T Nakamura
Journal:  Kidney Int       Date:  2001-04       Impact factor: 10.612

7.  Endogenous hepatocyte growth factor ameliorates chronic renal injury by activating matrix degradation pathways.

Authors:  Y Liu; K Rajur; E Tolbert; L D Dworkin
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8.  A prospective randomized trial of three different sizes of core-cutting needle for renal transplant biopsy.

Authors:  M L Nicholson; T J Wheatley; T M Doughman; S A White; J D Morgan; P S Veitch; P N Furness
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9.  Reciprocal balance of hepatocyte growth factor and transforming growth factor-beta 1 in renal fibrosis in mice.

Authors:  S Mizuno; K Matsumoto; T Kurosawa; Y Mizuno-Horikawa; T Nakamura
Journal:  Kidney Int       Date:  2000-03       Impact factor: 10.612

10.  Increased levels of serum hepatocyte growth factor in patients with end-stage renal disease.

Authors:  J W Lohr; T P Lee; M Farooqui; B K Mookerjee
Journal:  J Med       Date:  2000
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  14 in total

1.  Multicenter evaluation of a standardized protocol for noninvasive gene expression profiling.

Authors:  K S Keslar; M Lin; A A Zmijewska; T K Sigdel; T Q Tran; L Ma; M Bhasin; P Rao; R Ding; D N Iklé; R B Mannon; M M Sarwal; T B Strom; E F Reed; P S Heeger; M Suthanthiran; R L Fairchild
Journal:  Am J Transplant       Date:  2013-07       Impact factor: 8.086

2.  Urinary cell mRNA profiles and differential diagnosis of acute kidney graft dysfunction.

Authors:  Marie Matignon; Ruchuang Ding; Darshana M Dadhania; Franco B Mueller; Choli Hartono; Catherine Snopkowski; Carol Li; John R Lee; Daniel Sjoberg; Surya V Seshan; Vijay K Sharma; Hua Yang; Bakr Nour; Andrew J Vickers; Manikkam Suthanthiran; Thangamani Muthukumar
Journal:  J Am Soc Nephrol       Date:  2014-03-07       Impact factor: 10.121

Review 3.  Allograft rejection and tubulointerstitial fibrosis in human kidney allografts: interrogation by urinary cell mRNA profiling.

Authors:  Thangamani Muthukumar; John R Lee; Darshana M Dadhania; Ruchuang Ding; Vijay K Sharma; Joseph E Schwartz; Manikkam Suthanthiran
Journal:  Transplant Rev (Orlando)       Date:  2014-05-27       Impact factor: 3.943

4.  Tumor suppressor ataxia telangiectasia mutated functions downstream of TGF-β1 in orchestrating profibrotic responses.

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5.  MicroRNA-146a in Human and Experimental Ischemic AKI: CXCL8-Dependent Mechanism of Action.

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Journal:  J Am Soc Nephrol       Date:  2016-07-21       Impact factor: 10.121

Review 6.  Molecular assessment of disease states in kidney transplant biopsy samples.

Authors:  Philip F Halloran; Konrad S Famulski; Jeff Reeve
Journal:  Nat Rev Nephrol       Date:  2016-06-27       Impact factor: 28.314

7.  Noninvasive prognostication of polyomavirus BK virus-associated nephropathy.

Authors:  Darshana Dadhania; Catherine Snopkowski; Thangamani Muthukumar; John Lee; Ruchuang Ding; Vijay K Sharma; Paul Christos; Heejung Bang; Sandip Kapur; Surya V Seshan; Manikkam Suthanthiran
Journal:  Transplantation       Date:  2013-07-27       Impact factor: 4.939

Review 8.  Urinary cell mRNA profiles predictive of human kidney allograft status.

Authors:  John R Lee; Thangamani Muthukumar; Darshana Dadhania; Ruchuang Ding; Vijay K Sharma; Joseph E Schwartz; Manikkam Suthanthiran
Journal:  Immunol Rev       Date:  2014-03       Impact factor: 12.988

Review 9.  The Use of Genomics and Pathway Analysis in Our Understanding and Prediction of Clinical Renal Transplant Injury.

Authors:  Madhav C Menon; Karen L Keung; Barbara Murphy; Philip J OʼConnell
Journal:  Transplantation       Date:  2016-07       Impact factor: 4.939

Review 10.  TGF-β1/p53 signaling in renal fibrogenesis.

Authors:  Stephen P Higgins; Yi Tang; Craig E Higgins; Badar Mian; Wenzheng Zhang; Ralf-Peter Czekay; Rohan Samarakoon; David J Conti; Paul J Higgins
Journal:  Cell Signal       Date:  2017-11-28       Impact factor: 4.315

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