Literature DB >> 23009139

A peripheral blood diagnostic test for acute rejection in renal transplantation.

L Li1, P Khatri, T K Sigdel, T Tran, L Ying, M J Vitalone, A Chen, S Hsieh, H Dai, M Zhang, M Naesens, V Zarkhin, P Sansanwal, R Chen, M Mindrinos, W Xiao, M Benfield, R B Ettenger, V Dharnidharka, R Mathias, A Portale, R McDonald, W Harmon, D Kershaw, V M Vehaskari, E Kamil, H J Baluarte, B Warady, R Davis, A J Butte, O Salvatierra, M M Sarwal.   

Abstract

Monitoring of renal graft status through peripheral blood (PB) rather than invasive biopsy is important as it will lessen the risk of infection and other stresses, while reducing the costs of rejection diagnosis. Blood gene biomarker panels were discovered by microarrays at a single center and subsequently validated and cross-validated by QPCR in the NIH SNSO1 randomized study from 12 US pediatric transplant programs. A total of 367 unique human PB samples, each paired with a graft biopsy for centralized, blinded phenotype classification, were analyzed (115 acute rejection (AR), 180 stable and 72 other causes of graft injury). Of the differentially expressed genes by microarray, Q-PCR analysis of a five gene-set (DUSP1, PBEF1, PSEN1, MAPK9 and NKTR) classified AR with high accuracy. A logistic regression model was built on independent training-set (n = 47) and validated on independent test-set (n = 198)samples, discriminating AR from STA with 91% sensitivity and 94% specificity and AR from all other non-AR phenotypes with 91% sensitivity and 90% specificity. The 5-gene set can diagnose AR potentially avoiding the need for invasive renal biopsy. These data support the conduct of a prospective study to validate the clinical predictive utility of this diagnostic tool. © Copyright 2012 The American Society of Transplantation and the American Society of Transplant Surgeons.

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Year:  2012        PMID: 23009139      PMCID: PMC4148014          DOI: 10.1111/j.1600-6143.2012.04253.x

Source DB:  PubMed          Journal:  Am J Transplant        ISSN: 1600-6135            Impact factor:   8.086


  31 in total

1.  Significance analysis of microarrays applied to the ionizing radiation response.

Authors:  V G Tusher; R Tibshirani; G Chu
Journal:  Proc Natl Acad Sci U S A       Date:  2001-04-17       Impact factor: 11.205

2.  DNA hybridization to mismatched templates: a chip study.

Authors:  Felix Naef; Daniel A Lim; Nila Patil; Marcelo Magnasco
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-04-09

3.  A solution to the problem of separation in logistic regression.

Authors:  Georg Heinze; Michael Schemper
Journal:  Stat Med       Date:  2002-08-30       Impact factor: 2.373

4.  A comparative investigation of methods for logistic regression with separated or nearly separated data.

Authors:  Georg Heinze
Journal:  Stat Med       Date:  2006-12-30       Impact factor: 2.373

5.  Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.

Authors:  A A Alizadeh; M B Eisen; R E Davis; C Ma; I S Lossos; A Rosenwald; J C Boldrick; H Sabet; T Tran; X Yu; J I Powell; L Yang; G E Marti; T Moore; J Hudson; L Lu; D B Lewis; R Tibshirani; G Sherlock; W C Chan; T C Greiner; D D Weisenburger; J O Armitage; R Warnke; R Levy; W Wilson; M R Grever; J C Byrd; D Botstein; P O Brown; L M Staudt
Journal:  Nature       Date:  2000-02-03       Impact factor: 49.962

6.  Complete steroid avoidance is effective and safe in children with renal transplants: a multicenter randomized trial with three-year follow-up.

Authors:  M M Sarwal; R B Ettenger; V Dharnidharka; M Benfield; R Mathias; A Portale; R McDonald; W Harmon; D Kershaw; V M Vehaskari; E Kamil; H J Baluarte; B Warady; L Tang; J Liu; L Li; M Naesens; T Sigdel; Janie Waskerwitz; O Salvatierra
Journal:  Am J Transplant       Date:  2012-06-13       Impact factor: 8.086

7.  Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling.

Authors:  Minnie Sarwal; Mei-Sze Chua; Neeraja Kambham; Szu-Chuan Hsieh; Thomas Satterwhite; Marilyn Masek; Oscar Salvatierra
Journal:  N Engl J Med       Date:  2003-07-10       Impact factor: 91.245

Review 8.  Monocytes in the rat: phenotype and function during acute allograft rejection.

Authors:  B Steiniger; O Stehling; A Scriba; V Grau
Journal:  Immunol Rev       Date:  2001-12       Impact factor: 12.988

9.  Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes.

Authors:  Stuart M Flechner; Sunil M Kurian; Steven R Head; Starlette M Sharp; Thomas C Whisenant; Jie Zhang; Jeffrey D Chismar; Steve Horvath; Tony Mondala; Timothy Gilmartin; Daniel J Cook; Steven A Kay; John R Walker; Daniel R Salomon
Journal:  Am J Transplant       Date:  2004-09       Impact factor: 8.086

10.  Identification of regulatory T cells in tolerated allografts.

Authors:  Luis Graca; Stephen P Cobbold; Herman Waldmann
Journal:  J Exp Med       Date:  2002-06-17       Impact factor: 14.307

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  55 in total

1.  Transcriptional Perturbations in Graft Rejection.

Authors:  Matthew J Vitalone; Tara K Sigdel; Nathan Salomonis; Reuben D Sarwal; Szu-Chuan Hsieh; Minnie M Sarwal
Journal:  Transplantation       Date:  2015-09       Impact factor: 4.939

2.  Transplantation: Biomarkers in transplantation—the devil is in the detail.

Authors:  Michael Abecassis; Bruce Kaplan
Journal:  Nat Rev Nephrol       Date:  2015-01-27       Impact factor: 28.314

3.  A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection.

Authors:  Weijia Zhang; Zhengzi Yi; Karen L Keung; Huimin Shang; Chengguo Wei; Paolo Cravedi; Zeguo Sun; Caixia Xi; Christopher Woytovich; Samira Farouk; Weiqing Huang; Khadija Banu; Lorenzo Gallon; Ciara N Magee; Nader Najafian; Milagros Samaniego; Arjang Djamali; Stephen I Alexander; Ivy A Rosales; Rex Neal Smith; Jenny Xiang; Evelyne Lerut; Dirk Kuypers; Maarten Naesens; Philip J O'Connell; Robert Colvin; Madhav C Menon; Barbara Murphy
Journal:  J Am Soc Nephrol       Date:  2019-07-05       Impact factor: 10.121

Review 4.  Biomarkers to detect rejection after kidney transplantation.

Authors:  Vikas R Dharnidharka; Andrew Malone
Journal:  Pediatr Nephrol       Date:  2017-06-19       Impact factor: 3.714

Review 5.  Moving Biomarkers toward Clinical Implementation in Kidney Transplantation.

Authors:  Madhav C Menon; Barbara Murphy; Peter S Heeger
Journal:  J Am Soc Nephrol       Date:  2017-01-06       Impact factor: 10.121

Review 6.  Transplant genetics and genomics.

Authors:  Joshua Y C Yang; Minnie M Sarwal
Journal:  Nat Rev Genet       Date:  2017-03-13       Impact factor: 53.242

Review 7.  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

8.  Proteoforms in Peripheral Blood Mononuclear Cells as Novel Rejection Biomarkers in Liver Transplant Recipients.

Authors:  T K Toby; M Abecassis; K Kim; P M Thomas; R T Fellers; R D LeDuc; N L Kelleher; J Demetris; J Levitsky
Journal:  Am J Transplant       Date:  2017-06-27       Impact factor: 8.086

Review 9.  Through a glass darkly: seeking clarity in preventing late kidney transplant failure.

Authors:  Mark D Stegall; Robert S Gaston; Fernando G Cosio; Arthur Matas
Journal:  J Am Soc Nephrol       Date:  2014-08-05       Impact factor: 10.121

10.  The clinical impact of humoral immunity in pediatric renal transplantation.

Authors:  Abanti Chaudhuri; Mikki Ozawa; Matthew J Everly; Robert Ettenger; Vikas Dharnidharka; Mark Benfield; Robert Mathias; Anthony Portale; Ruth McDonald; William Harmon; David Kershaw; V Matti Vehaskari; Elaine Kamil; H Jorge Baluarte; Bradley Warady; Li Li; Tara K Sigdel; Szu-chuan Hsieh; Hong Dai; Maarten Naesens; Janie Waskerwitz; Oscar Salvatierra; Paul I Terasaki; Minnie M Sarwal
Journal:  J Am Soc Nephrol       Date:  2013-02-28       Impact factor: 10.121

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