Literature DB >> 21242883

Gene expression changes are associated with loss of kidney graft function and interstitial fibrosis and tubular atrophy: diagnosis versus prediction.

Mariano J Scian1, Daniel G Maluf, Kellie J Archer, Jihee L Suh, David Massey, Ryan C Fassnacht, Benjamin Whitehill, Amit Sharma, Anne King, Todd Gehr, Adrian Cotterell, Marc P Posner, Valeria Mas.   

Abstract

BACKGROUND: Loss of kidney graft function due to interstitial fibrosis (IF) and tubular atrophy (TA) is the most common cause of kidney allograft loss.
METHODS: One hundred one allograft tissues (26 samples with IF/TA, 17 normal allografts, and an independent biopsy group collected at 3 month [n=34] posttransplantation) underwent microarray analysis to identify early detection/diagnostic biomarkers of IF/TA. Profiling of 24 allograft biopsies collected at or after 9-month posttransplantation (range 9-18 months) was used for validation. Three-month posttransplantation biopsies were classified as IF/TA nonprogressors (group 1) or progressors (group 2) using graft function and histology at 9-month posttransplantation.
RESULTS: We identified 2223 differentially expressed probe sets between IF/TA and normal allograft biopsies using a Bonferroni correction. Genes up-regulated in IF/TA were primarily involved in pathways related to T-cell activation, natural killer cell-mediated cytotoxicity, and programmed cell death. A least absolute shrinkage and selection operator model was derived from the differentially expressed probe sets, resulting in a final model that included 10 probe sets and had 100% training set accuracy. The N-fold crossvalidated error was 2.4% (sensitivity 95.8% and specificity 100%). When 3-month biopsies were tested using the model, all the samples were classified as normal. However, evaluating gene expression of the 3-month biopsies and fitting a new penalized model, 100% sensitivity was observed in classifying the samples as group1 or 2. This model was evaluated in the sample set collected at or after 9-month posttransplantation.
CONCLUSIONS: An IF/TA gene expression signature was identified, and it was useful for diagnosis but not prediction. However, gene expression profiles at 3 months might predict IF/TA progression.

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Year:  2011        PMID: 21242883      PMCID: PMC7936857          DOI: 10.1097/TP.0b013e3182094a5a

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


  41 in total

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2.  Banff 07 classification of renal allograft pathology: updates and future directions.

Authors:  K Solez; R B Colvin; L C Racusen; M Haas; B Sis; M Mengel; P F Halloran; W Baldwin; G Banfi; A B Collins; F Cosio; D S R David; C Drachenberg; G Einecke; A B Fogo; I W Gibson; D Glotz; S S Iskandar; E Kraus; E Lerut; R B Mannon; M Mihatsch; B J Nankivell; V Nickeleit; J C Papadimitriou; P Randhawa; H Regele; K Renaudin; I Roberts; D Seron; R N Smith; M Valente
Journal:  Am J Transplant       Date:  2008-02-19       Impact factor: 8.086

3.  Granzymes and cell death.

Authors:  Denis Martinvalet; Jerome Thiery; Dipanjan Chowdhury
Journal:  Methods Enzymol       Date:  2008       Impact factor: 1.600

4.  Intragraft expression of the IL-10 gene is up-regulated in renal protocol biopsies with early interstitial fibrosis, tubular atrophy, and subclinical rejection.

Authors:  Miguel Hueso; Estanis Navarro; Francesc Moreso; Francisco O'Valle; Mercè Pérez-Riba; Raimundo García Del Moral; Josep M Grinyó; Daniel Serón
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Review 5.  CD40-CD40 ligand.

Authors:  C van Kooten; J Banchereau
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6.  A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.

Authors:  A S Levey; J P Bosch; J B Lewis; T Greene; N Rogers; D Roth
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7.  Molecular pathways involved in loss of kidney graft function with tubular atrophy and interstitial fibrosis.

Authors:  Daniel G Maluf; Valeria R Mas; Kellie J Archer; Kenneth Yanek; Eric M Gibney; Anne L King; Adrian Cotterell; Robert A Fisher; Marc P Posner
Journal:  Mol Med       Date:  2008 May-Jun       Impact factor: 6.354

8.  Natural history, risk factors, and impact of subclinical rejection in kidney transplantation.

Authors:  Brian J Nankivell; Richard J Borrows; Caroline L-S Fung; Philip J O'Connell; Richard D M Allen; Jeremy R Chapman
Journal:  Transplantation       Date:  2004-07-27       Impact factor: 4.939

9.  Bioconductor: open software development for computational biology and bioinformatics.

Authors:  Robert C Gentleman; Vincent J Carey; Douglas M Bates; Ben Bolstad; Marcel Dettling; Sandrine Dudoit; Byron Ellis; Laurent Gautier; Yongchao Ge; Jeff Gentry; Kurt Hornik; Torsten Hothorn; Wolfgang Huber; Stefano Iacus; Rafael Irizarry; Friedrich Leisch; Cheng Li; Martin Maechler; Anthony J Rossini; Gunther Sawitzki; Colin Smith; Gordon Smyth; Luke Tierney; Jean Y H Yang; Jianhua Zhang
Journal:  Genome Biol       Date:  2004-09-15       Impact factor: 13.583

Review 10.  Chronic allograft nephropathy.

Authors:  Jeffery T Fletcher; Brian J Nankivell; Stephen I Alexander
Journal:  Pediatr Nephrol       Date:  2008-06-27       Impact factor: 3.714

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  15 in total

1.  Upregulation of miR-142-3p in peripheral blood mononuclear cells of operationally tolerant patients with a renal transplant.

Authors:  Richard Danger; Annaïck Pallier; Magali Giral; Marc Martínez-Llordella; Juan José Lozano; Nicolas Degauque; Alberto Sanchez-Fueyo; Jean-Paul Soulillou; Sophie Brouard
Journal:  J Am Soc Nephrol       Date:  2012-01-26       Impact factor: 10.121

2.  Progressive histological damage in renal allografts is associated with expression of innate and adaptive immunity genes.

Authors:  Maarten Naesens; Purvesh Khatri; Li Li; Tara K Sigdel; Matthew J Vitalone; Rong Chen; Atul J Butte; Oscar Salvatierra; Minnie M Sarwal
Journal:  Kidney Int       Date:  2011-08-31       Impact factor: 10.612

Review 3.  Dendritic cells and macrophages in the kidney: a spectrum of good and evil.

Authors:  Natasha M Rogers; David A Ferenbach; Jeffrey S Isenberg; Angus W Thomson; Jeremy Hughes
Journal:  Nat Rev Nephrol       Date:  2014-09-30       Impact factor: 28.314

Review 4.  Renal interstitial fibrosis: mechanisms and evaluation.

Authors:  Alton B Farris; Robert B Colvin
Journal:  Curr Opin Nephrol Hypertens       Date:  2012-05       Impact factor: 2.894

Review 5.  Epigenetics in Kidney Transplantation: Current Evidence, Predictions, and Future Research Directions.

Authors:  Valeria R Mas; Thu H Le; Daniel G Maluf
Journal:  Transplantation       Date:  2016-01       Impact factor: 4.939

6.  Identification of biomarkers to assess organ quality and predict posttransplantation outcomes.

Authors:  Mariano J Scian; Daniel G Maluf; Kellie J Archer; Stephen D Turner; Jihee L Suh; Krystle G David; Anne L King; Marc P Posner; Kenneth L Brayman; Valeria R Mas
Journal:  Transplantation       Date:  2012-10-27       Impact factor: 4.939

7.  MicroRNA profiles in allograft tissues and paired urines associate with chronic allograft dysfunction with IF/TA.

Authors:  M J Scian; D G Maluf; K G David; K J Archer; J L Suh; A R Wolen; M U Mba; H D Massey; A L King; T Gehr; A Cotterell; M Posner; V Mas
Journal:  Am J Transplant       Date:  2011-07-27       Impact factor: 8.086

8.  Effects of DNA Methylation on Progression to Interstitial Fibrosis and Tubular Atrophy in Renal Allograft Biopsies: A Multi-Omics Approach.

Authors:  S V Bontha; D G Maluf; K J Archer; C I Dumur; M G Dozmorov; A L King; E Akalin; T F Mueller; L Gallon; V R Mas
Journal:  Am J Transplant       Date:  2017-07-08       Impact factor: 8.086

9.  Factors affecting the accuracy of a class prediction model in gene expression data.

Authors:  Putri W Novianti; Victor L Jong; Kit C B Roes; Marinus J C Eijkemans
Journal:  BMC Bioinformatics       Date:  2015-06-21       Impact factor: 3.169

10.  The urine microRNA profile may help monitor post-transplant renal graft function.

Authors:  Daniel G Maluf; Catherine I Dumur; Jihee L Suh; Mariano J Scian; Anne L King; Helen Cathro; Jae K Lee; Ricardo C Gehrau; Kenneth L Brayman; Lorenzo Gallon; Valeria R Mas
Journal:  Kidney Int       Date:  2013-09-11       Impact factor: 10.612

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