Literature DB >> 22992769

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

Mariano J Scian1, 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.   

Abstract

UNLABELLED: The increased disparity between organ supply and need has led to the use of extended criteria donors and donation after cardiac death donors with other comorbidities.
METHODS: We have examined the preimplantation transcriptome of 112 kidney transplant recipient samples from 100 deceased-donor kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate (eGFR) at 1 month after transplantation: the GFR-high group (n=74) included patients with eGFR 45 mL/min per 1.73 m(2), whereas the GFR-low group (n=35) included patients with eGFR 45 mL/min or less per 1.73 m(2).
RESULTS: Gene expression profiling identified higher expression of 160 probe sets (140 genes) in the GFR-low group, whereas expression of 37 probe sets (33 genes) was higher in the GFR-high group (P<0.01, false discovery rate <0.2). Four genes (CCL5, CXCR4, ITGB2, and EGF) were selected based on fold change and P value and further validated using an independent set of samples. A random forest analysis identified three of these genes (CCL5, CXCR4, and ITGB2) as important predictors of graft function after transplantation.
CONCLUSIONS: Inclusion of pretransplantation molecular gene expression profiles in donor quality assessment systems may provide the necessary information for better donor organ selection and function prediction. These biomarkers would further allow a more objective and complete assessment of procured renal allografts at pretransplantation time.

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Year:  2012        PMID: 22992769      PMCID: PMC3927314          DOI: 10.1097/TP.0b013e318263702b

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


  29 in total

1.  The reliability of pre-transplant donor renal biopsies (PTDB) in predicting the kidney state. A comparative single-centre study on 154 untransplanted kidneys.

Authors:  Gianna Mazzucco; Corrado Magnani; Mirella Fortunato; Annalisa Todesco; Guido Monga
Journal:  Nephrol Dial Transplant       Date:  2010-03-31       Impact factor: 5.992

Review 2.  Detection call algorithms for high-throughput gene expression microarray data.

Authors:  Kellie J Archer; Sarah E Reese
Journal:  Brief Bioinform       Date:  2009-11-25       Impact factor: 11.622

3.  Chemokines and their receptors in human renal allotransplantation.

Authors:  Denise J Lo; Tim A Weaver; David E Kleiner; Roslyn B Mannon; Lynn M Jacobson; Bryan N Becker; S John Swanson; Douglas A Hale; Allan D Kirk
Journal:  Transplantation       Date:  2011-01-15       Impact factor: 4.939

4.  Severe glomerular sclerosis is not associated with poor outcome after kidney transplantation.

Authors:  A D Lu; D Desai; B D Myers; D C Dafoe; E J Alfrey
Journal:  Am J Surg       Date:  2000-12       Impact factor: 2.565

5.  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
Journal:  Ann Intern Med       Date:  1999-03-16       Impact factor: 25.391

6.  In renal transplants with delayed graft function chemokines and chemokine receptor expression predict long-term allograft function.

Authors:  Ralf Dikow; Luis E Becker; Matthias Schaier; Rüdiger Waldherr; Marie-Luise Gross; Martin Zeier
Journal:  Transplantation       Date:  2010-10-15       Impact factor: 4.939

7.  Genome-wide gene-expression patterns of donor kidney biopsies distinguish primary allograft function.

Authors:  Peter Hauser; Christoph Schwarz; Christa Mitterbauer; Heinz M Regele; Ferdinand Mühlbacher; Gert Mayer; Paul Perco; Bernd Mayer; Timothy W Meyer; Rainer Oberbauer
Journal:  Lab Invest       Date:  2004-03       Impact factor: 5.662

8.  T cells expressing allograft inflammatory factor 1 display increased chemotaxis and induce a profibrotic phenotype in normal fibroblasts in vitro.

Authors:  Francesco Del Galdo; Sergio A Jiménez
Journal:  Arthritis Rheum       Date:  2007-10

9.  Development and current status of ECD kidney transplantation.

Authors:  Randall S Sung; Mary K Guidinger; Laura L Christensen; Valarie B Ashby; Robert M Merion; Alan B Leichtman; Friedrich K Port
Journal:  Clin Transpl       Date:  2005

10.  Cytoscape 2.8: new features for data integration and network visualization.

Authors:  Michael E Smoot; Keiichiro Ono; Johannes Ruscheinski; Peng-Liang Wang; Trey Ideker
Journal:  Bioinformatics       Date:  2010-12-12       Impact factor: 6.937

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  5 in total

Review 1.  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

Review 2.  Biomarkers for renal transplantation: where are we?

Authors:  Fangmin Ge; Qiaoding Dai; Weihua Gong
Journal:  Int J Nephrol Renovasc Dis       Date:  2013-10-01

Review 3.  Assessment of Organ Quality in Kidney Transplantation by Molecular Analysis and Why It May Not Have Been Achieved, Yet.

Authors:  Seraina von Moos; Enver Akalin; Valeria Mas; Thomas F Mueller
Journal:  Front Immunol       Date:  2020-05-12       Impact factor: 7.561

4.  A New Data Analysis System to Quantify Associations between Biochemical Parameters of Chronic Kidney Disease-Mineral Bone Disease.

Authors:  Mariano Rodriguez; M Dolores Salmeron; Alejandro Martin-Malo; Carlo Barbieri; Flavio Mari; Rafael I Molina; Pedro Costa; Pedro Aljama
Journal:  PLoS One       Date:  2016-01-25       Impact factor: 3.240

5.  Validation of systems biology derived molecular markers of renal donor organ status associated with long term allograft function.

Authors:  Paul Perco; Andreas Heinzel; Johannes Leierer; Stefan Schneeberger; Claudia Bösmüller; Rupert Oberhuber; Silvia Wagner; Franziska Engler; Gert Mayer
Journal:  Sci Rep       Date:  2018-05-03       Impact factor: 4.379

  5 in total

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