Literature DB >> 20931695

The molecular phenotype of kidney transplants.

P F Halloran1, D G de Freitas, G Einecke, K S Famulski, L G Hidalgo, M Mengel, J Reeve, J Sellares, B Sis.   

Abstract

Microarray studies of kidney transplant biopsies provide an opportunity to define the molecular phenotype. To facilitate this process, we used experimental systems to annotate transcripts as members of pathogenesis-based transcript sets (PBTs) representing biological processes in injured or diseased tissue. Applying this annotation to microarray results revealed that changes in single molecules and PBTs reflected a large-scale coordinate disturbance, stereotyped across various diseases and injuries, without absolute specificity of individual molecules or PBTs for rejection. Nevertheless, expression of molecules and PBTs was quantitatively specific: IFNG effects for rejection; T cell and macrophage transcripts for T cell-mediated rejection; endothelial and NK transcripts for antibody-mediated rejection. Various diseases and injuries induced the same injury-repair response, undetectable by histopathology, involving epithelium, stroma and endothelium, with increased expression of developmental, cell cycle and apoptosis genes and decreased expression of differentiated epithelial features. Transcripts reflecting this injury-repair response were the best correlates of functional disturbance and risk of future graft loss. Late biopsies with atrophy-fibrosis, reflecting their cumulative burden of injury, displayed more transcripts for B cells, plasma cells and mast cells. Thus the molecular phenotype is best described in terms of three elements: specific diseases, including rejection; the injury-repair response and the cumulative burden of injury.

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Year:  2010        PMID: 20931695     DOI: 10.1111/j.1600-6143.2010.03267.x

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


  25 in total

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Journal:  Inflamm Bowel Dis       Date:  2014-12       Impact factor: 5.325

2.  Variance component score test for time-course gene set analysis of longitudinal RNA-seq data.

Authors:  Denis Agniel; Boris P Hejblum
Journal:  Biostatistics       Date:  2017-10-01       Impact factor: 5.899

3.  Molecular remodeling of the renin-angiotensin system after kidney transplantation.

Authors:  Marlies Antlanger; Oliver Domenig; Johannes J Kovarik; Christopher C Kaltenecker; Chantal Kopecky; Marko Poglitsch; Marcus D Säemann
Journal:  J Renin Angiotensin Aldosterone Syst       Date:  2017 Apr-Jun       Impact factor: 1.636

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.  Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring.

Authors:  Michelle A Wood-Trageser; Andrew J Lesniak; Anthony J Demetris
Journal:  Transplantation       Date:  2019-07       Impact factor: 4.939

6.  B cells and kidney transplantation: beyond antibodies.

Authors:  Anita Mehrotra; Peter S Heeger
Journal:  J Am Soc Nephrol       Date:  2014-03-07       Impact factor: 10.121

7.  Applying rigor and reproducibility standards to assay donor-derived cell-free DNA as a non-invasive method for detection of acute rejection and graft injury after heart transplantation.

Authors:  Sean Agbor-Enoh; Ilker Tunc; Iwijn De Vlaminck; Ulgen Fideli; Andrew Davis; Karen Cuttin; Kenneth Bhatti; Argit Marishta; Michael A Solomon; Annette Jackson; Grace Graninger; Bonnie Harper; Helen Luikart; Jennifer Wylie; Xujing Wang; Gerald Berry; Charles Marboe; Kiran Khush; Jun Zhu; Hannah Valantine
Journal:  J Heart Lung Transplant       Date:  2017-05-20       Impact factor: 10.247

8.  Molecular phenotypes of acute kidney injury in kidney transplants.

Authors:  Konrad S Famulski; Declan G de Freitas; Chatchai Kreepala; Jessica Chang; Joana Sellares; Banu Sis; Gunilla Einecke; Michael Mengel; Jeff Reeve; Philip F Halloran
Journal:  J Am Soc Nephrol       Date:  2012-02-16       Impact factor: 10.121

9.  RNA expression profiling of renal allografts in a nonhuman primate identifies variation in NK and endothelial gene expression.

Authors:  R N Smith; B A Adam; I A Rosales; M Matsunami; T Oura; A B Cosimi; T Kawai; M Mengel; R B Colvin
Journal:  Am J Transplant       Date:  2018-02-02       Impact factor: 8.086

10.  RNA expression profiling of nonhuman primate renal allograft rejection identifies tolerance.

Authors:  R N Smith; M Matsunami; B A Adam; I A Rosales; T Oura; A B Cosimi; T Kawai; M Mengel; R B Colvin
Journal:  Am J Transplant       Date:  2018-02-17       Impact factor: 8.086

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