Use of Quantitative Real Time Polymerase Chain Reaction to Assess Gene Transcripts Associated With Antibody-Mediated Rejection of Kidney Transplants.

Transplantation

1 Centre for Complement and Inflammation Research, Division of Immunology and Inflammation, Department of Medicine, Imperial College, London, United Kingdom. 2 Department of Cellular Pathology, Hammersmith Hospital, London, United Kingdom. 3 Imperial College Kidney and Transplant Institute, Hammersmith Hospital, London, United Kingdom. 4 Histocompatibility and Immunogenetics Laboratory, Imperial College Healthcare NHS Trust, London, United Kingdom. 5 Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College, London, United Kingdom.

Published: September 2015

Introduction: Microarray studies have shown elevated transcript levels of endothelial and natural killer (NK) cell-associated genes during antibody-mediated rejection (AMR) of the renal allograft. This study aimed to assess the use of quantitative real-time polymerase chain reaction as an alternative to microarray analysis on a subset of these elevated genes.

Methods: Thirty-nine renal transplant biopsies from patients with de novo donor-specific antibodies and eighteen 1-year surveillance biopsies with no histological evidence of rejection were analyzed for expression of 11 genes previously identified as elevated in AMR.

Results: Expression levels of natural killer markers were correlated to microcirculation inflammation and graft outcomes to a greater extent than endothelial markers. Creating a predictive model reduced the number of gene transcripts to be assessed to 2, SH2D1b and MYBL1, resulting in 66.7% sensitivity and 89.7% specificity for graft loss.

Discussion: This work demonstrates that elevated gene expression levels, proposed to be associated with AMR, can be detected by established quantitative real-time polymerase chain reaction technology, making transition to the clinical setting feasible. Transcript analysis provides additional diagnostic information to the classification schema for AMR diagnosis but it remains to be determined whether significant numbers of centres will validate transcript analysis in their laboratories and put such analysis into clinical use.

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Source
http://dx.doi.org/10.1097/TP.0000000000000621DOI Listing

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