2010 - Transplantomics and Biomarkers in Transplantation
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NOVEL APPLICATIONS FOR GENOMIC TECHNOLOGIES IN ORG
1.2 - RECLASSIFYING GRAFT INJURY BY GENOMICS
Presenter: Philip F., Halloran, Edmonton, Canada Authors: Philip F. Halloran
RECLASSIFYING GRAFT INJURY BY GENOMICS Philip F. Halloran, Director, Alberta Transplant Applied Genomics Centre; Distinguished University Professor, University of Alberta; Editor-in-Chief, American Journal of Transplantation; Edmonton, AB, Canada
1. To understand how the molecular features of a biopsy add to the other features such as anti HLA, clinical state, biopsy histopathology, in predicting diagnosis and outcomes.
2. To examine the general implications of these findings for understanding disease mechanisms.
3. To discuss the platforms by which this new knowledge can be made available to clinicians.
A new global view of the molecular changes in kidney transplant biopsies is emerging from data driven approaches. This approach uses iterative loops to define the relationship of molecular features to the other phenotypes: clinical (function, proteinuria), HLA antibody, biopsy histology, and outcomes in approximately 650 kidneys with microarray results. Analysis incorporates annotation in mouse models, class comparison and classifier approaches, principal component analysis. The troubled kidneys display striking stereotyping of changes reflecting key events: T cell and macrophage infiltration, IFNG effects, active injury response and dedifferentiation, and time dependent cumulative burden of injury changes. The Other diseases can then be defined by relative shifts in the molecular features of this stereotyped disturbance. Specificity for T cell mediated rejection is captured by selective changes in T cell and macrophage genes and alternative macrophage activation, whereas specific for antibody-mediated rejection is derived from endothelial and NK cell transcripts. The injury response is the best correlate of both functional disturbance and probability of graft loss. Time dependent changes in injured kidneys include B cell, plasma cell, and mast cell transcripts, but these have little impact in multivariate analysis when time is factored in, since late biopsies have an intrinsic high risk due to the diseases operating. Transcripts of potential diagnostic utility for ABMR include those associated with DSA in biopsies for cause.
The results indicate that:
1. TCMR is an intense inflammatory process with an excellent prognosis when ABMR is absent. 2. ABMR is a disease of endothelium and NK cells that is often C4d negative and not diagnosed. 3. The strong reflection of progression is the ongoing injury response, driven by disease processes that are unresponsive to therapy. To progress, one must have a potentially progressive disease, but the true predictor of progression is the injury response.
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