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Microarray analysis of rejection in human kidney transplants using pathogenesis-based transcript sets.

Mueller TF, Einecke G, Reeve J, Sis B, Mengel M, Jhangri GS, Bunnag S, Cruz J, Wishart D, Meng C, Broderick G, Kaplan B, Halloran PF

Department of Medicine, Division of Nephrology and Immunology, University of Alberta, Edmonton, AB, Canada.

Microarrays offer potential for objective diagnosis and insights into pathogenesis of allograft rejection. We used mouse transplants to annotate pathogenesis-based transcript sets (PBTs) that reflect major biologic events in allograft rejection-cytotoxic T-cell infiltration, interferon-gamma effects and parenchymal deterioration. We examined the relationship between PBT expression, histopathologic lesions and clinical diagnoses in 143 consecutive human kidney transplant biopsies for cause. PBTs correlated strongly with one another, indicating that transcriptome disturbances in renal transplants have a stereotyped internal structure. This disturbance was continuous, not dichotomous, across rejection and nonrejection. PBTs correlated with histopathologic lesions and were the highest in biopsies with clinically apparent rejection episodes. Surprisingly, antibody-mediated rejection had changes similar to T-cell mediated rejection. Biopsies lacking PBT disturbances did not have rejection. PBTs suggested that some current Banff histopathology criteria are unreliable, particularly at the cut-off between borderline and rejection. Results were validated in 51 additional biopsies.Thus many transcriptome changes previously described in rejection are features of a large-scale disturbance characteristic of rejection but occurring at lower levels in many forms of injury. PBTs represent a quantitative measure of the inflammatory disturbances in organ transplants, and a new window on the mechanisms of these changes.

Published 6 November 2007 in Am J Transplant, 7(12): 2712-22.
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Microarrays Books

DNA Methylation Microarrays: Experimental Design and Statistical Analysis (Chapman & Hall/Crc Biostatistics Series)

DNA Methylation Microarrays: Experimental Design and Statistical Analysis (Chapman & Hall/Crc Biostatistics Series)