Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection

Abstract

Summary Transcriptomics could contribute significantly to the early and specific diagnosis of rejection episodes by defining ‘molecular Banff’ signatures. Recently, the description of pathogenesis‐based transcript sets offered a new opportunity for objective and quantitative diagnosis. Generating high‐quality transcript panels is thus critical to define high‐performance diagnostic classifier. In this study, a comparative analysis was performed across four different microarray datasets of heterogeneous sample collections from two published clinical datasets and two own datasets including biopsies for clinical indication, and samples from nonhuman primates. We characterized a common transcriptional profile of 70 genes, defined as acute rejection transcript set (ARTS). ARTS expression is significantly up‐regulated in all AR samples as compared with stable allografts or healthy kidneys, and strongly correlates with the severity of Banff AR types. Similarly, ARTS were tested as a classifier in a large collection of 143 independent biopsies recently published by the University of Alberta. Results demonstrate that the ‘in silico’ approach applied in this study is able to identify a robust and reliable molecular signature for AR, supporting a specific and sensitive molecular diagnostic approach for renal transplant monitoring.

Fibrosis with Inflammation at One Year Predicts Transplant Functional Decline

“…Second, we found that IFϩi was associated with upregulation of immune/ inflammatory pathways linked with acute cellular rejection. [17][18][19][20][21][22][23] The results lend credence to the view that early surveillance histology with or without targeted molecular analysis provides important prognostic information. 10,24 They also suggest that analysis of intragraft innate and adaptive immune pathways during early posttransplantation years 25 may provide the basis for interventions to subvert chronic deterioration in a subset of recipients with clinical expectations of excellent long-term outcome.…”

“…22,23 Most striking, gene expression signatures associated with cytotoxic T lymphocytes, IFN-␥ response, B cells, and acute rejection were heavily enriched in IFϩi compared with normal and IF-alone groups (Supplemental Tables S2 and S3). Microarrays were also carried out on T4 biopsies from the three groups and were compared in a paired manner with the results of T12 microarrays to determine expression changes over time of acute rejection-associated genes.…”

“…Microarrays were also carried out on T4 biopsies from the three groups and were compared in a paired manner with the results of T12 microarrays to determine expression changes over time of acute rejection-associated genes. 23 Between T4 and T12, only the IFϩi group demonstrated altered expression of a substantial proportion (38%) of the acute rejection-associated genes (Supplemental Table S3). Finally, we sought to determine whether the biological responses of renal parenchymal cells could be distinguished from those of infiltrating leukocytes.…”

Potential Impact of Microarray Diagnosis of T Cell–Mediated Rejection in Kidney Transplants: The INTERCOM Study

“…While many investigators have analyzed molecular changes in biopsies with histologic rejection, using either RT-PCR (17,18) or microarrays (19)(20)(21), these studies failed to distinguish TCMR from antibody-mediated rejection (ABMR), in part because the criteria for diagnosing ABMR, particularly C4d-negative ABMR, are evolving and remain controversial (22,23). Because of this, we established the Alberta Transplant Applied Genomics Centre (ATAGC) Reference Standard histology system (http://atagc.med.ualberta.ca/) in a prospective cohort of 403 indication biopsies (the BFC403 cohort).…”

Pharmacogenomics: a new paradigm to personalize treatments in nephrology patients

“…Nephrology researchers have begun to employ these innovative high-throughput procedures to identify the whole basal expression profile of normal or pathological human kidney [100], to select biomarkers predicting acute and chronic allograft outcomes [101,102] and to assess more clearly the intricate molecular pathways associated to the pathogenesis and onset of several immunological renal diseases [103,104]. On the contrary, only few reports to date have been published describing the multi-genetic influence on drug response in nephrology.…”