Dataset Information

The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study.

ABSTRACT:

Background

Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR.

Methods and findings

We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART) study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set--the Kidney Solid Organ Response Test (kSORT)--was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC]?= 0.94; 95% CI 0.91-0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88-1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86-0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials.

Conclusions

The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants. Please see later in the article for the Editors' Summary.

SUBMITTER: Roedder S

PROVIDER: S-EPMC4227654 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Publications

The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study.

Roedder Silke S Sigdel Tara T Salomonis Nathan N Hsieh Sue S Dai Hong H Bestard Oriol O Metes Diana D Zeevi Adriana A Gritsch Albin A Cheeseman Jennifer J Macedo Camila C Peddy Ram R Medeiros Mara M Vincenti Flavio F Asher Nancy N Salvatierra Oscar O Shapiro Ron R Kirk Allan A Reed Elaine F EF Sarwal Minnie M MM

PLoS medicine 20141111 11

<h4>Background</h4>Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR.<h4>Methods and findings</h4>We developed a no ...[more]

PMID: 25386950

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Project description:Acute rejection (AR) is closely associated with renal allograft dysfunction. Here, we utilised RNA sequencing (RNA-Seq) and bioinformatic methods to characterise the peripheral blood mononuclear cells (PBMCs) of patients with acute renal allograft rejection. Pretransplant blood samples were collected from 32 kidney allograft donors and 42 corresponding recipients with biopsies classified as T cell-mediated rejection (TCMR, n = 18), antibody-mediated rejection (ABMR, n = 5), and normal/non-specific changes (non-AR, n = 19). The patients with TCMR and ABMR were assigned to the AR group, and the patients with normal/non-specific changes (n = 19) were assigned to the non-AR group. We analysed RNA-Seq data for identifying differentially expressed genes (DEGs), and then gene ontology (GO) analysis, Reactome, and ingenuity pathway analysis (IPA), protein-protein interaction (PPI) network, and cell-type enrichment analysis were utilised for bioinformatics analysis. We identified DEGs in the PBMCs of the non-AR group when compared with the AR, ABMR, and TCMR groups. Pathway and GO analysis showed significant inflammatory responses, complement activation, interleukin-10 (IL-10) signalling pathways, classical antibody-mediated complement activation pathways, etc., which were significantly enriched in the DEGs. PPI analysis showed that IL-10, VEGFA, CXCL8, MMP9, and several histone-related genes were the hub genes with the highest degree scores. Moreover, IPA analysis showed that several proinflammatory pathways were upregulated, whereas antiinflammatory pathways were downregulated. The combination of NFSF14+TANK+ANKRD 33 B +HSPA1B was able to discriminate between AR and non-AR with an AUC of 92.3% (95% CI 82.8-100). Characterisation of PBMCs by RNA-Seq and bioinformatics analysis demonstrated gene signatures and biological pathways associated with AR. Our study may provide the foundation for the discovery of biomarkers and an in-depth understanding of acute renal allograft rejection.

Dataset Information

The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study.

Background

Methods and findings

Conclusions

Publications

The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study.

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