Details

Autor(en) / Beteiligte

• Roedder, Silke
• Sigdel, Tara
• Salomonis, Nathan
• Hsieh, Sue
• Dai, Hong
• Bestard, Oriol
• Metes, Diana
• Zeevi, Adriana
• Zeevi, Andrea
• Gritsch, Albin
• Cheeseman, Jennifer
• Macedo, Camila
• Peddy, Ram
• Medeiros, Mara
• Vincenti, Flavio
• Asher, Nancy
• Salvatierra, Oscar
• Shapiro, Ron
• Kirk, Allan
• Reed, Elaine F
• Reed, Elaine
• Sarwal, Minnie M
• Remuzzi, Giuseppe

Titel

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

Ist Teil von

• PLoS medicine, 2014-11, Vol.11 (11), p.e1001759

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2014

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. 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. 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.