Molecular classifiers for acute kidney transplant rejection in peripheral blood by whole genome gene expression profiling

Abstract

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.

Keywords: Acute dysfunction with no rejection; acute kidney rejection; gene expression profiling; microarrays; molecular classifiers.

Conflict of interest statement

Disclosure

The authors of this manuscript have conflicts of interest to disclose as described by the American Journal of Transplantation. SRH, DRS, SMK and MMA are founding scientists and have ownership stock in Transplant Genomics, Inc.

© Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.

Figures

Figure 1

Flow chart describing the cohort and bootstrapping strategies for biomarker discovery and validation.

Figure 2

Performance of the 200-probeset nearest centroids (NC) classifier discovered and locked in the discovery cohort tested on the validation cohort based on area under the curve (AUC).

Figure 3

Performance of the 200-probeset nearest centroids (NC) classifier discovered and locked in the discovery cohort using a one-by-one validation on 30 randomly selected samples (10 AR, 10 ADNR and 10 TX) from the validation cohort based on area under the curve (AUC). ADNR, acute dysfunction with no rejection by biopsy histology; AR, acute rejection; TX, excellent functioning transplant.