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. 2013 Dec 16;8(12):e82153.
doi: 10.1371/journal.pone.0082153. eCollection 2013.

Identification of Common Blood Gene Signatures for the Diagnosis of Renal and Cardiac Acute Allograft Rejection

Free PMC article

Identification of Common Blood Gene Signatures for the Diagnosis of Renal and Cardiac Acute Allograft Rejection

Li Li et al. PLoS One. .
Free PMC article


To test, whether 10 genes, diagnostic of renal allograft rejection in blood, are able to diagnose and predict cardiac allograft rejection, we analyzed 250 blood samples from heart transplant recipients with and without acute rejection (AR) and with cytomegalovirus (CMV) infection by QPCR. A QPCR-based logistic regression model was built on 5 of these 10 genes (AR threshold composite score >37% = AR) and tested for AR prediction in an independent set of 109 samples, where it correctly diagnosed AR with 89% accuracy, with no misclassifications for AR ISHLT grade 1b. CMV infection did not confound the AR score. The genes correctly diagnosed AR in a blood sample within 6 months prior to biopsy diagnosis with 80% sensitivity and untreated grade 1b AR episodes had persistently elevated scores until 6 months after biopsy diagnosis. The gene score was also correlated with presence or absence of cardiac allograft vasculopathy (CAV) irrespective of rejection grade. In conclusion, there is a common transcriptional axis of immunological trafficking in peripheral blood in both renal and cardiac organ transplant rejection, across a diverse recipient age range. A common gene signature, initially identified in the setting of renal transplant rejection, can be utilized serially after cardiac transplantation, to diagnose and predict biopsy confirmed acute heart transplant rejection.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Figure 1
Figure 1. Study Design: A peripheral blood 10-gene panel for Solid Organ Transplant Rejection.
A. The process of microarray discovery and QPCR validation of a 10 gene panel in 489 peripheral blood samples from pediatric and young adult renal transplant recipients, with validation of the gene biomarker panel in a prospective, randomized, multicenter trial (AUC = 0.937). B. The 10 genes were tested by QPCR in 141 peripheral blood samples from adult cardiac transplant recipients. A minimal logistic regression model of 5 genes was used for independent prediction for AR diagnosis in 86 samples and AR prediction prior to biopsy diagnosis.
Figure 2
Figure 2. Predicted Probability of AR in 141 Peripheral Blood samples from Adult Heart Transplant Recipients.
A. The predicted probability of a sample having a non-invasive diagnosis of AR, based on the logistic regression score on the 5-gene model is shown on the Y Axis (score range 0–100%). A score>37%, from the model, classifies a sample as AR, a score <37% from the model classifies a sample as non-AR. The score is shown on all 141 samples, inclusive of the training (n = 32; 11 Grade 3 AR, 21 STA) and the test set samples (12 CMV, 19 STA, 31 AR-Grade 1a, 22 AR-Grade 1b, 2 AR Grade 2). The clinical sample phenotype is based on the matched biopsy histology read. The misclassified samples from the histology read and the blood gene-model read are marked by asteryx. B. The Individual and group predicted probabilities for all 66 AR samples. The blood-gene model classifies all AR-Grade 1b correctly (a significant finding with p = 0.01, for classification of other AR grades). C. The predicted probabilities for AR for all Stable samples without any evidence of acute rejection (STA), with sampling times at different times post-transplantation. D. The predicted probabilities for AR for all 55 untreated AR samples (AR-Grades≤2), where no treatment intensification was given for the diagnosis of AR. Serial samples from these patients collected within 1–6 months prior (n = 11), or within 1–6 months after (n = 12), these AR episodes. The gene-model predicts AR prior to biopsy diagnosis and remains elevated in most samples without immunosuppression intensification.

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