Gene expression biomarkers for kidney transplant rejection - The entire landscape

MicroRNAs as Potential Graft Rejection or Tolerance Biomarkers and Their Dilemma in Clinical Routines Behaving like Devilish, Angelic, or Frightening Elements

Allograft rejection is a widespread complication in allograft recipients with chronic kidney disease. Undertreatment of subclinical and clinical rejection and later post-transplant problems are caused by an imperfect understanding of the mechanisms at play and a lack of adequate diagnostic tools. Many different biomarkers have been analyzed and proposed to detect and monitor these crucial events in transplant outcomes. In this sense, microRNAs may help diagnose rejection or tolerance and indicate appropriate treatment, especially in patients with chronic allograft rejection. As key epigenetic regulators of physiological homeostasis, microRNAs have therapeutic potential and may indicate allograft tolerance or rejection. However, more evidence and clinical validation are indispensable before microRNAs are ready for clinical prime time.

Integrative Analysis of Prognostic Biomarkers for Acute Rejection in Kidney Transplant Recipients

BACKGROUND

Noninvasive biomarkers may predict adverse events such as acute rejection after kidney transplantation and may be preferable to existing methods because of superior accuracy and convenience. It is uncertain how these biomarkers, often derived from a single study, perform across different cohorts of recipients.

METHODS

Using a cross-validation framework that evaluates the performance of biomarkers, the aim of this study was to devise an integrated gene signature set that predicts acute rejection in kidney transplant recipients. Inclusion criteria were publicly available datasets of gene signatures that reported acute rejection episodes after kidney transplantation. We tested the predictive probability for acute rejection using gene signatures within individual datasets and validated the set using other datasets. Eight eligible studies of 1454 participants, with a total of 512 acute rejections episodes were included.

RESULTS

All sets of gene signatures had good positive and negative predictive values (79%-96%) for acute rejection within their own cohorts, but the predictability reduced to <50% when tested in other independent datasets. By integrating signature sets with high specificity scores across all studies, a set of 150 genes (included CXCL6, CXCL11, OLFM4, and PSG9) which are known to be associated with immune responses, had reasonable predictive values (varied between 69% and 90%).

CONCLUSIONS

A set of gene signatures for acute rejection derived from a specific cohort of kidney transplant recipients do not appear to provide adequate prediction in an independent cohort of transplant recipients. However, the integration of gene signature sets with high specificity scores may improve the prediction performance of these markers.

MicroRNA Expression Changes in Kidney Transplant: Diagnostic Efficacy of miR-150-5p as Potential Rejection Biomarker, Pilot Study

Background: The kidney allograft biopsy is considered the gold standard for rejection diagnosis but is invasive and could be indeterminate. Several publications point to the role of miRNA expression in suggesting its involvement in the acceptance or rejection of organ transplantation. This study aimed to analyze microRNAs involved in the differentiation and activation of B and T lymphocytes from kidney transplant (KT) patients’ peripheral blood leukocytes to be used as biomarkers of acute renal rejection (AR). Methods: A total of 15 KT patients with and without acute rejection (AR/NAR) were analyzed and quantified by miRNA PCR array. A total of 84 miRNAs related to lymphocyte differentiation and activation B and T were studied. The functions and biological pathways were analyzed to predict the potential targets of differential expressed miRNAs. Results: Six miRNA were increased in the AR group (miR-191-5p, miR-223-3p, miR-346, miR-423-5p, miR-574-3p, and miR-181d) and miR-150-5p was increased in the NAR group. In silico studies showed a total of 2603 target genes for the increased miRNAs in AR, while for the decrease miRNA, a total of 1107 target-potential genes were found. Conclusions: Our results show that KT with AR shows a decrease in miR-150-5p expression compared to NAR, suggesting that the decrease in miR-150-5p could be related to an increased MBD6 whose deregulation could have clinical consequences.