Despite the advances in immunosuppression, renal allograft attrition over time remains unabated due to chronic allograft dysfunction (CAD) with interstitial fibrosis (IF) and tubular atrophy (TA). We aimed to evaluate microRNA (miRNA) signatures in CAD with IF/TA and appraise correlation with paired urine samples and potential utility in prospective evaluation of graft function. MicroRNA signatures were established between CAD with IF/TA vs. normal allografts by microarray. Validation of the microarray results and prospective evaluation of urine samples was performed using RT-qPCR. Fifty-six miRNAs were identified in samples with CAD-IF/TA. Five miRNAs were selected for further validation based on: array fold change, p-value and in silico predicted mRNA targets. We confirmed the differential expression of these 5 miRNAs by RT-qPCR using an independent set of samples. Differential expression was detected for miR-142-3p, miR-204, miR-107, and miR-211 (P<0.001) and miR-32 (p<0.05). Furthermore, differential expression of miR-142-3p (p<0.01), miR-204 (p<0.01) and miR-211 (p<0.05) was also observed between patient groups in urine samples. A characteristic miRNA signature for IF/TA that correlates with paired urine samples was identified. These results support the potential use of miRNAs as non-invasive markers of IF/TA and for monitoring graft function.

Non-invasive, cost-effective biomarkers that allow accurate monitoring of graft function are needed in kidney transplantation. Since microRNAs (miRNAs) have emerged as promising disease biomarkers we sought to establish an miRNA signature in urinary cell pellets comparing kidney transplant patients diagnosed with chronic allograft dysfunction (CAD) with interstitial fibrosis and tubular atrophy and those recipients with normal graft function. Overall, we evaluated 191 samples from 125 deceased donor primary kidney transplant recipients in the discovery, initial validation and the longitudinal validation studies for non-invasive monitoring of graft function. Of 1,733 mature miRNAs studied using microarrays, 22 were found to be differentially expressed between groups. Ontology and pathway analyses showed inflammation as the principal biological function associated with these miRNAs. Twelve selected miRNAs were longitudinally evaluated in urine samples of an independent set of 66 patients, at two time-points post-kidney transplant. A subset of these miRNAs was found to be differentially expressed between groups early post-kidney transplant before histological allograft injury was evident. Thus, a panel of urine miRNAs was identified as potential biomarkers for monitoring graft function and anticipating progression to CAD in kidney transplant patients.

Background Severe liver steatosis is a known risk factor for increased ischemia-reperfusion injury (IRI) and poor outcomes post liver transplantation (LT). This study aimed to identify steatosis-related molecular mechanisms associated with IRI exacerbation post-LT. Methods Paired graft biopsies (n=60) were collected at pre-implantation (L1) and 90 min post-reperfusion (L2). LT recipients (n=30) were classified by graft macrosteatosis: without steatosis or ≤5% (WS, n=13) and with steatosis ≥25% (S, n=17). Plasma samples were collected at L1, L2, and 1-day post-LT (POD1) for cytokines evaluation. Tissue RNA was isolated for gene expression microarrays. Probeset summaries were obtained using RMA algorithm. Pairwise comparisons were fit using two-sample t-test. P-values ≤0.01 were significant (FDR <5%). Molecular pathway analyses were conducted using IPA tool. Results Significantly differentially expressed genes were identified for WS and S grafts, post-reperfusion. Comprehensive comparison analysis of molecular profiles revealed significant association of S grafts molecular profile with innate immune response activation, macrophages production of nitric oxide and reactive oxygen species, IL-6, IL-8, IL-10 signaling activation, recruitment of granulocytes, and accumulation of myeloid cells. Post-reperfusion histological patterns of S grafts revealed neutrophilic infiltration surrounding fat accumulation. Circulating pro-inflammatory cytokines at post-reperfusion and 24 hours post-LT concurred with intra-graft deregulated molecular pathways. All tested cytokines were significantly increased in plasma of S grafts recipients at post-reperfusion when compared with WS group at same time. Conclusions Increases of graft steatosis exacerbate IRI by exacerbation of innate immune response post-LT. Preemptive strategies should consider it for safety usage of steatotic livers.

An IF/TA gene expression signature was identified, and it was useful for diagnosis but not prediction. However, gene expression profiles at 3 months might predict IF/TA progression.

Acute cellular rejection (ACR) and hepatitis C virus (HCV) recurrence (HCVrec) are common complications after liver transplantation (LT) in HCV patients, who share common clinical and histological features, making a differential diagnosis difficult. Fiftythree liver allograft samples from unique HCV LT recipients were studied using microarrays, including a training set (n = 32) and a validation set (n = 19). Two no-HCV-ACR samples from LT recipients were also included. Probe set intensity values were obtained using the robust multiarray average method (RMA) method. Analysis of variance identified statistically differentially expressed genes (P ≤ 0.005). The limma package was used to fit the mixed-effects models using a restricted maximum likelihood procedure. The last absolute shrinkage and selection operator (LASSO) model was fit with HCVrec versus ACR as the dependent variable predicted. N-fold cross-validation was performed to provide an unbiased estimate of generalization error. A total of 179 probe sets were differentially expressed among groups, with 71 exclusive genes between HCVrec and HCV-ACR. No differences were found within ACR group (HCV-ACR vs. no-HCV-ACR). Supervised clustering analysis displayed two clearly independent groups, and no-HCV-ACR clustered within HCV-ACR. HCVrec-related genes were associated with a cytotoxic T-cell profile, and HCV-ACR-related genes were associated with the inflammatory response. The best-fitting LASSO model classifier accuracy, including 15 genes, has an accuracy of 100% in the training set. N-fold cross-validation accuracy was 78.1%, and sensitivity, specificity and positive and negative predictive values were 50.0%, 90.9%, 71.4% and 80.0%, respectively. Arginase type II (ARG2), ethylmalonic encephalopathy 1 (ETHE1), transmembrane protein 176A (TMEM176A) and TMEM176B genes were significantly confirmed in the validation set. A molecular signature capable of distinguishing HCVrec and ACR in HCV LT recipients was identified and validated.