Jihee L. Suh

MicroRNA profiles in allograft tissues and paired urines associate with chronic allograft dysfunction with IF/TA

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. MiRNA signatures were established between CAD with IF/TA versus normal allografts by microarray. Validation of the microarray results and prospective evaluation of urine samples was performed using real‐time quantitative‐PCR (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 five 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 noninvasive markers of IF/TA and for monitoring graft function.

The urine microRNA profile may help monitor post-transplant renal 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.

Gene Expression Changes Are Associated With Loss of Kidney Graft Function and Interstitial Fibrosis and Tubular Atrophy: Diagnosis Versus Prediction

Background. Loss of kidney graft function due to interstitial fibrosis (IF) and tubular atrophy (TA) is the most common cause of kidney allograft loss. Methods. One hundred one allograft tissues (26 samples with IF/TA, 17 normal allografts, and an independent biopsy group collected at 3 month [n=34] posttransplantation) underwent microarray analysis to identify early detection/diagnostic biomarkers of IF/TA. Profiling of 24 allograft biopsies collected at or after 9-month posttransplantation (range 9–18 months) was used for validation. Three-month posttransplantation biopsies were classified as IF/TA nonprogressors (group 1) or progressors (group 2) using graft function and histology at 9-month posttransplantation. Results. We identified 2223 differentially expressed probe sets between IF/TA and normal allograft biopsies using a Bonferroni correction. Genes up-regulated in IF/TA were primarily involved in pathways related to T-cell activation, natural killer cell-mediated cytotoxicity, and programmed cell death. A least absolute shrinkage and selection operator model was derived from the differentially expressed probe sets, resulting in a final model that included 10 probe sets and had 100% training set accuracy. The N-fold crossvalidated error was 2.4% (sensitivity 95.8% and specificity 100%). When 3-month biopsies were tested using the model, all the samples were classified as normal. However, evaluating gene expression of the 3-month biopsies and fitting a new penalized model, 100% sensitivity was observed in classifying the samples as group1 or 2. This model was evaluated in the sample set collected at or after 9-month posttransplantation. Conclusions. 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.

Molecular pathways differentiate hepatitis C virus (HCV) recurrence from acute cellular rejection in HCV liver recipients.

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. Fifty-three 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.

Evaluation of molecular profiles in calcineurin inhibitor toxicity post-kidney transplant: input to chronic allograft dysfunction.

The molecular basis of calcineurin inhibitor toxicity (CNIT) in kidney transplantation (KT) and its contribution to chronic allograft dysfunction (CAD) with interstitial fibrosis (IF) and tubular atrophy (TA) were evaluated by: (1) identifying specific CNIT molecular pathways that associate with allograft injury (cross‐sectional study) and (2) assessing the contribution of the identified CNIT signature in the progression to CAD with IF/TA (longitudinal study). Kidney biopsies from well‐selected transplant recipients with histological diagnosis of CNIT (n = 14), acute rejection (n = 13) and CAD with IF/TA (n = 10) were evaluated. Normal allografts (n = 18) were used as controls. To test CNIT contribution to CAD progression, an independent set of biopsies (n = 122) from 61 KT patients collected at 3 and ∼12 months post‐KT (range = 9–18) were evaluated. Patients were classified based on 2‐year post‐KT graft function and histological findings as progressors (n = 30) or nonprogressors to CAD (n = 31). Molecular signatures characterizing CNIT samples were identified. Patients classified as progressors showed an overlap of 7% and 22% with the CNIT signature at 3 and at ∼12 months post‐KT, respectively, while the overlap was <1% and 1% in nonprogressor patients, showing CNIT at the molecular level as a nonimmunological factor involved in the progression to CAD.

Donor Hepatic Steatosis Induce Exacerbated Ischemia-Reperfusion Injury Through Activation of Innate Immune Response Molecular Pathways.

Background Severe liver steatosis is a known risk factor for increased ischemia-reperfusion injury (IRI) and poor outcomes after liver transplantation (LT). This study aimed to identify steatosis-related molecular mechanisms associated with IRI exacerbation after LT. Methods Paired graft biopsies (n = 60) were collected before implantation (L1) and 90 minutes after reperfusion (L2). The LT recipients (n = 30) were classified by graft macrosteatosis: without steatosis (WS) of 5% or less (n = 13) and with steatosis (S) of 25% or greater (n = 17). Plasma samples were collected at L1, L2, and 1 day after LT (postoperative [POD]1) for cytokines evaluation. Tissue RNA was isolated for gene expression microarrays. Probeset summaries were obtained using robust multiarray average algorithm. Pairwise comparisons were fit using 2-sample t test. P values 0.01 or less were significant (false discovery rate <5%). Molecular pathway analyses were conducted using Ingenuity Pathway Analysis tool. Results Significantly differentially expressed genes were identified for WS and S grafts after reperfusion. Comprehensive comparison analysis of molecular profiles revealed significant association of S grafts molecular profile with innate immune response activation, macrophage production of nitric oxide and reactive oxygen species, IL-6, IL-8, IL-10 signaling activation, recruitment of granulocytes, and accumulation of myeloid cells. Postreperfusion histological patterns of S grafts revealed neutrophilic infiltration surrounding fat accumulation. Circulating proinflammatory cytokines after reperfusion and 24 hours after LT concurred with intragraft-deregulated molecular pathways. All tested cytokines were significantly increased in plasma of S grafts recipients after reperfusion when compared with WS group at same time. Conclusions Increases of graft steatosis exacerbate IRI by exacerbation of innate immune response after LT. Preemptive strategies should consider it for safety usage of steatotic livers.

Identification of Biomarkers to Assess Organ Quality and Predict Posttransplantation Outcomes

&NA; The increased disparity between organ supply and need has led to the use of extended criteria donors and donation after cardiac death donors with other comorbidities. Methods We have examined the preimplantation transcriptome of 112 kidney transplant recipient samples from 100 deceased-donor kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate (eGFR) at 1 month after transplantation: the GFR-high group (n=74) included patients with eGFR 45 mL/min per 1.73 m2, whereas the GFR-low group (n=35) included patients with eGFR 45 mL/min or less per 1.73 m2. Results Gene expression profiling identified higher expression of 160 probe sets (140 genes) in the GFR-low group, whereas expression of 37 probe sets (33 genes) was higher in the GFR-high group (P<0.01, false discovery rate <0.2). Four genes (CCL5, CXCR4, ITGB2, and EGF) were selected based on fold change and P value and further validated using an independent set of samples. A random forest analysis identified three of these genes (CCL5, CXCR4, and ITGB2) as important predictors of graft function after transplantation. Conclusions Inclusion of pretransplantation molecular gene expression profiles in donor quality assessment systems may provide the necessary information for better donor organ selection and function prediction. These biomarkers would further allow a more objective and complete assessment of procured renal allografts at pretransplantation time.

Pretransplant transcriptome profiles identify among kidneys with delayed graft function those with poorer quality and outcome.

Robust biomarkers are needed to identify donor kidneys with poor quality associated with inferior early and longer-term outcome. The occurrence of delayed graft function (DGF) is most often used as a clinical outcome marker to capture poor kidney quality. Gene expression profiles of 92 preimplantation biopsies were evaluated in relation to DGF and estimated glomerular filtration rate (eGFR) to identify preoperative gene transcript changes associated with short-term function. Patients were stratified into those who required dialysis during the first week (DGF group) versus those without (noDGF group) and subclassified according to 1-month eGFR of >45 mL/min (eGFRhi) versus eGFR of ≤45 mL/min (eGFRlo). The groups and subgroups were compared in relation to clinical donor and recipient variables and transcriptome-associated biological pathways. A validation set was used to confirm target genes. Donor and recipient characteristics were similar between the DGF versus noDGF groups. A total of 206 probe sets were significant between groups (P< 0.01), but the gene functional analyses failed to identify any significantly affected pathways. However, the subclassification of the DGF and noDGF groups identified 283 probe sets to be significant among groups and associated with biological pathways. Kidneys that developed postoperative DGF and sustained an impaired 1-month function (DGFlo group) showed a transcriptome profile of significant immune activation already preimplant. In addition, these kidneys maintained a poorer transplant function throughout the first-year posttransplant. In conclusion, DGF is a poor marker for organ quality and transplant outcome. In contrast, preimplant gene expression profiles identify “poor quality” grafts and may eventually improve organ allocation.

Transcriptome at the time of hepatitis C virus recurrence may predict the severity of fibrosis progression after liver transplantation

Allograft gene expression analysis may provide insights into the mechanisms involved in liver damage during hepatitis C virus recurrence (HCVrec) after orthotopic liver transplantation (OLT) and allow the identification of patients who have a higher risk of developing severe disease. Forty‐three OLT recipients with hepatitis C virus (HCV) were evaluated. Genomewide gene expression analysis was performed with formalin‐fixed, paraffin‐embedded (FFPE) liver biopsy samples obtained from 21 OLT recipients with HCV at the time of clinical HCVrec, which was defined as increased alanine aminotransferase levels and detectable HCV RNA levels in serum. Patients were classified into 3 groups according to the severity of the fibrosis in the liver biopsies at 36 months post‐OLT : group 1 (G1) for mild fibrosis (F0‐F1), group 2 for moderate fibrosis (F2), and group 3 (G3) for severe fibrosis (F3‐F4). No significant differences were observed between the groups with respect to donor age, histology during HCVrec, treated episodes of acute cellular rejection, or immunosuppression therapy. The results were validated in the remaining 22 OLT recipients with HCV using quantitative real‐time polymerase chain reaction. Fifty‐seven beadtypes showed significantly different expression (P < 0.001) between the groups during HCVrec. In G3, the gene expression of interleukin‐28RA (IL‐28RA), IL‐28, and angiotensin‐converting enzyme was up‐regulated. Samples from G1 and G3 were used to determine whether a multigenetic classifier could be derived to predict the group class. The final model included the intercept and 9 bead types. Pairwise scatter plots of these 9 bead types revealed that G1 and G3 were well separated with respect to each gene. Our analysis has demonstrated the utility of a set of molecular markers indicating HCVrec severity early after OLT. Liver Transpl 17:824‐835, 2011.

Regulation of molecular pathways in ischemia-reperfusion injury after liver transplantation.

Background Ischemia-reperfusion (I/R) injury is a multifactorial phenomenon that occurs during the transplant event and frequently compromises early graft function after liver transplantation (LT). Current comprehension of molecular mechanisms and regulation processes of I/R injury lacks clarity. MicroRNA (miRNA) regulation results critical in several biological processes. Methods This study evaluated gene expression and miRNA expression profiles using microarrays in 34 graft biopsies collected at preimplantation (L1) and at 90 min postreperfusion (L2) from consecutives deceased-donor LT recipients. miRNA profiles were first analyzed. Data integration analysis (gene expression/miRNA expression) aimed to identify potential target genes for each identified miRNA from the L1/L2 differential gene expression profile. Results Pairwise comparison analyses identified 40 miRNAs and 3168 significantly differentially expressed genes at postreperfusion time compared with preimplantation time. Pathway analysis of miRNAs associated these profiles with antiapoptosis, inhibition of cellular proliferation, and proinflammatory processes. Target analysis identified an miRNA-associated molecular profile of 2172 genes involved in cellular growth and proliferation modulation by cell cycle regulation, cell death and survival, and proinflammatory and anti-inflammatory processes. miRNA-independent genes involved proinflammatory molecules. Conclusion We identified a miRNA profile involved in posttranscriptional regulatory mechanisms in I/R injury post-LT. A better understanding of these molecular processes involved in I/R may contribute to develop new strategies to minimize graft injury.