Project description:The study comprises various components: Samples TD: We aims to screen out different gene expression profile in donor biopsies after revascularization , We aims to predict renal allograft dysfunction early after transplantation. Samples AR, ATN, Tx: We aim to screen out different gene expression profile in acute rejection on the kidney. We aim to screen out different gene expression profile in acute tubular necrosis on the kidney. Results from the various study components can help to diagnose renal allograft dysfunction with different causes by distinct gene expression profile. Keywords: acute rejection, acute tubular necrosis, donor biopsies, renal allograft dysfunction Samples AR1-AR17: This study has been accomplished with 17 patients of acute rejection on the kidney.Technical replicates: 2 replicates Samples ATN1-ATN5: This study has been accomplished with 5 patients of acute tubular necrosis on the kidney. Technical replicates: 2 replicates Samples Tx1-Tx14: This study has been accomplished with 14 patients of stable renal function on the kidney.Tecnical replicates:2 replicates(except Tx12) Samples TD1-TD12: This study has been accomplished with 12 patients of donor tissue with stable function early after transplantation on the kidney.Technical replicates: 2 replicates Samples TD13-TD21: This study has been accomplished with 9 patients of donor tissue with renal dysfunction early after transplantation on the kidney.Technical replicates: 2 replicates
Project description:Shear-wave elastography (SWE) showed the absence or presence of significant differences among stable kidney allograft function and allograft dysfunction. We evaluated the variability of kidney allograft stiffness in relation to allograft dysfunction, respectively, in terms of a correlation of stiffness with patients' characteristics. A single-center prospective study on patients who had undergone renal transplantation was conducted between October 2017 and November 2018. Patients were clinically classified as having a stable allograft function or allograft dysfunction. SWE examinations performed by the same radiologist with a LOGIQ E9 were evaluated. Ten measurements were done for Young's modulus (kPa) at the level of allograft cortex and another ten at the level of medulla. Eighty-three SWE examinations from 63 patients, 69 stable allografts, and 14 allografts with dysfunction were included in the analysis. The intra-examinations stiffness showed high variability, with the quantile covariation coefficient ranging from 2.21% to 45.04%. The inter-examinations stiffness showed heterogeneity (from 28.66% to 42.38%). The kidney allograft cortex stiffness showed significantly higher values in cases with dysfunction (median = 28.70 kPa, interquartile range (IQR) = (25.68-31.98) kPa) as compared to those with stable function (median = 20.99 kPa, interquartile range = (16.08-27.68) kPa; p-value = 0.0142). Allograft tissue stiffness (both cortex and medulla) was significantly negatively correlated with body mass index (-0.44, p-value < 0.0001 for allograft cortex and -0.42, p-value = 0.0001 for allograft medulla), and positively correlated with Proteinuria/Creatinuria ratio (0.33, p-value = 0.0021 for allograft cortex and 0.28, p-value = 0.0105 for allograft medulla) but remained statistically significant only in cases with stable function. The cortical tissue stiffness proved significantly higher values for patients with allograft dysfunction as compared to patients with stable function, but to evolve as an additional tool for the evaluation of patients with a kidney transplant and to change the clinical practice, more extensive studies are needed.
Project description:The study comprises various components: Samples TD: We aims to screen out different gene expression profile in donor biopsies after revascularization , We aims to predict renal allograft dysfunction early after transplantation. Samples AR, ATN, Tx: We aim to screen out different gene expression profile in acute rejection on the kidney. We aim to screen out different gene expression profile in acute tubular necrosis on the kidney. Results from the various study components can help to diagnose renal allograft dysfunction with different causes by distinct gene expression profile. Keywords: acute rejection, acute tubular necrosis, donor biopsies, renal allograft dysfunction Overall design: Samples AR1-AR17: This study has been accomplished with 17 patients of acute rejection on the kidney.Technical replicates: 2 replicates Samples ATN1-ATN5: This study has been accomplished with 5 patients of acute tubular necrosis on the kidney. Technical replicates: 2 replicates Samples Tx1-Tx14: This study has been accomplished with 14 patients of stable renal function on the kidney.Tecnical replicates:2 replicates(except Tx12) Samples TD1-TD12: This study has been accomplished with 12 patients of donor tissue with stable function early after transplantation on the kidney.Technical replicates: 2 replicates Samples TD13-TD21: This study has been accomplished with 9 patients of donor tissue with renal dysfunction early after transplantation on the kidney.Technical replicates: 2 replicates
Project description:Acute rejection (AR) in renal transplantation is an established risk factor for reduced allograft survival. Molecules with regulatory control among immune pathways of AR that are inadequately suppressed, despite standard-of-care immunosuppression, could serve as important targets for therapeutic manipulation to prevent rejection. Here, an integrative, network-based computational strategy incorporating gene expression and genotype data of human renal allograft biopsy tissue was applied, to identify the master regulators - the key driver genes (KDGs) - within dysregulated AR pathways. A 982-meta-gene signature with differential expression in AR versus non-AR was identified from a meta-analysis of microarray data from 735 human kidney allograft biopsy samples across 7 data sets. Fourteen KDGs were derived from this signature. Interrogation of 2 publicly available databases identified compounds with predicted efficacy against individual KDGs or a key driver-based gene set, respectively, which could be repurposed for AR prevention. Minocycline, a tetracycline antibiotic, was chosen for experimental validation in a murine cardiac allograft model of AR. Minocycline attenuated the inflammatory profile of AR compared with controls and when coadministered with immunosuppression prolonged graft survival. This study demonstrates that a network-based strategy, using expression and genotype data to predict KDGs, assists target prioritization for therapeutics in renal allograft rejection.
Project description:Chronic injury in kidney transplants remains a major cause of allograft loss. The aim of this study was to identify a gene set capable of predicting renal allografts at risk of progressive injury due to fibrosis.This Genomics of Chronic Allograft Rejection (GoCAR) study is a prospective, multicentre study. We prospectively collected biopsies from renal allograft recipients (n=204) with stable renal function 3 months after transplantation. We used microarray analysis to investigate gene expression in 159 of these tissue samples. We aimed to identify genes that correlated with the Chronic Allograft Damage Index (CADI) score at 12 months, but not fibrosis at the time of the biopsy. We applied a penalised regression model in combination with permutation-based approach to derive an optimal gene set to predict allograft fibrosis. The GoCAR study is registered with ClinicalTrials.gov, number NCT00611702.We identified a set of 13 genes that was independently predictive for the development of fibrosis at 1 year (ie, CADI-12 ?2). The gene set had high predictive capacity (area under the curve [AUC] 0·967), which was superior to that of baseline clinical variables (AUC 0·706) and clinical and pathological variables (AUC 0·806). Furthermore routine pathological variables were unable to identify which histologically normal allografts would progress to fibrosis (AUC 0·754), whereas the predictive gene set accurately discriminated between transplants at high and low risk of progression (AUC 0·916). The 13 genes also accurately predicted early allograft loss (AUC 0·842 at 2 years and 0·844 at 3 years). We validated the predictive value of this gene set in an independent cohort from the GoCAR study (n=45, AUC 0·866) and two independent, publically available expression datasets (n=282, AUC 0·831 and n=24, AUC 0·972).Our results suggest that this set of 13 genes could be used to identify kidney transplant recipients at risk of allograft loss before the development of irreversible damage, thus allowing therapy to be modified to prevent progression to fibrosis.National Institutes of Health.
Project description:Accurate and effective biomarkers for continuous monitoring of graft function are needed after kidney transplantation. The aim of this study was to establish a circulating exosomal miRNA panel as non-invasive biomarker for kidney transplant recipients. Plasma exosomes of 58 kidney transplant recipients and 27 healthy controls were extracted by gel exclusion chromatography and characterized by transmission electron microscopy, nanoparticle tracking analysis and Western blotting. Post-transplant renal graft function was evaluated by estimated glomerular filtration rate (eGFR). Quantitative real-time polymerase chain reaction was used to determine the expression of exosomal microRNAs (miRNAs). Exosomal miR-21, miR-210 and miR-4639 showed negative correlations with eGFR in the training set and were selected for further analysis. In the validation set, miR-21, miR-210 and miR-4639 showed the capability to discriminate between subjects with chronic allograft dysfunction (eGFR < 60 mL/min/1.73 m2 ) and those with normal graft function (eGFR > 90 mL/min/1.73 m2 ). Three-miRNA panel exhibited higher accuracy compared with individual miRNAs or double indicators. One-year follow-up revealed a stable recovery of allograft function in subjects with low calculated score from three-miRNA panel (below the optimal cut-off value). In conclusion, a unique circulating exosomal miRNA panel was identified as an effective biomarker for monitoring post-transplant renal graft function in this study.
Project description:Alteration of certain metabolites may play a role in the pathophysiology of renal allograft disease.To explore metabolomic abnormalities in individuals with a failing kidney allograft, we analyzed by liquid chromatography-mass spectrometry (LC-MS/MS; for ex vivo profiling of serum and urine) and two dimensional correlated spectroscopy (2D COSY; for in vivo study of the kidney graft) 40 subjects with varying degrees of chronic allograft dysfunction stratified by tertiles of glomerular filtration rate (GFR; T1, T2, T3). Ten healthy non-allograft individuals were chosen as controls.LC-MS/MS analysis revealed a dose-response association between GFR and serum concentration of tryptophan, glutamine, dimethylarginine isomers (asymmetric [A]DMA and symmetric [S]DMA) and short-chain acylcarnitines (C4 and C12), (test for trend: T1-T3 = p<0.05; p = 0.01; p<0.001; p = 0.01; p = 0.01; p<0.05, respectively). The same association was found between GFR and urinary levels of histidine, DOPA, dopamine, carnosine, SDMA and ADMA (test for trend: T1-T3 = p<0.05; p<0.01; p = 0.001; p<0.05; p = 0.001; p<0.001; p<0.01, respectively). In vivo 2D COSY of the kidney allograft revealed significant reduction in the parenchymal content of choline, creatine, taurine and threonine (all: p<0.05) in individuals with lower GFR levels.We report an association between renal function and altered metabolomic profile in renal transplant individuals with different degrees of kidney graft function.
Project description:Tubulointerstitial fibrosis (fibrosis), a histologic feature associated with a failing kidney allograft, is diagnosed using the invasive allograft biopsy. A noninvasive diagnostic test for fibrosis may help improve allograft outcome.We obtained 114 urine specimens from 114 renal allograft recipients: 48 from 48 recipients with fibrosis in their biopsy results and 66 from 66 recipients with normal biopsy results. Levels of messenger RNAs (mRNAs) in urinary cells were measured using kinetic, quantitative polymerase chain reaction assays, and the levels were related to allograft diagnosis. A discovery set of 76 recipients (32 with allograft fibrosis and 44 with normal biopsy results) was used to develop a diagnostic signature, and an independent validation set of 38 recipients (16 with allograft fibrosis and 22 with normal biopsy results) was used to validate the signature.In the discovery set, urinary cell levels of the following mRNAs were significantly associated with the presence of allograft fibrosis: vimentin (P<0.0001, logistic regression model), hepatocyte growth factor (P<0.0001), ?-smooth muscle actin (P<0.0001), fibronectin 1 (P<0.0001), perforin (P=0.0002), plasminogen activator inhibitor 1 (P=0.0002), transforming growth factor ?1 (P=0.0004), tissue inhibitor of metalloproteinase 1 (P=0.0009), granzyme B (P=0.0009), fibroblast-specific protein 1 (P=0.006), CD103 (P=0.02), and collagen 1A1 (P=0.04). A four-gene model composed of the levels of mRNA for vimentin, NKCC2, and E-cadherin and of 18S ribosomal RNA provided the most accurate, parsimonious diagnostic model of allograft fibrosis with a sensitivity of 93.8% and a specificity of 84.1% (P<0.0001). In the independent validation set, this same model predicted the presence of allograft fibrosis with a sensitivity of 77.3% and a specificity of 87.5% (P<0.0001).Measurement of mRNAs in urinary cells may offer a noninvasive means of diagnosing fibrosis in human renal allografts.
Project description:Chronic renal allograft dysfunction (CAD) is a major limiting factor of long-term graft survival. The hallmarks of progressive CAD are interstitial fibrosis and tubular atrophy (IFTA). MicroRNAs are small, regulatory RNAs involved in many immunological processes. In particular, microRNA-21-5p (miR-21) is considered to be strongly associated with pathogenesis regarding tubulointerstitium. The aim of this study was to assess urinary miR-21 expression levels in the kidney transplant recipients and determine their application in the evaluation of IFTA and kidney allograft function. The expression levels of miR-21 were quantified in the urine of 31 kidney transplant recipients with biopsy-assessed IFTA (IFTA 0 + I: n = 17; IFTA II + III: n = 14) by real-time quantitative PCR. Urine samples were collected at the time of protocolar biopsies performed 1 or 2 years after kidney transplantation. MicroRNA-191-5p was used as reference gene. MiR-21 was significantly up-regulated in IFTA II + III group compared to IFTA 0 + I group (p = 0.003). MiR-21 correlated significantly with serum concentration of creatinine (r = 0.52, p = 0.003) and eGFR (r = -0.45; p = 0.01). ROC analysis determined the diagnostic value of miR-21 with an area under curve (AUC) of 0.80 (p = 0.0002), sensitivity of 0.86 and specificity of 0.71. miR-21 is associated with renal allograft dysfunction and IFTA. Therefore, it could be considered as a potential diagnostic, non-invasive biomarker for monitoring renal graft function.