Transcription profiling of human blood from kidney transplant patients to identify biomarkers for early and late stage chronic allograft nephropathy by genomic profiling
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ABSTRACT: Despite significant improvements in life expectancy of kidney transplant patients due to advances in surgery and immunosuppression, Chronic Allograft Nephropathy (CAN) remains a daunting problem. A complex network of cellular mechanisms in both graft and peripheral immune compartments complicates the non-invasive diagnosis of CAN, which still requires biopsy histology. This is compounded by non-immunological factors contributing to graft injury. There is a pressing need to identify and validate minimally invasive biomarkers for CAN to serve as early predictors of graft loss and as metrics for managing long-term immunosuppression. This study attempts to identify sets of unique transcript biomarkers with high predictive accuracy for both mild and moderate/severe CAN. These biomarkers are the necessary first step to a genomic classification of CAN based on peripheral blood and the targets for a prospective, serial-monitoring clinical study. Experiment Overall Design: We used DNA microarrays and bioinformatics to identify candidate genomic markers of mild and moderate/severe CAN in peripheral blood of two distinct cohorts (n=42 and n=35, respectively) of kidney transplant patients with biopsy-documented histology.
Project description:Despite significant improvements in life expectancy of kidney transplant patients due to advances in surgery and immunosuppression, Chronic Allograft Nephropathy (CAN) remains a daunting problem. A complex network of cellular mechanisms in both graft and peripheral immune compartments complicates the non-invasive diagnosis of CAN, which still requires biopsy histology. This is compounded by non-immunological factors contributing to graft injury. There is a pressing need to identify and validate minimally invasive biomarkers for CAN to serve as early predictors of graft loss and as metrics for managing long-term immunosuppression. This study attempts to identify sets of unique transcript biomarkers with high predictive accuracy for both mild and moderate/severe CAN. These biomarkers are the necessary first step to a genomic classification of CAN based on peripheral blood and the targets for a prospective, serial-monitoring clinical study. Experiment Overall Design: We used DNA microarrays and bioinformatics to identify candidate genomic markers of mild and moderate/severe CAN in peripheral blood of two distinct cohorts (n=42 and n=35, respectively) of kidney transplant patients with biopsy-documented histology.
Project description:Despite significant improvements in life expectancy of kidney transplant patients due to advances in surgery and immunosuppression, Chronic Allograft Nephropathy (CAN) remains a daunting problem. A complex network of cellular mechanisms in both graft and peripheral immune compartments complicates the non-invasive diagnosis of CAN, which still requires biopsy histology. This is compounded by non-immunological factors contributing to graft injury. There is a pressing need to identify and validate minimally invasive biomarkers for CAN to serve as early predictors of graft loss and as metrics for managing long-term immunosuppression. This study attempts to identify sets of unique transcript biomarkers with high predictive accuracy for both mild and moderate/severe CAN. These biomarkers are the necessary first step to a genomic classification of CAN based on peripheral blood and the targets for a prospective, serial-monitoring clinical study.
Project description:Despite significant improvements in life expectancy of kidney transplant patients due to advances in surgery and immunosuppression, Chronic Allograft Nephropathy (CAN) remains a daunting problem. A complex network of cellular mechanisms in both graft and peripheral immune compartments complicates the non-invasive diagnosis of CAN, which still requires biopsy histology. This is compounded by non-immunological factors contributing to graft injury. There is a pressing need to identify and validate minimally invasive biomarkers for CAN to serve as early predictors of graft loss and as metrics for managing long-term immunosuppression.We used DNA microarrays, tandem mass spectroscopy proteomics and bioinformatics to identify genomic and proteomic markers of mild and moderate/severe CAN in peripheral blood of two distinct cohorts (n = 77 total) of kidney transplant patients with biopsy-documented histology.Gene expression profiles reveal over 2400 genes for mild CAN, and over 700 for moderate/severe CAN. A consensus analysis reveals 393 (mild) and 63 (moderate/severe) final candidates as CAN markers with predictive accuracy of 80% (mild) and 92% (moderate/severe). Proteomic profiles show over 500 candidates each, for both stages of CAN including 302 proteins unique to mild and 509 unique to moderate/severe CAN.This study identifies several unique signatures of transcript and protein biomarkers with high predictive accuracies for mild and moderate/severe CAN, the most common cause of late allograft failure. These biomarkers are the necessary first step to a proteogenomic classification of CAN based on peripheral blood profiling and will be the targets of a prospective clinical validation study.
Project description:Metabolic changes associated with diabetes are reported to lead to the onset of early-stage diabetic nephropathy (DN). Furthermore, lipotoxicity is implicated in renal dysfunction. Most studies of DN have focused on a single or limited number of lipids, and the lipidome of the kidney during early-stage DN remains to be elucidated. In the present study, we aimed to comprehensively identify lipid abnormalities during early-stage DN; to this end, we established an early-stage DN rat model by feeding a high-sucrose and high-fat diet combined with administration of low-dose streptozotocin. Using a high-coverage, targeted lipidomic approach, we established the lipid profile, comprising 437 lipid species and 25 lipid classes, of the kidney cortex in normal rats and the DN rat model. Our findings additionally confirmed that the DN rat model had been successfully established. We observed distinct lipidomic signatures in the DN kidney, with characteristic alterations in side chain composition and degree of unsaturation. Glyceride lipids, especially cholesteryl esters, showed a significant increase in the DN kidney cortex. The levels of most phospholipids exhibited a decline, except those of phospholipids with side chain of 36:1. Furthermore, the levels of lyso-phospholipids and sphingolipids, including ceramide and its derivatives, were dramatically elevated in the present DN rat model. Our findings, which provide a comprehensive lipidome of the kidney cortex in rats with DN, are expected to be useful for the identification of pathologically relevant lipid species in DN. Furthermore, the results represent novel insights into the mechanistic basis of DN.
Project description:Renal transplantation is the preferred treatment of end stage renal disease, but allograft survival is limited by development of interstitial fibrosis and tubular atrophy in response to various stimuli. Much effort has been put into identifying new protein markers of fibrosis to support the diagnosis. In present work, we performed an in-depth quantitative proteomics analysis of allograft biopsies from 31 prevalent renal transplant patients and identified correlated the quantified proteins with the volume fraction of fibrosis as determined by a morphometric method. Linear regression analysis identified four proteins that were highly associated with the degree of interstitial fibrosis, namely Coagulation Factor XIII A chain (estimate 18.7, adjusted p<0.03), Uridine Phosphorylase 1 (estimate 19.4, adjusted p<0.001), Actin-related protein 2/3 subunit 2 (estimate 34.2, adjusted p<0.05) and Cytochrome C Oxidase Assembly Factor 6 homolog (estimate -44.9, adjusted p<0.002) even after multiple testing. Proteins that were negatively associated with fibrosis (p < 0.005) were primarily related to normal metabolic processes and respiration, whereas proteins that were positively associated with fibrosis (p < 0.005) were involved in catabolic processes, cytoskeleton organization and immune response. The identified proteins may be candidates for further validation with regards to renal fibrosis. The results support the notion that cytoskeleton organization and immune responses are prevalent processes in renal allograft fibrosis.
Project description:Renal transplantation is the preferred treatment of end stage renal disease, but allograft survival is limited by the development of interstitial fibrosis and tubular atrophy in response to various stimuli. Much effort has been put into identifying new protein markers of fibrosis to support the diagnosis. In the present work, we performed an in-depth quantitative proteomics analysis of allograft biopsies from 31 prevalent renal transplant patients and correlated the quantified proteins with the volume fraction of fibrosis as determined by a morphometric method. Linear regression analysis identified four proteins that were highly associated with the degree of interstitial fibrosis, namely Coagulation Factor XIII A chain (estimate 18.7, adjusted p < 0.03), Uridine Phosphorylase 1 (estimate 19.4, adjusted p < 0.001), Actin-related protein 2/3 subunit 2 (estimate 34.2, adjusted p < 0.05) and Cytochrome C Oxidase Assembly Factor 6 homolog (estimate -44.9, adjusted p < 0.002), even after multiple testing. Proteins that were negatively associated with fibrosis (p < 0.005) were primarily related to normal metabolic processes and respiration, whereas proteins that were positively associated with fibrosis (p < 0.005) were involved in catabolic processes, cytoskeleton organization and the immune response. The identified proteins may be candidates for further validation with regards to renal fibrosis. The results support the notion that cytoskeleton organization and immune responses are prevalent processes in renal allograft fibrosis.
Project description:The current Banff scoring system was not developed to predict graft loss and may not be ideal for use in clinical trials aimed at improving allograft survival. We hypothesized that scoring histologic features of digitized renal allograft biopsies using a continuous, more objective, computer-assisted morphometric (CAM) system might be more predictive of graft loss. We performed a nested case-control study in kidney transplant recipients with a surveillance biopsy obtained 5 years after transplantation. Patients that developed death-censored graft loss (n = 67) were 2:1 matched on age, gender, and follow-up time to controls with surviving grafts (n = 134). The risk of graft loss was compared between CAM-based models vs a model based on Banff scores. Both Banff and CAM identified chronic lesions associated with graft loss (chronic glomerulopathy, arteriolar hyalinosis, and mesangial expansion). However, the CAM-based models predicted graft loss better than the Banff-based model, both overall (c-statistic 0.754 vs 0.705, P < .001), and in biopsies without chronic glomerulopathy (c-statistic 0.738 vs 0.661, P < .001) where it identified more features predictive of graft loss (% luminal stenosis and % mesangial expansion). Using 5-year renal allograft surveillance biopsies, CAM-based models predict graft loss better than Banff models and might be developed into biomarkers for future clinical trials.
Project description:Being able to identify patients in whom immunological tolerance has been established or is developing would allow an individually tailored approach to post-transplant management of kidney allograft recipients. Ex vivo immunological monitoring was performed on samples from five groups of European renal transplant recipients (“IOT samples”): ten drug-free tolerant recipients who were functionally stable despite remaining immunosuppression-free for more than one year (Tol-DF); also functionally stable patients on minimal immunosuppression (<10 mg/day prednisone, s-LP); stable patients maintained with calcineurin inhibitors (s-CNI); stable patients maintained on CNI-free immunosuppression regimen (s-nCNI); patients showing signs of chronic rejection (CR) and healthy controls (HC). Among the investigation of other biomarkers and bioassays, gene expression profiles were generated on custom Agilent 8x15K 60mer oligonucleotide microarrays (“RISET 2.0”) on the IOT cohort (training set) and on an independent cohort of patients from the ITN (USA) that contained similar groups of patients and included 23 tolerant recipients (“ITN samples”, test set). Set of genes were identified, whose expression on whole blood allowed the identification of 100% of the tolerant recipients in the training set and 84% in the test set. Keywords: classification of clinical samples, tolerance prediction
Project description:Being able to identify patients in whom immunological tolerance has been established or is developing would allow an individually tailored approach to post-transplant management of kidney allograft recipients. Ex vivo immunological monitoring was performed on samples from five groups of European renal transplant recipients (“IOT samples”): ten drug-free tolerant recipients who were functionally stable despite remaining immunosuppression-free for more than one year (Tol-DF); also functionally stable patients on minimal immunosuppression (<10 mg/day prednisone, s-LP); stable patients maintained with calcineurin inhibitors (s-CNI); stable patients maintained on CNI-free immunosuppression regimen (s-nCNI); patients showing signs of chronic rejection (CR) and healthy controls (HC). Among the investigation of other biomarkers and bioassays, gene expression profiles were generated on custom Agilent 8x15K 60mer oligonucleotide microarrays (“RISET 2.0”) on the IOT cohort (training set) and on an independent cohort of patients from the ITN (USA) that contained similar groups of patients and included 23 tolerant recipients (“ITN samples”, test set). Set of genes were identified, whose expression on whole blood allowed the identification of 100% of the tolerant recipients in the training set and 84% in the test set. Keywords: classification of clinical samples, tolerance prediction IOT samples: 13 samples from 10 Tol-DF patients, 16 samples from 11 s-LP patients, 8 samples from 8 s-nCNI patients, 40 samples from 28 s-CNI patients, 10 samples from 9 CR patients, and 8 samples from 8 HC donors were analysed on a custom Agilent 8x15K 60mer oligonucleotide microarray encomprising 5069 probes in triplicates. The microarray is dedicated to transplantation research and was designed based on current literature and published and unpublished data provided by the RISET consortium. For the probe selection procedure we specially focused on the detection of multiple transcript variants of a gene, on optimized hybridization properties of the probes, and on the avoidance of crosshybridization. The sampling dates of replicate samples from the same patient range from one day to 1.5 years. ITN samples: 31 samples from 23 Tol-DF patients, 14 samples from 11 s-LP patients, 52 samples from 34 s-CNI patients, 25 samples from 18 CR patients, and 20 samples from 20 HC donors were analysed on the same microarray platform and served as test set. The samples of the two cohorts differ in the protocol of RNA preparation.
Project description:Pregnancy in kidney transplantation (KT) recipients has been challenging because of the high risk of maternal, fetal, and renal complications. Although patients with immunoglobulin A nephropathy (IgAN)-chronic kidney disease (CKD) are at a high risk for hypertension in pregnancy (HIP), the maternal risk in KT recipients with IgAN as the etiology remains unclear. We retrospectively reviewed the medical records of pregnant KT recipients who delivered at our hospital. The incidence of maternal and fetal complications and the impact on kidney allografts between the group with IgAN as the primary kidney disease and the group with other primary diseases were compared. The analysis included 73 pregnancies in 64 KT recipients. The IgAN group had a higher incidence of HIP than the non-IgAN group (69% vs. 40%, p = 0.02). IgAN as primary kidney disease and interval from transplantation to conception were associated with HIP (OR 3.33 [1.11-9.92], p = 0.03, OR 0.83 [0.72-0.96], p < 0.01, respectively). The 20-year graft survival or prevention of CKD stage 5 in group with IgAN was lower than that in the group with other primary disease (p < 0.01). KT recipients should be informed of the risk of HIP and possibility of long-term worsening of postpartum renal function.