Molecular regulation of acute kidney injury (miRNA)
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ABSTRACT: 18 zero-hour and 18 selected post-transplant (Tx) biopsy samples from 18 kidney allografts (8 acute kidney injury (AKI), 10 PBx - protocol biopsies - controls) were analyzed by using the Affymetrix GeneChipM-BM-. miRNA 3.0 Array. Comparison between control group (protocol biopsies) and indication biopsies with histological lesions of acute tubular necrosis without rejection (ATN).
Project description:18 zero-hour and 18 selected post-transplant (Tx) biopsy samples from 18 kidney allografts (8 acute kidney injury (AKI), 10 PBx - protocol biopsies - controls) were analyzed by using the Affymetrix GeneChip® Human Gene 2.0 ST Array. comparison between control group (protocol biopsies) and indication biopsies with histological lesions of acute tubular necrosis without rejection (ATN)
Project description:18 zero-hour and 18 selected post-transplant (Tx) biopsy samples from 18 kidney allografts (8 acute kidney injury (AKI), 10 PBx - protocol biopsies - controls) were analyzed by using the Affymetrix GeneChip® Human Gene 2.0 ST Array.
Project description:Microarray analysis of human kidneys with acute kidney injury (AKI) has been limited because such kidneys are seldom biopsied. However, all kidney transplants experience AKI, and early kidney transplants without rejection are an excellent model for human AKI: they are screened to exclude chronic kidney disease, frequently biopsied, and have extensive follow-up. We used histopathology and microarrays to compare indication biopsies from 28 transplants with AKI to 11 pristine protocol biopsies of stable transplants. Kidneys with AKI showed increased expression of 394 injury-repair response associated transcripts, including many known epithelial injury molecules (e.g. ITGB6, LCN2), tissue remodeling molecules (e.g. VCAN), and inflammation molecules (S100A8, ITGB3). Many other genes also predict the phenotype, depending on statistical filtering rules, including AKI biomarkers as HAVCR1 and IL18. Most mouse orthologs of the top injury-repair transcripts were increased in published mouse AKI models. Pathway analysis of the injury-repair transcripts revealed similarities to cancer, development, and cell movement. The injury-repair transcript score AKI kidneys correlated with reduced function, future recovery, brain death, and need for dialysis, but not future graft loss. In contrast, histologic features of "acute tubular injury" did not correlate with function or with the molecular changes. Thus the injury-repair associated transcripts represent a massive coordinate injury-repair response of kidney parenchyma to AKI, similar to mouse AKI models, and provide an objective measure for assessing the severity of AKI in kidney biopsies and validation for the use of many AKI biomarkers. AKI biopsies sample names and CEL files are from GSE21374. All consenting renal transplant patients undergoing biopsies for cause as standard of care between 09/2004 and 10/2007 at the university of Alberta or between 11/2006 and 02/2007 at the University of Illinois were included in the analysis. In addition to the cores required for standard histopathology, we collected one core for gene expression studies. the relationship between gene expression in the biopsy and subsequent graft loss was analyzed. This dataset is part of the TransQST collection.
Project description:Microarray analysis of human kidneys with acute kidney injury (AKI) has been limited because such kidneys are seldom biopsied. However, all kidney transplants experience AKI, and early kidney transplants without rejection are an excellent model for human AKI: they are screened to exclude chronic kidney disease, frequently biopsied, and have extensive follow-up. We used histopathology and microarrays to compare indication biopsies from 28 transplants with AKI to 11 pristine protocol biopsies of stable transplants. Kidneys with AKI showed increased expression of 394 injury-repair response associated transcripts, including many known epithelial injury molecules (e.g. ITGB6, LCN2), tissue remodeling molecules (e.g. VCAN), and inflammation molecules (S100A8, ITGB3). Many other genes also predict the phenotype, depending on statistical filtering rules, including AKI biomarkers as HAVCR1 and IL18. Most mouse orthologs of the top injury-repair transcripts were increased in published mouse AKI models. Pathway analysis of the injury-repair transcripts revealed similarities to cancer, development, and cell movement. The injury-repair transcript score AKI kidneys correlated with reduced function, future recovery, brain death, and need for dialysis, but not future graft loss. In contrast, histologic features of "acute tubular injury" did not correlate with function or with the molecular changes. Thus the injury-repair associated transcripts represent a massive coordinate injury-repair response of kidney parenchyma to AKI, similar to mouse AKI models, and provide an objective measure for assessing the severity of AKI in kidney biopsies and validation for the use of many AKI biomarkers.
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
Project description:Sepsis-induced acute kidney injury (AKI) is the most common form of AKI with poor outcomes. Renal proteomic analysis after bacterial lipopolysaccharide (LPS) administration revealed that the local renal acute phase reaction (APR) is one of the strongest responses of the kidney during septic AKI in mice. Evaluation of mRNA expression confirmed that most acute phase proteins were produced in the kidney. Our study also provides missing information on the time course of septic renal APR. Proteomic analysis of LPS-induced AKI demonstrated a marked upregulation of local renal acute phase response (APR) that commenced a few hours post injection and peaked at 24 h. Much more APPs were involved in the renal APR than previously identified.
Project description:Despite tubular injury being one of the main mechanisms driving acute kidney injury (AKI), clinicians still have a limited diagnostic repertoire to precisely monitor damage to tubular epithelial cells (TEC). In our previous work we used single cell sequencing to identify TEC subsets as main component of the urine signature in AKI. The aim of this study was to establish TEC as a clinical marker for tubular damage. In total 243 patients were analyzed. For sequencing, we collected eight urine samples of patients with AKI and glomerular disease. By aligning urinary single-cell transcriptomes and TEC-surface proteins using Cellular Indexing of Transcriptome and Epitope Sequencing (CITE-Seq), we developed a protocol for flow cytometric quantification of CD10/CD13+ proximal and CD227/CD326+ distal TEC in urine. The marker combinations were confirmed in kidney biopsies. We validated our approach across four cohorts totaling 235 patients, consisting of patients with AKI (n=63), SARS-CoV-2 infection (n=47), ANCA-associated vasculitis (AAV) with active disease and stable remission (n=110) and healthy controls (n=15). Our findings demonstrate that CD10/CD13 and CD227/CD326 adequately identify proximal and distal urinary TEC, respectively. Distal urinary TEC counts correlate with the severity of AKI based on KDIGO stage and acute eGFR loss in two separate cohorts and can successfully discriminate AKI from healthy controls as well as glomerular disease. We propose urinary CD227/CD326+ TEC counts as a specific, non-invasive marker for tubular injury in AKI. Our protocol provides the basis for a deeper phenotypic analysis of urinary TECs