Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Comparing three phenotypes: Comparing molecular assessment of implantation biopsy

ABSTRACT: In deceased donor kidney transplantation, acute kidney injury (AKI) prioir to surgery is a major determinant of delayed graft function (DGF), but AKI is histologically silent and difficult to assess. We hypothesized that a molecular measurement of AKI would add power to conventional risk assessments to predict the early poor allograft function at first week post transplantation. We performed microarrays on implantation biopsies taken during reperfusion in 70 deceased donor kidneys from 53 donors. Early poor function was classified by two definitions on day 7 post-transplantation: serum creatinine greater than 265 umol/L (3 mg/dL) or the requirement for dialysis. Donor age and related risk scores (Irish, Schold, KDRI) associated with worse early function, as expected, but histologic features (glomerulosclerosis; pathology risk scores (Remuzzi, MAPI)) correlated with donor age but not with poor function. However, molecular AKI signal, previously defined in kidneys with early injury, was the best single predictor of poor allograft function. The combination of donor age and the AKI signal improved the prediction of poor function. In addition, asssessments of tissue quality particularly donor age, Banff ct, Irish and KDRI scores, showed negative correlative trend with late graft function, whereas the AKI signal did not. Thus donor age and the molecular AKI signal are the main predictors of early impaired function, but have little impact on survival.

ORGANISM(S): Homo sapiens

SUBMITTER: Jessica Chang

PROVIDER: E-GEOD-37838 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

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.

Dataset Information

Comparing three phenotypes: Comparing molecular assessment of implantation biopsy

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure