E-GEOD-21374
Ontology highlight
ABSTRACT:
PROVIDER: E-GEOD-21374 | ExpressionAtlas | 2025-01-24
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-21374-analysis-methods.tsv | Tabular | |||
| E-GEOD-21374-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-21374-configuration.xml | Xml | |||
| E-GEOD-21374-percentile-ranks.tsv | Tabular | |||
| E-GEOD-21374.condensed-sdrf.tsv | Tabular |
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Project description:Expression data from rejection and non-rejection kidney transplant patients
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Project description:The Australian Chronic Allograft Dysfunction (AUSCAD) study is an ongoing single centre cohort study at Westmead hospital in Australia. In this section of the study, we aimed to identify biomarkers for allograft rejection in kidney transplant recipients, 3-months after their transplant. Our study recruited 123 patients, each having protocol renal allograft biopsies taken 3-months post transplantation.
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Project description:Expression of the IL-17/Th17 axis in the development of acute renal allograft rejection
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Project description:We investigated blood miRNAs as potential non-invasive biomarkers in kidney transplantation as part of the BIOMARGIN consortium (ClinicalTrials.gov, number NCT02832661). Blood samples were collected at time of the 717 renal allograft biopsies, in four European transplant centers. Profiling of mIR transcriptomes was performed in a multistage discovery-to-validation study. Antibody-mediated rejection (ABMR) is the most common cause of allograft failure after kidney transplantation. The revised Banff 2017 classification defines ABMR as conditions in which histologic evidence of acute and chronic injury is associated with evidence of current/recent antibody interaction with vascular endothelium and serologic evidence of donor-specific antibodies (DSA) to human leukocyte antigen (HLA) or non-HLA antigens
2021-05-31 | E-MTAB-9595 | biostudies-arrayexpress
Project description:CONTEXT Slowly progressive chronic tubulo-interstitial damage jeopardizes long-term renal allograft survival. Both immune and non-immune mechanisms are thought to contribute, but the most promising targets for timely intervention have not been identified. OBJECTIVE In the current study we seek to determine the driving force behind progressive histological damage of renal allografts, without the interference of donor pathology, delayed graft function and acute graft rejection. DESIGN We used microarrays to examine whole genome expression profiles in renal allograft protocol biopsies, and analyzed the correlation between gene expression and the histological appearance over time. The gene expression profiles in these protocol biopsies were then compared with gene expression of biopsies with acute T-cell mediated rejection. PATIENTS Human renal allograft biopsies (N=120) were included: 96 rejection-free protocol biopsies and 24 biopsies with T-cell mediated acute rejection. RESULTS In this highly cross-validated study, we demonstrate the significant association of established, ongoing and future chronic histological damage with regulation of adaptive immune gene expression (T-cell and B-cell transcript sets) and innate immune response gene expression (dendritic cell, NK-cell, mast cell and granulocyte transcripts). We demonstrate the ability of gene expression analysis to perform as a quantitative marker for ongoing inflammation with a wide dynamic range: from subtle subhistological inflammation prior to development of chronic damage, over moderate subclinical inflammation associated with chronic histological damage, to marked inflammation of Banff-grade acute T-cell mediated rejection. CONCLUSION Progressive chronic histological damage after kidney transplantation is associated with significant regulation of both innate and adaptive immune responses, months before the histological lesions appear. This study therefore corroborates the hypothesis that quantitative inflammation below the diagnostic threshold of classic T-cell or antibody-mediated rejection is associated with early subclinical stages of progressive renal allograft damage. We used microarrays to examine whole genome expression profiles in renal allograft protocol biopsies, and analyzed the correlation between gene expression and the histological appearance over time. The gene expression profiles in these protocol biopsies were then compared with gene expression of biopsies with acute T-cell mediated rejection. Human renal allograft biopsies (N=120) were included: 96 rejection-free protocol biopsies and 24 biopsies with T-cell mediated acute rejection.
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Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining “molecular Banff” signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set here comprises a small validation batch of renal allograft biopsies for clinical indications plus control normal kidney samples from patients at Hôpital Tenon, Paris (second batch) that complements the first batch of 60 samples. We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Keywords: disease state analysis 4 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to Banff'97 criteria and 2 normal kidney samples.
2009-02-24 | E-GEOD-9492 | biostudies-arrayexpress
Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining âmolecular Banffâ signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at Hôpital Tenon, Paris (February 2003 until September 2004) and few respective patients from Hôpital Bicêtre, Paris, Hôpital Pellegrin, Bordeaux, and Hôpital Dupuytren, Limoges, plus control normal kidney samples from Hôpital Tenon, Paris, France (first batch). We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Experiment Overall Design: 47 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to BANFF'97 criteria, and 13 normal kidney samples as controls.
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Project description:Expression data from uremic patients (end stage renal failure) and 20 healthy controls
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Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining M-bM-^@M-^\molecular BanffM-bM-^@M-^] signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at HM-CM-4pital Tenon, Paris (February 2003 until September 2004) and few respective patients from HM-CM-4pital BicM-CM-*tre, Paris, HM-CM-4pital Pellegrin, Bordeaux, and HM-CM-4pital Dupuytren, Limoges, plus control normal kidney samples from HM-CM-4pital Tenon, Paris, France (first batch). We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Keywords: disease state analysis Keywords: Expression profiling by array 16 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to BANFF'97 criteria (additional samples associated with GSE9489)
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