E-GEOD-1563
Ontology highlight
ABSTRACT:
TISSUE(S): Kidney, Blood
DISEASE(S): Renal Dysfunction Without Rejection,Renal Dysfunction,Normal,Acute Transplant Rejection
PROVIDER: E-GEOD-1563 | ExpressionAtlas | 2020-11-17
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-1563-analysis-methods.tsv | Tabular | |||
| E-GEOD-1563-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-1563-configuration.xml | Xml | |||
| E-GEOD-1563-percentile-ranks.tsv | Tabular | |||
| E-GEOD-1563.condensed-sdrf.tsv | Tabular |
Items per page: 5 1 - 5 of 45 |
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Project description:Kidney Transplant Rejection and Tissue Injury by Gene Profiling of Biopsies and Peripheral Blood Lymphocytes
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Project description:We used DNA microarrays (HG-U95Av2 GeneChips) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients. Sample classes include kidney biopsies and PBLs from patients with 1) healthy normal donor kidneys, 2) well-functioning transplants with no clinical evidence of rejection, 3) kidneys undergoing acute rejection, and 4) transplants with renal dysfunction without rejection. Nomenclature for samples is as follows: 1) all sample names include either BX or PBL to indicate that they were derived from biopsies or PBLs respectively, 2) C indicates samples from healthy normal donors, 3) TX indicates samples from patients with well-functioning transplants with no clinical evidence of rejection, 3) AR indicates samples from transplant patients with kidneys undergoing acute rejection, 4) NR indicates samples from transplant patients with renal dysfunction without rejection. Abbreviations used to describe patient samples include the following: BX - Biopsy; PBL- Peripheral Blood Lymphocytes; CsA -Cyclosporine; MMF - Mycophenolate Mofetil; P - Prednisone; FK - Tacrolimus; SRL - Sirolimus; CAD -Cadaveric; LD - Live Donor; Scr - Serum Creatinine; ATN - Acute Tubular Necrosis CNI - Calcineurin Inhibitor; FSGS - Focal Segmental Glomerulosclerosis several array data sets did not pass quality control and were not analyzed. These include AR1PBL, NR4BX, and NR6PBL Keywords = DNA microarrays, gene expression, kidney, rejection, transplant Keywords: other. This dataset is part of the TransQST collection.
2004-07-14 | E-GEOD-1563 | biostudies-arrayexpress
Project description:We used DNA microarrays (HG-U95Av2 GeneChips) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients. Sample classes include kidney biopsies and PBLs from patients with 1) healthy normal donor kidneys, 2) well-functioning transplants with no clinical evidence of rejection, 3) kidneys undergoing acute rejection, and 4) transplants with renal dysfunction without rejection. Nomenclature for samples is as follows: 1) all sample names include either BX or PBL to indicate that they were derived from biopsies or PBLs respectively, 2) C indicates samples from healthy normal donors, 3) TX indicates samples from patients with well-functioning transplants with no clinical evidence of rejection, 3) AR indicates samples from transplant patients with kidneys undergoing acute rejection, 4) NR indicates samples from transplant patients with renal dysfunction without rejection. Abbreviations used to describe patient samples include the following: BX - Biopsy; PBL- Peripheral Blood Lymphocytes; CsA -Cyclosporine; MMF - Mycophenolate Mofetil; P - Prednisone; FK - Tacrolimus; SRL - Sirolimus; CAD -Cadaveric; LD - Live Donor; Scr - Serum Creatinine; ATN - Acute Tubular Necrosis CNI - Calcineurin Inhibitor; FSGS - Focal Segmental Glomerulosclerosis several array data sets did not pass quality control and were not analyzed. These include AR1PBL, NR4BX, and NR6PBL Keywords = DNA microarrays, gene expression, kidney, rejection, transplant Keywords: other
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Project description:Kidney transplantation is the treatment of choice for patients with end-stage chronic kidney disease (ESKD). Despite the usefulness of transplantation as replacement therapy, long-term graft survival represents a major challenge for transplant immunology. Although nowadays there has been an advance in understanding immunological mechanisms mediating rejection, and the improvement of immunomodulation therapies, there are still underlying molecular processes marking an important variability among patients, and presumably influencing allograft rejection. With our analysis we explored differences in gene expression by Next Generation Sequencing implementing RNA-Seq in biopsies, blood and urine from kidney transplant patients with acute and chronic rejection. For this, we performed an intra-outcome analysis simultaneously in acute and chronic rejection, with which we sought: 1. To identify differences in gene expression between peripheral blood vs renal tissue and peripheral blood vs urine in acute rejection and chronic rejection; 2. To identify the level of agreement in gene expression between renal tissue and urine in acute rejection and chronic rejection and 3. To identify genes and biological processes associated with acute rejection and chronic rejection that could be potentially detected in blood, and simultaneously in urine and biopsy in acute rejection and in chronic rejection.
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Project description:Microarrays were used to analyze the gene expression in peripheral blood and kidney allograft biopsies from patients with a kidney transplantation to get more insight in the molecular mechanisms underlying the different clinical phenotypes of kidney transplant rejection.
2019-08-15 | GSE129166 | GEO
Project description:Microarrays were used to analyze the gene expression in peripheral blood and kidney allograft biopsies from patients with a kidney transplantation to get more insight in the molecular mechanisms underlying the different clinical phenotypes of kidney transplant rejection. 117 peripheral blood samples and 95 kidney allograft biopsies were used for genome-wide gene expression analysis. The updated Banff 2017 classification was used for diagnosis of the samples. Total RNA extracted from blood and biopsies was used to analyze mRNA expression via Affymetrix Human U133 Plus 2.0 arrays. This dataset is part of the TransQST collection.
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Project description:Molecular diagnosis of rejection is emerging in kidney, heart, and lung transplant biopsies and could offer insights for liver transplant biopsies. Groups differed in median time post-transplant e.g. R3injury 99 days vs. R4late 3117 days. R2TCMR biopsies expressed typical TCMR-related transcripts e.g. intense IFNG-induced effects. R3injury displayed increased expression of parenchymal injury transcripts (e.g. hypoxia-inducible factor EGLN1). R4late biopsies showed immunoglobulin transcripts and injury-related transcripts. R2TCMR correlated with histologic rejection although with many discrepancies, and R4late with fibrosis. R2TCMR, R3injury, and R4late correlated with liver function abnormalities. Supervised classifiers trained on histologic rejection showed less agreement with histology than unsupervised R2TCMR scores. No confirmed cases of clinical ABMR were present in the population, and strategies that previously revealed antibody-mediated rejection (ABMR) in kidney and heart transplants failed to reveal a liver ABMR phenotype. In conclusion, molecular analysis of liver transplant biopsies detects rejection, has the potential to resolve ambiguities, and could assist with immunosuppressive management.
2020-05-06 | GSE145780 | GEO
Project description:In the present work, we have used whole genome expression profiling of peripheral blood samples from 51 patients with biopsy-proven acute kidney transplant rejection and 24 patients with excellent function and biopsy-proven normal transplant histology. The results demonstrate that there are 1738 probesets on the Affymetrix HG-U133 Plus 2.0 GeneChip representing 1472 unique genes which are differentially expressed in the peripheral blood during an acute kidney transplant rejection. By ranking these results we have identified minimal sets of 50 to 150 probesets with predictive classification accuracies for AR of greater than 90% established with several different prediction tools including DLDA and PAM. We have demonstrated that a subset of peripheral blood gene expression signatures can also diagnose four different subtypes of AR (Banff Borderline, IA, IB and IIA) and the top 100 ranked classifiers have greater than 89% predictive accuracy. Finally, we have demonstrated that there are gene signatures for early and late AR defined as less than or greater than one year post-transplant with greater than 86% predictive accuracies. We also confirmed that there are 439 time-independent gene classifiers for AR. Based on these results, we conclude that peripheral blood gene expression profiling can be used to diagnose AR at any time in the first 5 years post-transplant in the setting of acute kidney transplant dysfunction not caused by BK nephropathy, other infections, drug-induced nephrotoxicity or ureteral obstruction. Keywords: kidney transplantation, peripheral blood, DNA microarrays, acute kidney rejection, biomarkers Microarray profiles of peripheral blood from 51 biopsy-proven acute kidney rejection (AR) and 24 well-functioning kidney transplants were randomized and compared using class comparisons, network and biological function analyses.
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Project description:Kidney transplant injury processes are associated with molecular changes in renal tissue, primarily related to immune cell activation and infiltration. How these processes are reflected by molecular alterations in circulating immune cells is poorly understood. We performed RNA-sequencing on 384 biobanked blood samples from four transplant centers, taken at time of a kidney allograft biopsy, selected for their phenotype (acute T cell- and antibody-mediated rejection, polyomavirus-associated nephropathy, and control). We performed differential expression analysis and pathway analysis per phenotype. In peripheral blood, differentially expressed genes in rejection vs. no rejection samples demonstrated upregulation of glucocorticoid receptor and NOD-like receptor signaling pathways. Pathways enriched in antibody-mediated rejection were strongly immune-specific, whereas pathways enriched in T cell-mediated rejection were less immune related. Differentially expressed genes in polyoma viremia and polyomavirus-associated nephropathy were similar and demonstrated upregulation of mitochondrial dysfunction and interferon signaling pathways. Our results highlight the immune activation pathways in peripheral blood leukocytes at time of antibody-mediated rejection and polyomavirus nephropathy and provide a framework for future therapeutic interventions.
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