E-GEOD-46474
Ontology highlight
ABSTRACT:
PROVIDER: E-GEOD-46474 | ExpressionAtlas | 2020-09-03
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-46474-analysis-methods.tsv | Tabular | |||
| E-GEOD-46474-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-46474-configuration.xml | Xml | |||
| E-GEOD-46474-percentile-ranks.tsv | Tabular | |||
| E-GEOD-46474.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:Gene expression data was analyzed to map with urine proteomics data gene expression data from kidney biopsies from kidney transplant patients with and without acute rejection, chronic allograft nephropathy and BK virus nephritis was used to study gene expression changes during acute rejection, chronic allograft nephropathy and bk virus nephropathy. Samples labeled STA16, STA22, STA14, and STA18 were included in the CAN vs no-CAN analysis as no-CAN samples as they also qualified as non-CAN samples.
2017-08-22 | GSE75693 | GEO
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
2004-07-14 | GSE1563 | GEO
Project description:Short-term kidney transplant rejection rates have vastly improved. Unfortunately, the focus is still on clinical acute rejection, whereas patients with no graft dysfunction and subclinical rejection without protocol biopsies would be treated as having no ongoing injury. Molecular diagnostic tests to detect rejection are still reliant on the current gold standard, kidney histology. Our work is the first to examine molecular profiles in matched tissue and blood samples from a prevalent kidney transplant recipient population. We show molecular evidence, in blood and tissue, that subclinical rejection is a precursor of clinical rejection and that non-alloimmune injury to the graft can be distinguished from immune activation. Our work supports consideration of tissue molecular profiling for a comprehensive understanding of noninvasive diagnostics.
2025-12-01 | GSE249451 | 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.
2014-03-01 | E-GEOD-15296 | biostudies-arrayexpress
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.
2023-12-31 | GSE242302 | GEO
Project description:Kidney transplantation offers the best survival and quality of life for patients’ with end-stage kidney disease. The major barrier to successful long-term transplantation is the host’s immune response to alloantigens’ causing rejection of the transplant. The complexity of this immune response in kidney transplantation is still not fully understood and effective treatment strategies are needed. To better understand rejection at the molecular and cellular level we characterized 4,487 cells from a single biopsy core from a kidney transplant undergoing mixed rejection using single cell RNA sequencing.
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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.
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Project description:The authors report that in INTERCOM, a prospective international study of 300 kidney transplant biopsies, a microarray-based molecular score for T cell-mediated rejection changed the assessment of 26% of all biopsies, illustrating the potential of precision diagnostics to impact practice. Microarray analysis of 300 kidney transplant biopsies (non-TCMR, TCMR) and 6 nephrectomies.
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