Kidney transplantation (Agilent set)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE14356 | GEO | 2012/12/26
SECONDARY ACCESSION(S): PRJNA114469
REPOSITORIES: GEO
Similar Datasets
Project description:In this study, we examined transcriptional profiles from 3 different microarray platforms, across 103 peripheral blood samples with and without acute rejection, to find a critical gene-set for the diagnosis of acute renal rejection that matched biopsy diagnosis, irrespective of patient demographics, clinical confounders, concomitant infection, immunosuppression usage or sample processing methods. We hypothesized that changes in peripheral blood expression profiles correlate with biopsy-proven rejection, and that these changes could be used as biomarkers for the diagnosis and prediction of acute rejection. Disease State: Acute Rejection (AR#sampleid) or Stable (S#sampleid) samples
2012-12-26 | GSE14357 | GEO
Project description:In this study, we examined transcriptional profiles from 3 different microarray platforms, across 103 peripheral blood samples with and without acute rejection, to find a critical gene-set for the diagnosis of acute renal rejection that matched biopsy diagnosis, irrespective of patient demographics, clinical confounders, concomitant infection, immunosuppression usage or sample processing methods. We hypothesized that changes in peripheral blood expression profiles correlate with biopsy-proven rejection, and that these changes could be used as biomarkers for the diagnosis and prediction of acute rejection.
2012-12-26 | GSE14346 | GEO
Project description:In this study, we examined transcriptional profiles from 3 different microarray platforms, across 103 peripheral blood samples with and without acute rejection, to find a critical gene-set for the diagnosis of acute renal rejection that matched biopsy diagnosis, irrespective of patient demographics, clinical confounders, concomitant infection, immunosuppression usage or sample processing methods. We hypothesized that changes in peripheral blood expression profiles correlate with biopsy-proven rejection, and that these changes could be used as biomarkers for the diagnosis and prediction of acute rejection. This SuperSeries is composed of the SubSeries listed below.
2012-12-26 | GSE14067 | GEO
Project description:In this study, we examined transcriptional profiles from 3 different microarray platforms, across 103 peripheral blood samples with and without acute rejection, to find a critical gene-set for the diagnosis of acute renal rejection that matched biopsy diagnosis, irrespective of patient demographics, clinical confounders, concomitant infection, immunosuppression usage or sample processing methods. We hypothesized that changes in peripheral blood expression profiles correlate with biopsy-proven rejection, and that these changes could be used as biomarkers for the diagnosis and prediction of acute rejection. Disease State: Acute Rejection (AR#sampleid) or Stable (S#sampleid) samples We performed cross-sectional microarray analysis of 103 matched peripheral blood samples collected at a single time point, timed with a biopsy where acute rejection was either confirmed as present (60 AR samples) or absent (62 STA samples). The samples were hybridized to one of 3 microarray platforms: Affymetrix (n=75 the 54K HG-U133_Plus2 Array), Agilent (n=26, 44K oligo Array) and cDNA array (n=21, ~30K cDNA). Of 103 samples, 14 were used on both Affy and Agilent arrays; 1 was used in cDNA and Agilent array and 2 were used across 3 array platforms. Microarray data generated from 3 array platforms were cross-compared, by mapping common and overlapping transcripts to Human Gene Organization (HUGO) gene names. Significant gene lists on each platform were identified using Significant Analysis of Microarray (SAM, ref) with a common significance threshold of a false discovery rate (FDR) of <10%. This set contains the data for samples hybridized to cDNA arrays.
2012-12-26 | E-GEOD-14357 | biostudies-arrayexpress
Project description:In this study, we examined transcriptional profiles from 3 different microarray platforms, across 103 peripheral blood samples with and without acute rejection, to find a critical gene-set for the diagnosis of acute renal rejection that matched biopsy diagnosis, irrespective of patient demographics, clinical confounders, concomitant infection, immunosuppression usage or sample processing methods. We hypothesized that changes in peripheral blood expression profiles correlate with biopsy-proven rejection, and that these changes could be used as biomarkers for the diagnosis and prediction of acute rejection. We performed cross-sectional microarray analysis of 103 matched peripheral blood samples collected at a single time point, timed with a biopsy where acute rejection was either confirmed as present (60 AR samples) or absent (62 STA samples). The samples were hybridized to one of 3 microarray platforms: Affymetrix (n=75 the 54K HG-U133_Plus2 Array), Agilent (n=26, 44K oligo Array) and cDNA array (n=21, ~30K cDNA). Of 103 samples, 14 were used on both Affy and Agilent arrays; 1 was used in cDNA and Agilent array and 2 were used across 3 array platforms. Microarray data generated from 3 array platforms were cross-compared, by mapping common and overlapping transcripts to Human Gene Organization (HUGO) gene names. Significant gene lists on each platform were identified using Significant Analysis of Microarray (SAM, ref) with a common significance threshold of a false discovery rate (FDR) of <10%.This set contains the data for samples hybridized to Affymetrix arrays. Disease State: Acute Rejection (AR#sampleid) or Stable (S#sampleid) samples. This dataset is part of the TransQST collection.
2012-12-26 | E-GEOD-14346 | biostudies-arrayexpress
Project description:In this study, we examined transcriptional profiles from 3 different microarray platforms, across 103 peripheral blood samples with and without acute rejection, to find a critical gene-set for the diagnosis of acute renal rejection that matched biopsy diagnosis, irrespective of patient demographics, clinical confounders, concomitant infection, immunosuppression usage or sample processing methods. We hypothesized that changes in peripheral blood expression profiles correlate with biopsy-proven rejection, and that these changes could be used as biomarkers for the diagnosis and prediction of acute rejection. This SuperSeries is composed of the SubSeries listed below. We performed cross-sectional microarray analysis of 103 matched peripheral blood samples collected at a single time point, timed with a biopsy where acute rejection was either confirmed as present (60 AR samples) or absent (62 STA samples). The samples were hybridized to one of 3 microarray platforms: Affymetrix (n=75 the 54K HG-U133_Plus2 Array), Agilent (n=26, 44K oligo Array) and cDNA array (n=21, ~30K cDNA). Of 103 samples, 14 were used on both Affy and Agilent arrays; 1 was used in cDNA and Agilent array and 2 were used across 3 array platforms. Microarray data generated from 3 array platforms were cross-compared, by mapping common and overlapping transcripts to Human Gene Organization (HUGO) gene names. Significant gene lists on each platform were identified using Significant Analysis of Microarray (SAM, ref) with a common significance threshold of a false discovery rate (FDR) of <10%.This set contains the data for samples hybridized to Affymetrix arrays. Refer to individual Series
2012-12-26 | E-GEOD-14067 | biostudies-arrayexpress
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:Histological features of acute rejection can be detected in surveillance biopsies despite stable graft function and can negatively impact graft outcomes. However, routine surveillance biopsies for detection of subclinical rejection are not generally performed due to potential risks and costs associated with repeated biopsies. Noninvasive biomarkers are required to facilitate early detection of acute rejection and borderline changes. We examined the impact of histological abnormalities at 3-month in surveillance biopsies on graft outcomes in kidney transplant recipients from the prospective Genomics of Chronic Allograft Rejection (GoCAR) study. We then performed RNA sequencing on whole blood collected at the time of biopsy in 88 patients (22 vs. 66) to identify transcripts associated with histological abnormalities. Subjects with subclinical ACR or borderline ACR at 3 month (ACR-3) had higher risk of subsequent clinical acute rejection at 12 and 24 month (P < 0.05), more rapid functional decline (P < 0.05) and a decreased graft survival in adjusted cox analysis (P < 0.01) than patients with no abnormalities on 3-month biopsy. We then identified a 17-gene signature in peripheral blood that accurately diagnosed ACR-3. The gene set was then validated for diagnosis of ACR-3 using microarray data (N=65; 12 vs. 53; 26 overlapping with the RNAseq cohort).
2019-09-11 | GSE120397 | 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
2014-03-01 | GSE15296 | GEO