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Transcription profiling of peripheral blood from stable and acute rejection pediatric kidney transplant patients.

ABSTRACT: Full title: Expression data from whole blood gene expression analysis of stable and acute rejection pediatric kidney transplant patients Tissues are often made up of multiple cell-types. Blood, for example, contains many different cell-types, each with its own functional attributes and molecular signature. In humans, because of its accessibility and immune functionality, blood cells have been used as a source for RNA-based biomarkers for many diseases. Yet, the proportions of any given cell-type in the blood can vary markedly, even between normal individuals. This results in a significant loss of sensitivity in gene expression studies of blood cells and great difficulty in identifying the cellular source of any perturbations. Ideally, one would like to perform differential expression analysis between patient groups for each of the cell-types within a tissue but this is impractical and prohibitively expensive. This dataset is the validation dataset used to test the csSAM gene expression deconvolution algorithm as reported in the accompanying paper. Whole blood gene expression measurements for 24 pediatric renal transplant patients were analyzed on human specific HGU133V2.0 (+) whole genome expression arrays. Blood drawn using PaxGene Blood RNA Tubes (PreAnalytiX, Qiagen).

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PROVIDER: S-DIXA-D-1057 | biostudies-other |

REPOSITORIES: biostudies-other

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Transcription profiling of peripheral blood from stable and acute rejection pediatric kidney transplant patients.

Project description:Full title: Expression data from whole blood gene expression analysis of stable and acute rejection pediatric kidney transplant patients Tissues are often made up of multiple cell-types. Blood, for example, contains many different cell-types, each with its own functional attributes and molecular signature. In humans, because of its accessibility and immune functionality, blood cells have been used as a source for RNA-based biomarkers for many diseases. Yet, the proportions of any given cell-type in the blood can vary markedly, even between normal individuals. This results in a significant loss of sensitivity in gene expression studies of blood cells and great difficulty in identifying the cellular source of any perturbations. Ideally, one would like to perform differential expression analysis between patient groups for each of the cell-types within a tissue but this is impractical and prohibitively expensive. This dataset is the validation dataset used to test the csSAM gene expression deconvolution algorithm as reported in the accompanying paper. Whole blood gene expression measurements for 24 pediatric renal transplant patients were analyzed on human specific HGU133V2.0 (+) whole genome expression arrays. Blood drawn using PaxGene Blood RNA Tubes (PreAnalytiX, Qiagen).

2010-04-06 | E-GEOD-20300 | biostudies-arrayexpress

Whole blood gene expression analysis of stable and acute rejection pediatric kidney transplant patients

2010-03-08 | GSE20300 | GEO

Peripheral blood biomarker signatures for acute kidney transplant rejection

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

Molecular classifiers for acute kidney transplant rejection in peripheral blood by whole genome gene expression profiling.

Project description:There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.

| S-EPMC4439107 | biostudies-literature

Peripheral blood biomarker signatures for acute kidney transplant rejection

2014-03-01 | E-GEOD-15296 | biostudies-arrayexpress

Transcription profiling of human kidney and peripheral blood lymphocytes from kidney transplant patients

Project description: Not available

| S-DIXA-D-1031 | biostudies-other

Heart Transplant Rejection Profiling in Peripheral Blood

Project description:PBMC samples from heart transplant patients were profiled. Sample classification was based on endomyocardial biopsy at the time of sample collection. Keywords = Transplant Keywords = Transplantation Keywords = Heart Transplant Keywords = Graft Rejection Keywords = Rejection Keywords = PBMC Keywords = Immune Response Keywords = Peripheral Blood Keywords: other

2005-09-01 | GSE2445 | GEO

Comparative top down proteomics of peripheral blood mononuclear cells from kidney transplant recipients with normal kidney biopsies or acute rejection.

Project description:Recent studies utilizing transcriptomics, metabolomics, and bottom up proteomics have identified molecular signatures of kidney allograft pathology. Although these results make significant progress toward non-invasive differential diagnostics of dysfunction of a transplanted kidney, they provide little information on the intact, often modified, protein molecules present during progression of this pathology. Because intact proteins underpin diverse biological processes, measuring the relative abundance of their modified forms promises to advance mechanistic understanding, and might provide a new class of biomarker candidates. Here, we used top down proteomics to inventory the modified forms of whole proteins in peripheral blood mononuclear cells (PBMCs) taken at the time of kidney biopsy for 40 kidney allograft recipients either with healthy transplants or those suffering acute rejection. Supported by gas-phase fragmentation of whole protein ions during tandem mass spectrometry, we identified 344 proteins mapping to 2905 distinct molecular forms (proteoforms). Using an initial implementation of a label-free approach to quantitative top down proteomics, we obtained evidence suggesting relative abundance changes in 111 proteoforms between the two patient groups. Collectively, our work is the first to catalog intact protein molecules in PBMCs and suggests differentially abundant proteoforms for further analysis.

| S-EPMC4956503 | biostudies-literature

Heart Transplant Rejection Profiling in Peripheral Blood

2010-06-10 | E-GEOD-2445 | biostudies-arrayexpress

Kidney Transplant Rejection and Tissue Injury by Gene Profiling of Biopsies and Peripheral Blood Lymphocytes

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

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