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GSE46474
Homo sapiens
37 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Acute renal allograft rejection is an important complication in kidney transplantation. Accurate diagnosis of rejection events is necessary for timely response and treatment. We illustrate the usefulness and biological relevance of selected multivariate approaches to detect rejection from genomic and proteomic signals. The data was used to study gene expression changes using whole genome microarray analysis of peripheral blood from subjects with acute rejection (n=20) and non-rejecting controls (n=20) to obtain insight into the molecular and biological causation of acute renal allograft rejection when combined with proteomics (iTRAQ) data for the same patients/time-points.
Publication Title
Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study.
Sample Metadata Fields
Sex, Specimen part, Race
View Samples- Homo sapiens
- 34 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Peripheral blood gene expression changes during allergen inhalation challenge in atopic asthmatic individuals.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 18 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
To determine differential gene expression in peripheral blood of asthmatic individuals undergoing allergen inhalation challenge, post-challenge compared to pre-challenge
Publication Title
Peripheral blood gene expression changes during allergen inhalation challenge in atopic asthmatic individuals.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 8 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Detecting differential changes in the peripheral whole-blood transcriptome, post-challenge compared to pre-challenge; using non-globin reduced PAXgene (PAX.NGR) tubes
Publication Title
Peripheral blood gene expression changes during allergen inhalation challenge in atopic asthmatic individuals.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 8 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Detecting differential changes in the peripheral whole-blood transcriptome, post-challenge compared to pre-challenge; using globin reduced PAXgene (PAX.GR) tubes
Publication Title
Peripheral blood gene expression changes during allergen inhalation challenge in atopic asthmatic individuals.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 23 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Acute cardiac allograft rejection is a serious complication of heart transplantation. Investigating molecular processes in whole blood via microarrays is a promising avenue of research in transplantation, particularly due to the non-invasive nature of blood sampling. However, whole blood is a complex tissue and the consequent heterogeneity in composition amongst samples is ignored in traditional microarray analysis. This complicates the biological interpretation of microarray data. Here we have applied a statistical deconvolution approach, cell-specific significance analysis of microarrays (csSAM), to whole blood samples from subjects either undergoing acute heart allograft rejection (AR) or not (NR). We identified eight differentially expressed probe-sets significantly correlated to monocytes (mapping to 6 genes, all down-regulated in ARs versus NRs) at a false discovery rate (FDR) <= 15%. None of the genes identified are present in a biomarker panel of acute heart rejection previously published by our group and discovered in the same data.
Publication Title
White blood cell differentials enrich whole blood expression data in the context of acute cardiac allograft rejection.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 51 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
Changes in Treg function are difficult to quantify due to the lack of Treg-exclusive markers in humans and the complexity of functional experiments. We sorted naive and memory human Tregs and conventional T cells, and identified genes that identify human Tregs regardless of their state of activation. We developed this Treg signature using Affymetrix human genome U133A 2.0 microarrays.
Publication Title
A Regulatory T-Cell Gene Signature Is a Specific and Sensitive Biomarker to Identify Children With New-Onset Type 1 Diabetes.
Sample Metadata Fields
Treatment, Subject
View Samples- Homo sapiens
- 529 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
Background: COPD is currently the fourth leading cause of death worldwide and predicted to rank third by 2020. Statins are commonly used lipid lowering agents with documented benefits on cardiovascular morbidity and mortality, and have also been shown to have pleiotropic effects including anti-inflammatory and anti-oxidant activity. Objective: Identify a gene signature associated with statin use in the blood of COPD patients, and identify molecular mechanisms and pathways underpinning this signature that could explain any potential benefits in COPD. Methods: Whole blood gene expression was measured on 168 statin users and 452 non-users from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study. Gene expression was measured using the Affymetrix Human Gene 1.1 ST microarray chips. Factor Analysis for Robust Microarray Summarization (FARMS) was used to process the expression data and to filter out non-informative probe sets. Differential gene expression analysis was undertaken using the Linear Models for Microarray data (Limma) package adjusting for propensity score and employing a surrogate variable analysis. Similarity of the expression signal with published gene expression profiles was performed in ProfileChaser. Results: 18 genes were differentially expressed between statin users and non-users at a false discovery rate of 10%. Top genes included LDLR, ABCA1, ABCG1, MYLIP, SC4MOL, and DHCR24. The 18 genes were significantly enriched in pathways and biological processes related to cholesterol homeostasis and metabolism, and were enriched for transcription factor binding sites for sterol regulatory element binding protein 2 (SREBP-2). The resulting gene signature showed correlation with Huntington disease, Parkinsons disease and acute myeloid leukemia. Conclusion: Statins gene signature was not enriched in any pathways related to respiratory diseases, beyond the drugs effect on cholesterol homeostasis.
Publication Title
The Effect of Statins on Blood Gene Expression in COPD.
Sample Metadata Fields
Sex, Age, Disease
View Samples- Homo sapiens
- 47 Downloadable Samples
IlluminaHiSeq2000
Description
In this study we aimed to assess technical variability associated with globin depletion in addition to assessing general technical variability in RNA-Seq from whole blood derived samples. We compared technical and biological replicates having undergone globin depletion or not and found that globin depletion removed approximately 80% of globin transcripts, improved the correlation of technical replicates, allowed for reliable detection of thousands of additional transcripts and generally increased transcript abundance measures. Overall design: Peripheral whole blood transcriptome assessed by RNA-Seq on Illumina HiSeq 2000 in 6 healthy individuals and 6 pooled samples, either globin depleted or not.
Publication Title
Variation in RNA-Seq transcriptome profiles of peripheral whole blood from healthy individuals with and without globin depletion.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 35 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Acute rejection in cardiac transplant patients is still a contributing factor to limited survival of the implanted heart. Currently there are no biomarkers in clinical use that can predict, at the time of transplantation, the likelihood of post-transplantation acute rejection, which would be of great importance for personalizing immunosuppressive treatment. Within the Biomarkers in Transplantation initiative, the predictive biomarker discovery focused on data and samples collected before or during transplantation such as: clinical variables, genes and proteins from the recipient, and genes from the donor. Based on this study, the best predictive biomarker panel contains genes from the recipient whole blood and from donor endomyocardial tissue and has an estimated area under the curve of 0.90. This biomarker panel provides clinically relevant prediction power and may help personalize immunosuppressive treatment and frequency of rejection monitoring.
Publication Title
Predicting acute cardiac rejection from donor heart and pre-transplant recipient blood gene expression.
Sample Metadata Fields
Sex, Age, Specimen part, Race
View Samples