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GSE16149
Homo sapiens
18 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies.
Publication Title
Examining smoking-induced differential gene expression changes in buccal mucosa.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 72 Downloadable Samples
- Illumina HumanHT-12 V4.0 expression beadchip
Description
Glucocorticoids (GC) and 1,25-dihydroxyvitamin D3 (1,25(OH)2 D3) are steroid hormones with anti-inflammatory properties with enhanced effects when combined. We previously showed that transcriptional response to GCs was correlated with inter-individual and inter-ethnic cellular response. Here, we profiled cellular and transcriptional responses to 1,25(OH)2 D3 from the same donors. We studied cellular response to combined treatment with GCs and 1,25(OH)2 D3 in a subset of individuals least responsive to GCs. We found that combination treatment had significantly greater inhibition of proliferation than with either steroid hormone alone. Overlapping differentially expressed (DE) genes between the two hormones were enriched for adaptive and innate immune processes. Non-overlapping differentially expressed genes with 1,25(OH)2 D3 treatment were enriched for pathways involving the electron transport chain, while with GC treatment, non-overlapping genes were enriched for RNA-related processes. These results suggest that 1,25(OH)2 D3 enhances GC anti-inflammatory properties through a number of shared and non-shared transcriptionally-mediated pathways.
Publication Title
Comparison of cellular and transcriptional responses to 1,25-dihydroxyvitamin d3 and glucocorticoids in peripheral blood mononuclear cells.
Sample Metadata Fields
Sex, Age, Specimen part, Treatment
View Samples- Homo sapiens
- 51 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we present results of our DNA microarray analysis of samples from a timecourse study of individuals given ethanol orally, and then evaluated by breathalyzer to monitor blood alcohol content (BAC). At five blood alcohol levels, T1-T5, blood was drawn such that the samples represented 0%, 0.04%, 0.08% BAC, and return to 0.04%, and 0.02% BAC. Microarray analysis showed that changes in gene expression could be detected across the time-course. We verified these expression changes by quantitative polymerase chain reaction (qPCR). Candidate target genes identified from the microarray analysis were clustered by expression change pattern, examined for shared functions and functional network membership. Five coordinately expressed groups were revealed and functional analysis showed shared transcription factor binding sites and functions for members of the clusters. These functions include protein synthesis and modification, expected for changes in gene expression, hematological and immune functions, expected for a blood sample, and pancreatic and hepatic function, expected as response to ethanol. The results provide a first look at changing gene expression patterns in blood during acute increase of ethanol concentration and its depletion due to metabolism or excretion and demonstrate that it is possible to detect significant changes in gene expression using total RNA isolated from whole blood. The analysis approach for this study can be utilized as part of a workflow to identify target genes by timecourse changes in gene expression that may affect pilot performance.
Publication Title
Microarray characterization of gene expression changes in blood during acute ethanol exposure.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 555 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Sample Metadata Fields
Subject, Time
View Samples- Homo sapiens
- 199 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.
Publication Title
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Sample Metadata Fields
Subject, Time
View Samples- Homo sapiens
- 193 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.
Publication Title
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Sample Metadata Fields
Subject, Time
View Samples- Homo sapiens
- 163 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.
Publication Title
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Sample Metadata Fields
Subject, Time
View Samples- Homo sapiens
- 59 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Synovial fibroblasts of 6 RA patients were treated with IL1 or PDGF-D. The aim of this study was to outline mechanism of the disease RA by a treatment with one of these cytokines.
Publication Title
Novel application of multi-stimuli network inference to synovial fibroblasts of rheumatoid arthritis patients.
Sample Metadata Fields
Treatment, Subject, Time
View Samples- Homo sapiens
- 40 Downloadable Samples
- Illumina HumanHT-12 V4.0 expression beadchip
Description
Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with diseases of the colon including inflammatory bowel diseases (IBD) and colorectal cancer (CRC). However, the functional role of many of these SNPs is largely unknown and tissue-specific resources are lacking. Expression quantitative trait loci (eQTL) mapping identifies target genes of disease-associated SNPs. Here, we comprehensively map eQTLs in the human colon, assess their relevance for GWAS of colonic diseases and provide functional characterization.
Publication Title
Enrichment of inflammatory bowel disease and colorectal cancer risk variants in colon expression quantitative trait loci.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 32 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory/degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers. Three multi-center genome-wide transcriptomic data sets (Affymetrix HG- U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule- based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendls statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio.
Publication Title
Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation.
Sample Metadata Fields
Sex, Age
View Samples