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accession-icon GSE20214
Gene expression profiling of pancreatic islets in BioBreeding rats
  • organism-icon Rattus norvegicus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Like humans, the NOD mouse and other diabetes susceptible rat strains, T1D in BB rats is dependent on the major histocompatibility complex (MHC, insulin dependent diabetes mellitus locus 1, Iddm1) located on chromosome 20. In rats this is the HLA-DQB1 homologue RT1-B, specifically the RT1u haplotype. Our studies employ congenic derivatives of the BB rat, the DRlyp/lyp and DR+/+ strains, which differ only by the 2 Mb lyp (lymphopenia, Iddm2) region on chromosome 4. TID in the lymphopenic DRlyp/lyp rat is spontaneous and onset occurs in 100% of animals during adolescence (65.3+/-6.3 days) due to a recessive mutation within GIMAP5 (GTPase, IMAP family member 5). Gimap5 is a mitochondrial GTP-binding protein necessary for post-thymic T cell survival. The spontaneously diabetic phenotype observed in DRlyp/lyp rats is thought to be elicited through deficiency in CD4+CD25+ TREG cells as T1D in lymphopenic BB rats can be rescued through adoptive transfer of this population. Genetic variation in GIMAP5 has been associated with the development of protein-tyrosine phosphatase-2 (IA-2) autoantibodies in human T1D [28] and is significantly associated with systemic lupus erythematosus (SLE). The non-lymphopenic DR+/+ strain possesses wild-type GIMAP5 alleles and does not develop spontaneous T1D, however, T1D is inducible through administration of lymphotoxic anti-RT6 monoclonal antibody and immune activating polyinosinic polycytidylic acid (poly I:C; a ligand of toll-like receptor 3), or through viral depletion of CD4+CD25+ regulatory T (TREG) cells. Such treatments do not induce T1D in the related Wistar-Furth (WF) rats and suggest the presence of an underlying diabetic predisposition in BB rats that is phenotypically manifested upon loss of immune regulation.

Publication Title

Biobreeding rat islets exhibit reduced antioxidative defense and N-acetyl cysteine treatment delays type 1 diabetes.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE35713
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes
  • organism-icon Homo sapiens
  • sample-icon 202 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE35725
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [T1D_114]
  • organism-icon Homo sapiens
  • sample-icon 114 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we analyzed larger RO T1D and HC cohorts. In addition, we examined T1D progression by looking at longitudinal, pre-onset and longstanding T1D samples.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35711
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [CF_S1S3_5Auto_20CF_10HC]
  • organism-icon Homo sapiens
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we compared the signature found between unrelated healthy controls and non-diabetic cystic fibrosis patients possessing Pseudomonas aeruginosa pulmonary tract infection.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35716
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [Pneu_S3S24_10Pneu_4HC]
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we compared the signature found between unrelated healthy controls and patients with bacterial pneumonia.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35712
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [H1N1_S5_5Pre_5D0]
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we compared the signature found in pre H1N1 samples to the signature associated with active H1N1 flu.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE60674
Upregulation of Interferon-inducible and damage response pathways in chronic graft-versus-host disease
  • organism-icon Homo sapiens
  • sample-icon 34 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To identify systemic cytokine patterns in Chronic Graft-versus-Host-Disease (CGVHD), we profiled the gene expression of circulating monocytes. Pathway analysis identified two gene sets that were significantly upregulated across a broad range of patients with inflammatory and sclerotic presentations: (1) genes induced by Type I and Type II IFN, and (2) receptor genes for innate immune responses to cellular damage. Multiple IFN-inducible genes involved in signal transduction, anti-viral function, lymphocyte homeostasis, trafficking, and antigen presentation were increased. Furthermore, upregulation of TLR/NLR/CLR receptor genes for nucleic acids, ribonucleoproteins and annexin implicated response to damaged cells as a source of activation of inflammasomes and induction of Type I IFN.

Publication Title

Upregulation of IFN-Inducible and Damage-Response Pathways in Chronic Graft-versus-Host Disease.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE9675
Maternal Diabetes alters Transcriptional Programs in the Developing Embryo
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Diabetic embryopathy can affect any developing organ system, although cardiovascular malformations, neural tube defects and caudal dysgenesis syndrome are the most prominent congenital malformations. We hypothesize that the metabolic imbalance occurring in diabetic pregnancy de-regulates tissue specific gene expression programs in the developing embryo. In order to identify genes whose expression is affected by maternal diabetes, we analyzed gene expression profiles of diabetes-exposed mouse embryos by using Affymetrix microarrays. We identified 129 genes with altered expression levels; 21 genes had increased and 108 genes had decreased expression levels in diabetes-exposed embryos relative to controls. A substantial fraction of these genes (35) are essential for normal embryonic development as shown by functional studies in mouse models. The largest fraction of diabetes-affected genes was in transcription factor and DNA-binding/chromatin remodeling functional categories (19%), which directly affect transcription. These findings suggest that transcriptional regulation in the developing embryos is perturbed by maternal diabetes and that transcriptional regulation plays a major role in the responses of embryos to intrauterine exposure to diabetic conditions. Interestingly, we found the expression of hypoxia-inducible factor 1 (Hif1) deregulated in the embryos exposed to the conditions of maternal diabetes. Since hypoxic stress is associated with the complications of diabetic pregnancy, we performed a post-hoc analysis of our microarray data with a specific focus on known HIF1 target genes. Of 39 genes detected in our microarrays, the expression changes of 22 genes (20 were increased and two genes were decreased in diabetes-exposed embryos) were statistically significant. These results indicate that HIF1-regulated pathways are affected in diabetes-exposed embryos. These results strongly suggest that de-regulation of hypoxia/HIF1 activated pathways could be the one of the key molecular events associated with the exposure to the teratogenic intrauterine environment of a diabetic mother.

Publication Title

Maternal diabetes alters transcriptional programs in the developing embryo.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE41095
Maternal diabetes alters transcriptional programs in the developing embryo.
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Exposure to maternal diabetes during pregnancy alters transcriptional profiles in the developing embryo. The enrichment, within the set of de-regulated genes, of those encoding transcriptional regulatory molecules provides support for the hypothesis that maternal diabetes affects specific developmental programs.

Publication Title

Maternal diabetes alters transcriptional programs in the developing embryo.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE3077
Dillution series comparison of Affymetrix and Illumina Expression Platforms
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The growth in popularity of RNA expression microarrays has been accompanied by concerns about the reliability of the data especially when comparing between different platforms. Here we present an evaluation of the reproducibility of microarray results using two platforms, Affymetrix GeneChips and Illumina BeadArrays. The study design is based on a dilution series of two human tissues (blood and placenta), tested in duplicate on each platform. By a variety of measures the two platforms yielded data of similar quality and properties. The results of a comparison between the platforms indicate very high agreement, particularly for genes which are predicted to be differentially expressed between the two tissues. Agreement was strongly correlated with the level of expression of a gene. Concordance was also improved when probes on the two platforms could be identified as being likely to target the same set of transcripts of a given gene. These results shed light on the causes or failures of agreement across microarray platforms. The set of probes we found to be most highly reproducible can be used by others to help increase confidence in analyses of other data sets using these platforms.

Publication Title

Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms.

Sample Metadata Fields

No sample metadata fields

View Samples
...

refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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