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accession-icon GSE65391
Longitudinal transcriptional pediatric SLE study with clinical parameters
  • organism-icon Homo sapiens
  • sample-icon 996 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The goal of the study was to identify transcriptional correlates of SLE disease activity both at the cohort and at the individual levels. To do so, we longitudinally profiled the whole blood transcriptomes of 158 SLE patients by microarray for up to 4 years, yielding 924 SLE samples and 48 matched pediatric healthy samples. The transcriptional data are complemented by demographic, laboratory and clinical data.

Publication Title

Personalized Immunomonitoring Uncovers Molecular Networks that Stratify Lupus Patients.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Treatment, Race, Subject

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accession-icon GSE44722
Transcriptional specialization of human dendritic cell subsets in response to microbial vaccines
  • organism-icon Homo sapiens
  • sample-icon 351 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip, Illumina HumanHT-12 V3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptional specialization of human dendritic cell subsets in response to microbial vaccines.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE80325
A multidimensional blood stimulation assay reveals immune alterations underlying systemic juvenile idiopathic arthritis
  • organism-icon Homo sapiens
  • sample-icon 291 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment, Subject, Time

View Samples
accession-icon GSE64456
Defining RNA Transcriptional Biosignatures to Distinguish Febrile Infants 60 Days of Age and Younger with Bacterial vs Non-Bacterial Infections
  • organism-icon Homo sapiens
  • sample-icon 298 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The use of microbiological cultures for diagnosing bacterial infections in young febrile infants have substantial limitations, including false positive and false negative cultures, and non-ideal turn-around times. Analysis of host genomic expression patterns (RNA biosignatures) in response to the presence of specific pathogens, however, may provide an alternate and potentially improved diagnostic approach. This study was designed to define bacterial and non-bacterial RNA biosignatures to distinguish these infections in young febrile infants.

Publication Title

Association of RNA Biosignatures With Bacterial Infections in Febrile Infants Aged 60 Days or Younger.

Sample Metadata Fields

Sex, Age, Specimen part, Race

View Samples
accession-icon GSE103500
Healthy adult and sJIA blood stimulation with innate immune ligands
  • organism-icon Homo sapiens
  • sample-icon 291 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The goal of this study was to characterize altered inducible immune networks in Systemic onset juvenile idiopathic arthritis (sJIA), an IL-1-driven autoinflammatory disease of unknown etiology. To this end, we developed a high-throughput assay that quantifies the transcriptional and protein-level responses of blood leukocytes to innate stimuli. Herein, we report transcriptional data from healthy adult blood stimulated with 16 different conditions, including TLR ligands, cytosolic receptor ligands and inflammatory cytokines. We further report blood transcriptional profiles from sJIA patients with various disease activity and treatment statuses, both ex vivo (baseline) and after in vitro stimulation with a subset of innate stimuli including heat-killed bacterial pathogens.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Disease stage, Treatment, Subject, Time

View Samples
accession-icon GSE68004
Whole blood Transcriptional Profiles as a Prognostic and Diagnostic Tool in Complete and Incomplete Kawasaki Disease
  • organism-icon Homo sapiens
  • sample-icon 162 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The diagnosis of Kawasaki disease (KD) is often difficult to distinguish from adenovirus (HAdV) and Group A streptococcal disease (GAS). We sought to: 1) to define the KD transcriptional signature that can aid in the diagnosis of complete and incomplete KD in children; 2) to identify specific biomarkers that objectively discriminate between KD and other mimicking conditions, including HAdV and 3) to test the prognostic utility of GEP to determine response to IVIG therapy and development of coronary artery lesions (CAL). Methods: Blood RNA samples were analyzed from 76 pediatric patients with complete KD, 13 with incomplete KD, 19 patients with HAdV, 17 patients with GAS disease, and age- and sex-matched healthy controls (HC). We used class comparisons (MW p< 0.01, Benjamini-Hochberg, and 1.25 fold change filter), class prediction, modular analysis and MDTH analyses to define the specificity of the KD profiles and identify markers of severity. Results: Statistical group comparisons identified 7,899 genes differentially expressed in 39 complete KD patients versus HC (KD biosignature). This signature was validated in another 37 patients with complete KD and in 13 patients with incomplete KD. Modular analysis in children with complete KD demonstrated overexpression of inflammation, neutrophils, myeloid cell, coagulation cascade, and cell cycle genes. The KNN class prediction algorithm identified 25-classifier genes that differentiated children with KD vs HAdV infection in two independent cohorts of patients with 96% (95% CI [80%-99%]) sensitivity and 95% [74%-99%] specificity. MDTH scores in KD patients significantly correlated with the baseline c-reactive protein (R=0.29, p=0.008) and was four fold higher than in children with HAdV (p<0.01). In addition, KD patients that remained febrile 36 hours after treatment with IVIG (non-responders) demonstrated higher baseline, pre-treatment MDTH values compared with responders [12,290 vs. 5,572 respectively; p=0.009]. Conclusion: Transcriptional signatures can be used as a tool to discriminate between KD and HAdV infection, and may also provide prognostic information.

Publication Title

Whole blood transcriptional profiles as a prognostic tool in complete and incomplete Kawasaki Disease.

Sample Metadata Fields

Sex, Specimen part, Race

View Samples
accession-icon GSE67059
Whole Blood Transcriptional Profiling Differentiates Between Asymptomatic and Symptomatic Human Rhinovirus Detection in Children
  • organism-icon Homo sapiens
  • sample-icon 151 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Human rhinoviruses (HRV) are among the most common causes of respiratory infections in humans but can be frequently detected also in asymptomatic subjects. We evaluated the value of gene expression profiles to differentiate asymptomatic detection from symptomatic HRV infection in children.

Publication Title

Rhinovirus Detection in Symptomatic and Asymptomatic Children: Value of Host Transcriptome Analysis.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Race

View Samples
accession-icon GSE46923
Systemic lupus erythematosus
  • organism-icon Homo sapiens
  • sample-icon 139 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133B Array (hgu133b), Affymetrix Human Genome U133A Array (hgu133a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

IFN priming is necessary but not sufficient to turn on a migratory dendritic cell program in lupus monocytes.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment, Subject, Time

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accession-icon GSE44721
IL4 DCs and monocytes stimulated by 13 human vaccines and LPS for 6hr
  • organism-icon Homo sapiens
  • sample-icon 128 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip, Illumina HumanHT-12 V4.0 expression beadchip

Description

While dendritic cells (DCs) are known to play a major role in the process of vaccination, the mechanisms by which vaccines induce protective immunity in humans remain elusive. Herein, we used gene microarrays to characterize the transcriptional programs induced over time in human monocyte-derived DCs (moDCs) in vitro in response to influenza H1N1 Brisbane, Salmonella enterica and Staphylococcus aureus. We built a data-driven modular analytical framework focused on 204 pathogen-induced gene clusters. The expression of these modules was analyzed in response to 16 well-defined ligands, targeting TLRs, cytoplasmic PAMP receptors and cytokine receptors. This multi-dimensional framework covers the major biological functions of APC, including the IFN response, inflammation, DC maturation, T cell activation, antigen processing, cell motility and histone regulation. This framework was used to characterize the response of monocytes and moDCs to 14 commercially available vaccines. These vaccines displayed quantitatively and qualitatively distinct modular signatures in monocytes and DCs, in particular Fluzone and Pneumovax, highlighting the functional and phenotypic differences between APC subsets. This modular framework allows the application of systems immunology approaches to study early transcriptional changes in human APC subsets in response to pathogens and vaccines, which might guide the development of improved vaccines.

Publication Title

Transcriptional specialization of human dendritic cell subsets in response to microbial vaccines.

Sample Metadata Fields

Specimen part, Subject, Time

View Samples
accession-icon GSE44720
IFNa DCs and IL4 DCs exposed to H1N1, heat killed S. aureus, or heat killed S. enterica (HKSE) for 1h, 2h, 6h, 12h, or 24h
  • organism-icon Homo sapiens
  • sample-icon 120 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip, Illumina HumanHT-12 V4.0 expression beadchip

Description

While dendritic cells (DCs) are known to play a major role in the process of vaccination, the mechanisms by which vaccines induce protective immunity in humans remain elusive. Herein, we used gene microarrays to characterize the transcriptional programs induced over time in human monocyte-derived DCs (moDCs) in vitro in response to influenza H1N1 Brisbane, Salmonella enterica and Staphylococcus aureus. We built a data-driven modular analytical framework focused on 204 pathogen-induced gene clusters. The expression of these modules was analyzed in response to 16 well-defined ligands, targeting TLRs, cytoplasmic PAMP receptors and cytokine receptors. This multi-dimensional framework covers the major biological functions of APC, including the IFN response, inflammation, DC maturation, T cell activation, antigen processing, cell motility and histone regulation. This framework was used to characterize the response of monocytes and moDCs to 14 commercially available vaccines. These vaccines displayed quantitatively and qualitatively distinct modular signatures in monocytes and DCs, in particular Fluzone and Pneumovax, highlighting the functional and phenotypic differences between APC subsets. This modular framework allows the application of systems immunology approaches to study early transcriptional changes in human APC subsets in response to pathogens and vaccines, which might guide the development of improved vaccines.

Publication Title

Transcriptional specialization of human dendritic cell subsets in response to microbial vaccines.

Sample Metadata Fields

Specimen part, Subject, Time

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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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