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accession-icon GSE45885
Potential biomarkers of non-obstructive azoospermia identified in microarray gene expression analysis
  • organism-icon Homo sapiens
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We analyzed gene expression profiles of human testicular biopsies in men with idiopathic nonobstructive azoospermia. Using new generation oligonucleotide microarray platform GeneChip Human Gene 1.0 ST, we identified genes which could be potential biomarkers of azoospermia and molecular indicators that could determine a particular stage of impaired spermatogenesis. Thus, we shed light on genes which were had so far been weakly characterized and which were had never related to infertility before. These studies also included the comparative analysis of the hierarchical clustering of gene expression profile with histopathological data provided for azoospermic patients.

Publication Title

Potential biomarkers of nonobstructive azoospermia identified in microarray gene expression analysis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE45887
The gene expression analysis of paracrine/autocrine factors in patients with spermatogenetic failure compared to normal spermatogenesis
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The role of paracrine/autocrine factors in inflammation, immune response and tumor development is well established. There is also an evidence that some of the cytokines there involved may participate in the regulation of the male gonads. However, their involvement in pathogenesis of male infertility has not been well defined yet. The aim of the present study was to examine the expression levels of IL-1 family members, IL-6, IL-10, TNF family, SCF and c-kit in infertile patients with idiopathic non-obstructive azoospermia (NOA) compared to men with normal spermatogenesis

Publication Title

The gene expression analysis of paracrine/autocrine factors in patients with spermatogenetic failure compared with normal spermatogenesis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE51111
Potential biomarkers tah could help to determine the prognosis of azoospermia treatment
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We analyzed gene expression profiles of human testicular biopsies in men with idiopathic nonobstructive azoospermia who underwent therapy with hCG/rFSH. Using new generation oligonucleotide microarray platform GeneChip Human Gene 1.0 ST, we identified genes which could be potential prognostic biomarkers of azoospermia treatment.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE63099
BMSC gene expression in co-culture with endothelial cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

In this experiment human Bone Marrow Stem Cells (hBMSCs) are grown in co-culture with Human Umbilical Vein Endothelial Cells (HUVECs) for 5 days, HUVECs are removed by trypsination before call harvest. In parallel hBMSCs are grown in monoculture as a control for 5 days, and a sham trypsination performed before harvesting of the cells.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon GSE73072
Host gene expression signatures of H1N1, H3N2, HRV, RSV virus infection in adults
  • organism-icon Homo sapiens
  • sample-icon 2886 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.

Publication Title

An individualized predictor of health and disease using paired reference and target samples.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE138914
Gene expression data from lymphoblastoid cell lines from African American participants in the GENOA study
  • organism-icon Homo sapiens
  • sample-icon 711 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

African-American individuals of the GENOA cohort

Publication Title

Genetic Architecture of Gene Expression in European and African Americans: An eQTL Mapping Study in GENOA.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE18927
University of Washington Human Reference Epigenome Mapping Project
  • organism-icon Homo sapiens
  • sample-icon 97 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

The NIH Roadmap Epigenomics Mapping Consortium aims to produce a public resource of epigenomic maps for stem cells and primary ex vivo tissues selected to represent the normal counterparts of tissues and organ systems frequently involved in human disease.

Publication Title

The NIH Roadmap Epigenomics Mapping Consortium.

Sample Metadata Fields

Sex, Specimen part, Disease, Subject

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accession-icon GSE30211
Gene expression changes during Type 1 diabetes pathogenesis
  • organism-icon Homo sapiens
  • sample-icon 724 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip, Affymetrix Human Genome U219 Array (hgu219)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE45642
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder [control set]
  • organism-icon Homo sapiens
  • sample-icon 667 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

A cardinal symptom of Major Depressive Disorder (MDD) is the disruption of circadian patterns. Yet, to date, there is no direct evidence of circadian clock dysregulation in the brains of MDD patients. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain was difficult to characterize. Here we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-hour cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ('Controls') and 34 MDD patients. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (AnCg), hippocampus (HC), amygdala (AMY), nucleus accumbens (NAcc) and cerebellum (CB). Several hundred transcripts in each region showed 24-hour cyclic patterns in Controls, and >100 transcripts exhibited consistent rhythmicity and phase-synchrony across regions. Among the top ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERB), DBP, BHLHE40(DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in MDD brains, due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This is the first transcriptome-wide analysis of cyclic patterns in the human brain and demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggest novel molecular targets for treatment of mood disorders.

Publication Title

Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.

Sample Metadata Fields

Subject

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accession-icon GSE71620
The effects of aging on circadian patterns of gene expression in the human prefrontal cortex
  • organism-icon Homo sapiens
  • sample-icon 419 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

With aging, significant changes in circadian rhythms occur, including a shift in phase toward a morning chronotype and a loss of rhythmicity in circulating hormones. However, the effects of aging on molecular rhythms in the human brain have remained elusive. Here we employed a previously-described time-of-death analyses to identify transcripts throughout the genome that have a significant circadian rhythm in expression in the human prefrontal cortex (Brodmanns areas (BA) 11 and 47). Expression levels were determined by microarray analysis in 146 individuals. Rhythmicity in expression was found in ~10% of detected transcripts (p<0.05). Using a meta-analysis across the two brain areas, we identified a core set of 235 genes (q<0.05) with significant circadian rhythms of expression. These 235 genes showed 92% concordance in the phase of expression between the two areas. In addition to the canonical core circadian genes, a number of other genes were found to exhibit rhythmic expression in the brain. Notably, we identified more than one thousand genes (1186 in BA11; 1591 in BA47) that exhibited age-dependent rhythmicity or alterations in rhythmicity patterns with aging. Interestingly, a set of transcripts gained rhythmicity in older individuals, which may represent a compensatory mechanism due to a loss of canonical clock function. Thus, we confirm that rhythmic gene expression can be reliably measured in human brain and identified for the first time significant changes in molecular rhythms with aging that may contribute to altered cognition, sleep and mood in later life.

Publication Title

Effects of aging on circadian patterns of gene expression in the human prefrontal cortex.

Sample Metadata Fields

Sex, Age, Specimen part, Race

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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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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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