Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA216054 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:DNA Methylation Changes in Allergic Patients Correlate with Symptom Severity [methylation]
| PRJNA217396 | ENA
Project description:Epigenetic alterations may represent new therapeutic targets and/or biomarkers of allergic rhinitis (AR). Our aim was to examine genome-wide epigenetic changes induced by controlled pollen exposure in the Environmental Exposure Unit (EEU). 38 AR-sufferers and 8 non-allergic controls were exposed to grass pollen for 3h on two consecutive days. We interrogated DNA methylation at baseline and 3h in peripheral blood mononuclear cells (PBMCs) using the Infinium Methylation 450K array. We corrected for demographics, cell composition, and multiple testing (Benjamini-Hochberg), and verified hits using bisulfite PCR-pyrosequencing and qPCR. To extend these findings to a clinically relevant tissue, we investigated DNA methylation and gene expression of mucin 4 (MUC4), in nasal brushings from a separate validation cohort exposed to birch pollen. In PBMCs of allergic rhinitis participants, 42 sites showed significant DNA methylation changes of 2% or greater. DNA methylation changes in tryptase gamma 1 (TPSG1), schlafen 12 (SLFN12) and MUC4 in response to exposure were validated by pyrosequencing. SLFN12 DNA methylation significantly correlated with symptoms (p<0.05), and baseline DNA methylation pattern was found to be predictive of symptom severity upon grass allergen exposure (p<0.05). Changes in MUC4 DNA methylation in nasal brushings in the validation cohort correlated with drop in peak nasal inspiratory flow (Spearman r = 0.314, p = 0.034), and MUC4 gene expression was significantly increased (p<0.0001). This study revealed novel and rapid epigenetic changes upon exposure in a controlled allergen challenge facility, identified baseline epigenetic status as a predictor of symptom severity.
2018-06-01 | GSE100386 | GEO
Project description:Altered DNA methylation patterns in CD4+ T-cells indicate the importance of epigenetic mechanisms in inflammatory diseases. However, the identification of these alterations is complicated by the heterogeneity of most inflammatory diseases. Seasonal allergic rhinitis (SAR) is an optimal disease model for the study of DNA methylation because of its well-defined phenotype and etiology. We generated genome-wide DNA methylation (Npatients = 8, Ncontrols = 8) and gene expression (Npatients= 9, Ncontrols = 10) profiles of CD4+ T-cells from SAR patients and healthy controls using Illumina’s HumanMethylation450 and HT-12 microarrays, respectively. DNA methylation profiles clearly and robustly distinguished SAR patients from controls, during and outside the pollen season. Moreover, we found that this methylation signature correlated with symptom severity. In agreement with previously published studies, gene expression profiles of the same samples failed to separate patients and controls. Separation by methylation (Npatients = 12, Ncontrols = 12), but not by gene expression (Npatients = 21, Ncontrols = 21; GSE50223) was also observed in an in vitro model system in which purified PBMCs from patients and healthy controls were challenged with allergen. We observed changes in the proportions of memory T-cell populations between patients (Npatients = 35) and controls (Ncontrols= 9), which could explain the observed difference in DNA methylation. Our data highlight the potential of epigenomics in the stratification of immune disease and represents the first successful molecular classification of SAR using CD4+ T cells. Genomic DNA was isolated from CD4+ T-cells of patients with seasonal allergic rhinitis and healthy controls both during and outside the pollen season. Genomic DNA was bisulfite converted and hybridized to Illumina HumanMethylation450 BeadChip (Illumina, San Diego, CA) and scanned using the Illumina iScan.
2013-12-01 | E-GEOD-50222 | biostudies-arrayexpress
Project description:Altered DNA methylation patterns in CD4+ T-cells indicate the importance of epigenetic mechanisms in inflammatory diseases. However, the identification of these alterations is complicated by the heterogeneity of most inflammatory diseases. Seasonal allergic rhinitis (SAR) is an optimal disease model for the study of DNA methylation because of its well-defined phenotype and etiology. We generated genome-wide DNA methylation (Npatients = 8, Ncontrols = 8) and gene expression (Npatients= 9, Ncontrols = 10) profiles of CD4+ T-cells from SAR patients and healthy controls using Illumina’s HumanMethylation450 and HT-12 microarrays, respectively. DNA methylation profiles clearly and robustly distinguished SAR patients from controls, during and outside the pollen season. Moreover, we found that this methylation signature correlated with symptom severity. In agreement with previously published studies, gene expression profiles of the same samples failed to separate patients and controls. Separation by methylation (Npatients = 12, Ncontrols = 12), but not by gene expression (Npatients = 21, Ncontrols = 21) was also observed in an in vitro model system in which purified PBMCs from patients and healthy controls were challenged with allergen. We observed changes in the proportions of memory T-cell populations between patients (Npatients = 35) and controls (Ncontrols= 9), which could explain the observed difference in DNA methylation. Our data highlight the potential of epigenomics in the stratification of immune disease and represents the first successful molecular classification of SAR using CD4+ T cells. Total RNA was isolated from CD4+ T-cells of patients with seasonal allergic rhinitis and healthy controls both during and outside the pollen season. Total RNA was amplified and hybridized to Illumina HT12 version 4 human whole-genome arrays (Illumina, San Diego, CA).
2013-12-01 | E-GEOD-50101 | biostudies-arrayexpress
Project description:Blood and Nasal Epigenetics Correlate to Allergic Rhinitis Symptom Development in the Environmental Exposure Unit
| PRJNA391492 | ENA
Project description:To elucidate the epithelial cell diversity within the nasal inferior turbinates, a comprehensive investigation was conducted comparing control subjects to individuals with house dust mite-induced allergic rhinitis. This study aimed to delineate the differential expression profiles and phenotypic variations of epithelial cells in response to allergic rhinitis. This research elucidated distinct subpopulations and rare cell types of epithelial cells within the nasal turbinates, discerning alterations induced by allergic rhinitis. Furthermore, by interrogating transcriptomic signatures, the investigation provided novel insights into the cellular dynamics and immune responses underlying allergic rhinitis pathogenesis
2024-05-30 | GSE261706 | GEO
Project description:Altered DNA methylation patterns in CD4+ T-cells indicate the importance of epigenetic mechanisms in inflammatory diseases. However, the identification of these alterations is complicated by the heterogeneity of most inflammatory diseases. Seasonal allergic rhinitis (SAR) is an optimal disease model for the study of DNA methylation because of its well-defined phenotype and etiology. We generated genome-wide DNA methylation (Npatients = 8, Ncontrols = 8) and gene expression (Npatients= 9, Ncontrols = 10) profiles of CD4+ T-cells from SAR patients and healthy controls using Illumina’s HumanMethylation450 and HT-12 microarrays, respectively. DNA methylation profiles clearly and robustly distinguished SAR patients from controls, during and outside the pollen season. Moreover, we found that this methylation signature correlated with symptom severity. In agreement with previously published studies, gene expression profiles of the same samples failed to separate patients and controls. Separation by methylation (Npatients = 12, Ncontrols = 12), but not by gene expression (Npatients = 21, Ncontrols = 21; GSE50223) was also observed in an in vitro model system in which purified PBMCs from patients and healthy controls were challenged with allergen. We observed changes in the proportions of memory T-cell populations between patients (Npatients = 35) and controls (Ncontrols= 9), which could explain the observed difference in DNA methylation. Our data highlight the potential of epigenomics in the stratification of immune disease and represents the first successful molecular classification of SAR using CD4+ T cells.
2013-12-01 | GSE50222 | GEO
Project description:Altered DNA methylation patterns in CD4+ T-cells indicate the importance of epigenetic mechanisms in inflammatory diseases. However, the identification of these alterations is complicated by the heterogeneity of most inflammatory diseases. Seasonal allergic rhinitis (SAR) is an optimal disease model for the study of DNA methylation because of its well-defined phenotype and etiology. We generated genome-wide DNA methylation (Npatients = 8, Ncontrols = 8) and gene expression (Npatients= 9, Ncontrols = 10) profiles of CD4+ T-cells from SAR patients and healthy controls using Illumina’s HumanMethylation450 and HT-12 microarrays, respectively. DNA methylation profiles clearly and robustly distinguished SAR patients from controls, during and outside the pollen season. Moreover, we found that this methylation signature correlated with symptom severity. In agreement with previously published studies, gene expression profiles of the same samples failed to separate patients and controls. Separation by methylation (Npatients = 12, Ncontrols = 12), but not by gene expression (Npatients = 21, Ncontrols = 21) was also observed in an in vitro model system in which purified PBMCs from patients and healthy controls were challenged with allergen. We observed changes in the proportions of memory T-cell populations between patients (Npatients = 35) and controls (Ncontrols= 9), which could explain the observed difference in DNA methylation. Our data highlight the potential of epigenomics in the stratification of immune disease and represents the first successful molecular classification of SAR using CD4+ T cells.
2013-12-01 | GSE50101 | GEO
Project description:Gene methylation profiling of immortalized human mesenchymal stem cells comparing HPV E6/E7-transfected MSCs cells with human telomerase reverse transcriptase (hTERT)- and HPV E6/E7-transfected MSCs. hTERT may increase gene methylation in MSCs. Goal was to determine the effects of different transfected genes on global gene methylation in MSCs.
2011-08-25 | GSE23936 | GEO