F093633c-22e6-471a-896d-e22c6779e401 - samples
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ABSTRACT:
PROVIDER: EGAD00001009775 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Single nucleotide variants (SNVs) associated with Parkinson’s disease (PD) have been investigated mainly through genome-wide association studies. Here, we conducted whole genome sequencing of 410 PD patients and 200 healthy individuals of the Korean population and identified disease-related SNVs.
| EGAS00001006811 | EGA
Project description:Background: Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that immune cell-types, and especially CD4+ T-cells, play an important role in asthma pathogenesis. Despite this, CD4+ T-cells are under-represented in asthma transcriptome studies. Objective: To identify differences in gene expression between asthmatics and healthy controls in CD4+ T-cells. Methods: CD4+ T-cells were isolated within 2 hours from collection from peripheral blood from people with well-established asthma (n=33) and healthy controls (n=12). 3'-RNA-Seq was used to generate gene expression data. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules). The asthma-associated modules were tested for enrichment of GWAS-identified asthma genes and gene ontology (GO) biological processes. For the genes in the asthma-associated modules, integration of eQTL and GWAS summary statistics (colocalisation), and protein-protein interaction (PPI) data was used to identify master regulators. Results: After quality control, 43 samples were available for the analysis. WGCNA identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Colocalisation analysis of eQTL and GWAS summary statistics, together with PPI data, identified PTPRC as a master regulator of asthma gene-expression profiles in CD4+ T-cells. Conclusion: Unstimulated CD4+ T-cells from peripheral blood from asthmatics have different expression profiles, compared to healthy controls, for sets of genes involved in immune response to viral infections and antigen processing/presentation . Integration of genetic and protein-protein interaction data identified PTPRC as a master regulator of genes in asthma.
2023-12-27 | GSE217904 | GEO
Project description:More than 200 asthma-associated genetic variants have been identified in genome-wide association studies (GWASs). Expression quantitative trait loci (eQTL) data resources can help identify causal genes of the GWAS signals, but it can be difficult to find an eQTL that reflects the disease state because most eQTL data are obtained from normal healthy subjects. We performed a blood eQTL analysis using transcriptomic and genotypic data from 436 Korean asthma patients. To identify asthma-related genes, we carried out colocalization and Summary-based Mendelian Randomization (SMR) analysis using the results of asthma GWASs and eQTL data. In addition, we compared the results of disease eQTL data and asthma-related genes with two normal blood eQTL data from Genotype-Tissue Expression (GTEx) project and a Japanese study. We identified 342,054 cis-eQTL and 2,931 eGenes from asthmatic eQTL analysis. We compared the disease eQTL results with GTEx and a Japanese study and found that 63.2 % of the 2,931 eGenes overlapped with the GTEx eGenes and 38.5 % with the Japanese eGenes. Following the integrated analysis of the asthmatic eQTL data with asthma GWASs, using colocalization and SMR methods, we identified 13 asthma-related genes specific to the Korean asthmatic eQTL data. We provided Korean asthmatic cis-eQTL data and identified asthma-related genes by integrating them with GWAS data. In addition, we suggested these asthma-related genes as therapeutic targets for asthma. We envisage that our findings will contribute to understanding the etiological mechanisms of asthma and provide novel therapeutic targets.
2023-03-08 | GSE226825 | GEO
Project description:To gain insights into the in vivo function of miRNAs in the context of periodontitis, we examined the occurrence of miRNAs in healthy and diseased gingival tissues and validated their in silico-predicted targets through mRNA profiling using whole-genome microarrays in the same specimens. Eighty-six individuals with periodontitis contributed 198 gingival papillae: 158 'diseased' (bleeding-on-probing, PD > 4 mm, and AL M-bM-^IM-% 3 mm) and 40 'healthy' (no bleeding, PD M-bM-^IM-$ 4 mm, and AL M-bM-^IM-$ 2 mm). Expression of 1,205 miRNAs was assessed by microarrays, followed by selected confirmation by quantitative RT-PCR. Predicted miRNA targets were identified and tested for enrichment by Gene Set Enrichment Analysis (GSEA). Enriched gene sets were grouped in functional categories by DAVID and Ingenuity Pathway Analysis. One hundred fifty-nine miRNAs were significantly differentially expressed between healthy and diseased gingiva. Four miRNAs (hsa-miR-451, hsa-miR-223, hsa-miR-486-5p, hsa-miR-3917) were significantly overexpressed, and 7 (hsa-miR-1246, hsa-miR-1260, hsa-miR-141, hsa-miR-1260b, hsa-miR-203, hsa-miR-210, hsa-miR-205*) were underexpressed by > 2-fold in diseased vs. healthy gingiva. GSEA and additional filtering identified 60 enriched miRNA gene sets with target genes involved in immune/inflammatory responses and tissue homeostasis. This is the first study that concurrently examined miRNA and mRNA expression in gingival tissues and will inform mechanistic experimentation to dissect the role of miRNAs in periodontal tissue homeostasis and pathology. The dataset comprise 200 gingival tissue samples from 86 patients with periodontitis. All samples are included in this series, but 2 where not included in the study, as they did not pass our QC. Each patient has one or more healthy and disease sample and samples can be of chronic or aggressive periodontitis type.
2014-02-05 | E-GEOD-54710 | biostudies-arrayexpress
Project description:Summary statistics for a multi-cohort epigenome-wide association study. This includes summary statistics (effect-size, standard error, p-value) for 470,000 methylation markers.
| EGAD00010001029 | EGA
Project description:Summary statistics from Haemgen RBC GWAS
| EGAD00010000300 | EGA
Project description:Summary statistics from meta-analysis for BP phenotypes
| EGAD00010000819 | EGA
Project description:Summary statistics from GWAS meta-analysis of cervical cancer
| EGAD00001004361 | EGA
Project description:In these studies, we used splice variant-specific microarrays manufactured by the ExonHit company ( www.exonhit.com) on the Affymetrix platform. The goal was to identify splice isoforms whose expression is altered in whole blood of early-stage ParkinsonM-bM-^@M-^Ys disease patients compared to healthy and neurodegenerative disease controls. The study included 19 cases of ParkinsonM-bM-^@M-^Ys disease (PD) samples, 4 of multiple system atrophy (MSA), 4 progressive supranuclear palsy (PSP) and 10 healthy controls. Thirteen splice variants were confirmed in quantitative polymerase chain reactions and used to classify blinded samples from ParkinsonM-bM-^@M-^Ys disease patients and controls with 90% accuracy and 94% sensitivity. In these studies, we used splice variant-specific microarrays manufactured by the ExonHit company ( www.exonhit.com) on the Affymetrix platform. The study included 19 cases of ParkinsonM-bM-^@M-^Ys disease (PD) samples and 20 control samples including 4 cases of multiple system atrophy (MSA), 4 progressive supranuclear palsy (PSP) and 12 healthy controls. Splice isoforms differentially expressed in PD vs any other control group were identified and validated using real-time quantitative PCR on two independent sets of 33 coded and 53 blinded samples.
2012-12-01 | E-GEOD-34287 | biostudies-arrayexpress
Project description:Genetics of thinness compared to obesity - summary statistics
| EGAD00010001624 | EGA