{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"omics_type":["Metabolomics","Unknown","Transcriptomics","Genomics","Proteomics"],"submitter":["Susan Wang"],"study_type":["methylation profiling by array"],"organism":["Homo sapiens"],"species":["Homo sapiens"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15620"],"description":["In this study, genome-wide DNA methylation profiling was performed on synovial biopsies from patients with established RA before and after treatment with the TNF inhibitor etanercept. The intent was to determine whether therapeutic modulation of inflammation is associated with changes in DNA methylation signatures in disease-relevant tissue and whether baseline methylation patterns could provide insight into inter-patient variability in treatment response.  By generating these data, we aim to contribute to understanding the role of epigenetic regulation in RA pathogenesis and treatment response, to facilitate identification of biomarkers predictive of therapeutic efficacy, and to provide a resource for investigating gene–environment–epigenome interactions in inflammatory arthritis."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Sample Collection - Synovial biopsies were collected from patients enrolled in the STRAP RCT (REC 14/WA/1209), a phase III, multicentre, open-label, randomised trial in established RA. Biopsies were obtained from joints with active synovitis confirmed by ultrasound. Samples were preserved in Allprotect Tissue Reagent (Qiagen, UK) and stored at −80°C prior to nucleic acid extraction. Whole blood samples were also collected at baseline and stored under identical conditions.","Labeling - Bisulfite conversion of 250 ng genomic DNA was performed using the EZ-96 DNA Methylation Kit (Zymo Research, USA) according to the manufacturer’s instructions, converting unmethylated cytosines to uracil. This step enabled downstream methylation analysis on the Infinium MethylationEPIC BeadChip.","Nucleic Acid Extraction - DNA and RNA were extracted using the AllPrep RNA/DNA/Protein kit (Qiagen, UK). Synovial tissue was homogenised in RLT/βME buffer using a TissueLyser (2 min, 20 Hz). DNA was purified on AllPrep DNA spin columns, washed (AW1/AW2), and eluted with heated Buffer EB. Where additional DNA was required, residual tissue underwent extraction with the QIAamp DNA Mini kit (Qiagen, UK).","Scaning - Arrays were processed using the Illumina iScan system (Illumina, UK). Fluorescence-based detection captured methylated versus unmethylated signal intensities. Raw IDAT files were generated and securely transferred to the QMUL EMR server.","Hybridization - Following bisulfite conversion, DNA was amplified, fragmented, and hybridised to the Infinium MethylationEPIC BeadChip (Illumina, UK) according to the Infinium HD Assay Methylation Protocol (Document 15019519 v01, Nov 2015). Eight samples were processed per array, with balanced randomisation across array positions to minimise positional bias. Hybridisation occurred through locus-specific probe capture of methylated and unmethylated CpG sites."],"figure_sub":["MIAME Score","Raw Data","Organization","Assays and Data","MAGE-TAB Files","Array Designs"],"pubmed_authors":["Susan Wang"],"additional_accession":[]},"is_claimable":false,"name":"DNA methylation of synovial tissue from establised Rheumatoid Arthritis patients before and after Etanercept Treatment","description":"In this study, genome-wide DNA methylation profiling was performed on synovial biopsies from patients with established RA before and after treatment with the TNF inhibitor etanercept. The intent was to determine whether therapeutic modulation of inflammation is associated with changes in DNA methylation signatures in disease-relevant tissue and whether baseline methylation patterns could provide insight into inter-patient variability in treatment response.  By generating these data, we aim to contribute to understanding the role of epigenetic regulation in RA pathogenesis and treatment response, to facilitate identification of biomarkers predictive of therapeutic efficacy, and to provide a resource for investigating gene–environment–epigenome interactions in inflammatory arthritis.","dates":{"release":"2026-06-26T00:00:00Z","modification":"2026-06-26T15:17:49.78Z","creation":"2026-05-20T11:02:47.072Z"},"accession":"E-MTAB-15620","cross_references":{"EFO":["EFO_0002944","EFO_0003814","EFO_0003813","EFO_0002759","EFO_0005518","EFO_0003815"]}}