Independent validation of human CD4+ T-cell transcriptome in early arthritis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE80513 | GEO | 2018/04/03
REPOSITORIES: GEO
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Project description:An exploration of the peripheral blood CD4+ T-cell transcriptome of early arthritis clinic attendees, seeking novel diagnostic tools and pathophysiological insights.
2012-03-03 | GSE20098 | GEO
Project description:An exploration of the peripheral blood CD4+ T-cell transcriptome of early arthritis clinic attendees, seeking novel diagnostic tools and pathophysiological insights. Ex-vivo CD4+ T-cell RNA was obtained following first early arthritis clinic attendance from 173 patients. Four diagnostic categories were confirmed at median 28 months follow-up. Outcome categories are ACPA- RA (A; n=31), ACPA+ RA (B; n=41), Non-RA Inflammatory arthritis (C; n=56), and Non-RA/Non-Inflammatory arthritis (D; n=45). In order to derive and validate a diagnostic gene signature, samples were split into Training set (where patients could be diagnosed at presentation; n=111) and validation set of undifferentiated arthritis (UA; n=62) patients, in whom diagnosis could only be confirmed after the follow-up period. Arrays were processed in two phases (phases 1 and 2). Phase 1 was split into 4 labelling batches, Phase 2 was split into 2 labelling batches. Batch effects were controlled for using this information using the empirical Bayes approach of Johnson et al. (2007). The supplementary file 'GSE20098_non-normalized.txt' contains non-normalized data for Samples GSM502124-GSM502280 and GSM506251-GSM506266.
2012-03-03 | E-GEOD-20098 | biostudies-arrayexpress
Project description:242 patients recruited from an early arthritis clinic donated RNA and DNA from freshly isolated and purified peripheral blood CD19+ B cells. Global gene expression measurement was carried out using Illumina BeadChip HT12v4 microarrays. Objectives included the identification of B cell transcripts differentially expressed between disease phenotypes, where all patients were naive to immunomodulatory therapy. In addition an eQTL analysis was carried out with reference to known genotype data for this cohort of patients
2018-04-18 | GSE100648 | GEO
Project description:With a focus on rheumatoid arthritis (RA), we sought new insight into genetic mechanisms of adaptive immune dysregulation to help prioritise molecular pathways for targeting in this and related immune pathologies. Whole genome methylation data from isolated CD4+ T cells of >100 genotyped and phenotyped inflammatory arthritis patients, all of whom were naïve to immunomodulatory treatments, were obtained. Analysis integrated these comprehensive data with GWAS findings across IMDs and other publically available resources.
2019-12-17 | GSE137593 | GEO
Project description:The study presents: - an optimized synovium dissociation protocol for single cell RNA-sequencing studies of the human synovium. The protocol enables the isolation of high yield of viable synovial cells from prospectively collected fresh synovial biopsies from patients with inflammatory arthritis with a minimal sample droupout. The protocol is derived from the method for dissociation of cryopreserved synovia published by Donlin and colleagues (Arthritis Res. Ther. 2019). - a reference single-cell atlas of fresh human synovium in inflammatory arthritis, comprising more than 100´000 unsorted synovial scRNA-seq profiles from 27 freshly dissociated synovia of patients with different types of inflammatory arthritis. The synovial cells segregate into ten lymphoid, 14 myeloid and 17 stromal synovial cell populations and subpopulations, including synovial neutrophils, representing broadly representing the cellular heterogeneity and composition of the human synovium in inflammatory arthritis.
2024-04-21 | E-MTAB-11791 | biostudies-arrayexpress
Project description:Juvenile idiopathic arthritis (JIA) is the most common chronic childhood rheumatic disease in the Western world. To identify novel JIA predisposing loci, a genome-wide association study (GWAS) in 814 Caucasian JIA cases and 3058 Caucasian controls was completed. After adjusting for the most significant HLA associations, the strongest novel associations included rs6479891 (10q21, odds ratio (OR)=1.59, P=1.3x10-8) and rs10761747 (OR=1.34, P=4.0x10-5) within JMJD1C; rs12719740 (15q26, OR=1.47, P=3.3x10-7) near FAM169B; rs4688011 (3q13, OR=1.33, P=1.1x10-4) within C3orf1 and rs4254850 (4q31, OR=0.85, P=7.8x10-3) near IL15. Eleven SNPs were genotyped in Caucasian replication cohorts (1744 cases, 7010 controls) and meta-analysis continued to provide evidence for association with three of the SNPs (rs6479891, P=4.3x10-5; rs12719740, P=5.2x10-4; rs4688011, P=3.6x10-7). Analysis of expression data from 68 JIA cases and 23 controls overlapping in the GWAS cohort1 and published lymphoblastoid cell lines (LCL)2 showed cis eQTL associations for JMJD1C SNPs (P=0.01 and P=1.6x10-6, respectively), and the C3orf1 SNP (P=5.7x10-6). Peripheral blood samples were obtained from 23 healthy children and 68 children with JIA. RNA was purified from Ficoll-isolated mononuclear cells, fluorescently labeled and then hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were imported using Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization. eQTL analysis were performed using genomewide association data.
2012-03-23 | E-GEOD-26554 | biostudies-arrayexpress
Project description:Rheumatoid arthritis (RA) is an autoimmune disease that causes chronic inflammation of the joints involved with genetic and epigenetic aberrant. Recent evidence found more and more importance of the epigenetic contribution, especially the DNA methylation, to the pathogenesis of rheumatoid arthritis. To understand the extent and nature of dysregulated DNA methylation in rheumatoid arthritis T cells, we performed a genome-wide DNA methylation study in CD4+ T cells in 12 rheumatoid arthritis patients compared to 12 matched normal healthy controls. [Methods and Result] Cytosine methylation status was quantified with Illumina methylation 450K microarray (HM450K, 485512 CpG sites). We identified 810 hypomethylated and 392 hypermethylated CG sites in RA CD4+ T cells compared to normal controls, representing 383 and 785 genes hypermethylated and hypomethylated in RA patients (P<3.4*10-7). Cluster analysis based on significantly differential methylated loci showed distinct separation between RA and normal controls. Gene ontology analysis showed alternative splicing (P=1.2*10-7, FDR) and phosphoprotein (1.7*10-2, FDR) were significantly aberrant in RA patients, indicating the abnormal of transcript alternative splicing and protein modification mediated by DNA methylation might play important role in the pathogenesis of rheumatoid arthritis. What’s more, the result showed human leukocyte antigen (HLA) region was frequently hypomethylated in RA patients, including HLA-DRB6, HLA-DQA1 and HLA-E, however, HLA-DQB1 showed different methylation profiles with significant hypermethylation in CpG island region and hypomethylation in CpG shelf region. Outsite of the MHC region, the most hypermethylated genes in RA included HDAC4, NXN, TBCD and TMEM61 while the most significant hypomethylated genes included ITIH3, TCN2, PRDM16, SLC1A5 and GALNT9. [Conclusion] Genome-wide DNA methylation patterns revealed significant DNA methylation change in CD4+ T cells from patients with rheumatoid arthritis. 12 rheumatoid arthritis and 12 matched health individuals
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Project description:RNAseq of CD4 cells from 24 female RA patients activated with aCD3 for 48 hours. Patients were collected crossectionally from the Rheumatology clinic during 2018. Age md 47, range 24-67 years, Disease duration md 5.5, range 1-30 years.
2022-11-29 | GSE190349 | GEO
Project description:Although activated CD4+ T cell-driven overproduction of cytokines, especially TNF and IL1, is generally regarded as the major factor in the development of rheumatoid arthritis (RA), little is known about the precise role of CD4+ T cells in the initiation and progression of this disease. In this study, this issue was addressed using a time-course microarray analysis in a mouse model of RA, Il1rn deficient mice.No obvious cytokine gene expression changes reflecting T cell activation was observed in CD4+ T cells in the Il1rn deficient mice during the course of spontaneous arthritis. On the contrast, majority of dysregulated genes were those predominantly expressed in myeloid lineage cells, suggesting T cell reprogramming involvement in arthritis development. Distinct gene expression patterns were identified for different stages of disease, including downregulated expression of immunoglobulin heavy chain constant region genes and increased expression of inflammatory genes in the early phase, and downregulation of MHC class II genes in the late phase. The common changes occurred in both early and late phases included upregulation of Arl2bp and Mfap1, which are involved in the regulation of cytoskeletal dynamics. Keywords: Time course
2008-05-01 | GSE7705 | GEO
Project description:RNAseq of CD4 cells from 60 female RA patients activated with aCD3 for 2 hours. Patients were collected crossectionally from the Rheumatology clinic during 2019-2020. Age md 64, range 23-76 years, Disease duration md 10, range 1-45 years.
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