Human CD4+ T-cell transcriptome in early arthritis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE20098 | GEO | 2012/03/03
SECONDARY ACCESSION(S): PRJNA124345
REPOSITORIES: GEO
Similar Datasets
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:An exploration of the peripheral blood CD4+ T-cell transcriptome of early arthritis clinic attendees, (i) to provide validation of previously published observations, and (ii) to facilitate an eQTL analysis.
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2018-04-18 | GSE100648 | GEO
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Project description:Early arthritis CD4+ T cell DNA methylation profiling
| PRJNA565981 | ENA
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 B 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.
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Project description:Systemic juvenile idiopathic arthritis (SJIA) is a clinically heterogenous systemic inflammatory disorder sometimes complicated by macrophage activation syndrome (MAS) and lung disease (LD), which are thought to be driven by IFN signaling. To identify cellular sources and novel gene programs underlying SJIA pathogenesis, we performed the first in-depth single-cell RNA Sequencing (scRNA-Seq) analysis of 21 SJIA, SJIA-LD, and SJIA-MAS patient PBMCs. To define novel heterogenous patient-subtypes associated with shared transcriptional responses and associate these with clinical and diagnostic metadata, we developed the tools UDON and SATAY-UDON. These tools identify hidden patient-subtypes, including a novel Complement and IFN signaling gene program expressed by SJIA-LD monocyte populations, unravel cellular sources of IFN signaling in SJIA-MAS as CD4 T cells and monocytic cell types, and identify a previously unknown role for platelets and S100 proteins as drivers of systemic inflammation. These data provide insights into new potential therapeutic targets for SJIA complications.
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Project description:Systemic onset Juvenile Idiopathic Arthritis (SoJIA) represents up to 20% of Juvenile Idiopathic Arthritis (JIA). We have previously reported that this disease is Interleukin 1 (IL1)-mediated, and that IL-1 blockade results in clinical remission in the majority of patients. The diagnosis of SoJIA, however, still relies on clinical findings as no specific diagnostic tests are available, which leads to delays in the initiation of specific therapy. To identify specific diagnostic markers, we analyzed gene expression profiles in 19 pediatric patients with SoJIA during the systemic phase of the disease (fever and/or arthritis), 25 SoJIA patients with no systemic symptoms (arthritis only or no symptoms), 39 healthy controls, 94 pediatric patients with acute viral and bacterial infections (available under GSE6269), 38 pediatric patients with Systemic Lupus Erythematosus (SLE), and 6 patients with a second IL-1 mediated disease known as PAPA syndrome. Statistical group comparison and class prediction identified genes differentially expressed in SoJIA patients compared to healthy children. These genes, however, were also changed in patients with acute infections and SLE. By performing an analysis of significance across all diagnostic groups, we generated a list of 88 SoJIA-specific genes (p<0.01 in SoJIA and >0.5 in all other groups). A subset of 12/88 genes permitted us to accurately classify an independent test set of SoJIA patients with systemic disease. We were also able to identify a group of transcripts that changed significantly in patients undergoing IL-1 blockade. Thus, analysis of transcriptional signatures from SoJIA blood leukocytes can help distinguishing this disease from other febrile illnesses and assessing response to therapy. Availability of accurate diagnostic markers for SoJIA patients may allow prompt initiation of effective therapy and prevention of long-term disabilities. Keywords: Disease state analysis 123 RNA samples extracted from PBMCs were studied. For more details on the clinical information, please refer to the paper (PudMed ID...).
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