Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA211855 | ENA |
REPOSITORIES: ENA
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Project description:Synovial biopsies of Rheumatoid Arthritis patients with active disease were obtained prior to anti-TNF therapy. Clinical response to anti-TNF treatment was measured 20 weeks later using the EULAR response criteria. Gene expression profiles of patients responding to anti-TNF therapy were compared to non-responders and several genes were found to be differentially expressed between both groups of Rheumatoid Arthritis patients.
2019-07-26 | GSE47726 | GEO
Project description:This experiment investigates differences in expression of circulating miRNAs between responders and non-responders to treatment of rheumatoid arthritis with allogeneic adipose-derived mesenchymal stem cells. The ability to stratify patients based on their response to treatment has been transformational in a number of disease areas, and it is anticipated that this will also be the case for cell-based therapies. In line with this, the goal of this study was to identify miRNA biomarkers that could be used to predict response to treatment of rheumatoid arthritis with allogeneic adipose-derived mesenchymal stem cells. Promising candidates from the microarrays were validated with quantitative reverse transcriptase PCR.
2017-01-09 | E-MTAB-4988 | biostudies-arrayexpress
Project description:Objective: Glucocorticoids (GC) have been a cornerstone of Rheumatoid arthritis (RA)-therapy for the last decades. However, about a third of RA-patients do not respond adequately. As monocytes and T-cells play an important role in RA-pathogenesis, the differential gene expression of these cells before pulse therapy with methylprednisolone was evaluated in order to find predictors for clinical response to GC. Methods: CD14-positive and CD4-positive cells were isolated by MACS sorting from five GC-Responders meeting the European League against Rheumatism (EULAR) response criteria and five Non-Responders. The clinical response was measured by disease activity score (DAS28) at the end of pulse therapy (3x 1000mg Methylprednisolone) at day 5. Cellular RNA was hybridized to Agilent 4x44K microarray chips and differentially expressed genes were calculated by MAANOVA. False discovery rate (FDR) was used as multiple testing correction. Selected genes were verified by quantitative real-time PCR (qPCR). Results: Eight genes were differentially regulated in CD14-cells and 4 genes in CD4-T-cells of GC-Responders compared to Non-Responders. Up-regulation of ERAP2 in monocytes and CD4-cells and LST1 and FAM26F in CD4-Tcells of GC-Responders was verified by qPCR and correlated with DAS28 at day 5 and (for LST1 and FAM26F) with smoking. Conclusion: As ERAP2 and LST1 are implicated in autoimmune disease, their increased expression in GC-Responders before GC-therapy may constitute not only a new tool for prediction of the clinical response to GC in RA, but also warrants further investigation to elucidate their role in the inflammatory process of RA.
2017-11-11 | GSE48823 | GEO
Project description:Synovial biopsies of Rheumatoid Arthritis patients were obtained at week 20 of anti-TNF therapy. The clinical response to therapy was determined comparing the DAS28 at this time point with the baseline DAS28, using the EULAR response criteria. Gene expression profiles of patients responding to anti-TNF therapy were compared to non-responders and different genes, pathways and deconvoluted cell types were found to be differential between both groups of rheumatoid arthritis patients.
2020-06-30 | GSE140036 | GEO
Project description:Oligo microarrays were used to access the transcription profiling of the rheumatoid arthritis patients under two different therapeutic approaches, aiming to evaluate if the cDNA microarray study is able to differentiate responders and non-responders to therapies. In the first experiment (MTX therapy) we analyzed 25 patients from which 8 were classified as MTX responders and 17 MTX non-responders. In the second experiment from the 17 MTX non-responder patients, 8 were non-responders and 9 were responders to additional anti-TNF therapy.
2011-12-31 | E-MEXP-3390 | biostudies-arrayexpress
Project description:Background: Pathogenesis of Rheumatoid arthritis (RA) is driven by monocytes and T-cells, which are heavily influenced by Glucocorticoids (GC). Although a cornerstone of RA-therapy, one third of RA-patients do not respond adequately to GC and the mechanisms of resistance have not yet been clarified. Objective: To find differences in GC-working mechanism in RA-patients responding versus GC-resistant patients by gene expression profiling. Methods: Patients were treated with 3x 1000mg Methylprednisolone. Before start (T0) and 24 hours (T24) after first treatment, CD14+ and CD4+cells were MACS-isolated At day 5, response was determined using the DAS28. Labeled cRNA from 5 GC-Responders and 5 Non-Responders was hybridized to Agilent 4x44K microarray chips. Differentially expressed genes between T0 and T24 were identified using MAANOVA, FWER (family wise error rate) correction and a >1.5 ratio cut-off. Gene Ontology was used for pathway analysis; Transcription-factors were identified via TRANSFAC. Selected genes were validated by qPCR. Results: After 24 hours, 48 genes were exclusively changed in GC-Responders’ monocytes (CD4+cells: 19), 253 exclusively in Non-Responders (CD4+cells: 104) and 104 genes in both (CD4+: 18). In both cell-types a more pronounced down-regulation of interferon related genes was seen in Non-Responders, which was validated by qPCR in CD4+cells. At T24 higher expression of ERAP2 and FAM26F was seen in GC-Responders compared to Non-Responders. Several relevant transcription-factors were identified, among which LEF1in both cell types. Conclusion: GC treatment resulted in stronger suppression of the interferon signature in Non-Responders. This might be disease-specific, but should prompt further investigation of GC-mechanism in several auto-immune diseases known for an interferon signature.
2020-01-30 | GSE53221 | GEO
Project description:The whole blood was collected pre-treatment from rheumatoid arthritis patients starting the anti_TNF therapy. All patients were naïve to anti_TNFs. The disease activity was measured using the DAS28 score at the pre-treatment visit1 (DAS28_v1) and 14 weeks after treatment visit3 (DAS28_v3). The response to the therapy was evaluated using the EULAR [European League Against Rheumatism] definition of the response. The objective of the data analysis was to identify gene expression coorelating with response as well as to identify genes that differentiate responders versus non-responders pre-treatment. The results of this investigation identified 8 trainscripts that predict responders vs. non-responders with 89% accuracy. Experiment Overall Design: Patients' response to anti-TNF was assessed using EULAR score and patients were classified as responders, moderate responders and non-responders. Genes correlating with the response status have been identified.
2009-09-18 | E-GEOD-15258 | biostudies-arrayexpress
Project description:Objective: We performed whole-blood transcriptomic profiling for patients with rheumatoid arthritis (RA) who received rituximab (RTX). We aimed to identify a molecular signature that could predict the clinical response to RTX and transcriptomic changes after RTX therapy. Methods: We performed a microarray assay of the whole human genome with RNA from a peripheral blood sample taken before the first RTX cycle from 68 patients included in the SMART study (24 EULAR non-responders and 44 responders at week 24). The transcriptomic profile was also assessed 24 weeks after the first RTX administration
2015-01-01 | E-GEOD-54629 | biostudies-arrayexpress
Project description:The whole blood was collected pre-treatment from rheumatoid arthritis patients starting the anti_TNF therapy. All patients were naïve to anti_TNFs. The disease activity was measured using the DAS28 score at the pre-treatment visit1 (DAS28_v1) and 14 weeks after treatment visit3 (DAS28_v3). The response to the therapy was evaluated using the EULAR [European League Against Rheumatism] definition of the response. The objective of the data analysis was to identify gene expression coorelating with response as well as to identify genes that differentiate responders versus non-responders pre-treatment. The results of this investigation identified 8 trainscripts that predict responders vs. non-responders with 89% accuracy.
2009-09-14 | GSE15258 | GEO
Project description:Autoreactive CD8+ T effector (eff) cells specific to vimentin, actin cytoplasmic 1, or non-muscle myosin heavy chain 9 epitopes, evade regulatory T (Treg) cells in patients with rheumatoid arthritis undergoing worsening disease and who would become non-responders to tumor necrosis factor (TNF)-α inhibitor therapy, in contrast to autoreactive CD8+ T naïve (N) cells that are efficiently controlled by Treg cells in healthy individuals or patients who would become responders. Gene expression analysis revealed that the autoreactive CD8+ TN cell subset is comprised of a heterogeneous population of cells at various stages of development in healthy individuals or patients. Mechanistically, the production of TNF-α by CD8+ TN cells and the killing activity by CD8+ Teff cells in response to the relevant self-antigens influence the endorsement or suppression of Treg function, respectively. These data provide evidence of a previously undescribed role of such mechanisms in the progression and therapy of a prototypical human autoimmune disease, such as rheumatoid arthritis.
2018-05-01 | GSE105162 | GEO