Gene expression from the whole blood of rheumatoid arthritis patients and normal controls.
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE68689 | GEO | 2018/05/01
REPOSITORIES: GEO
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Project description:Genome wide DNA methylation profiling of monocytes from healthy donors and rheumatoid arthritis patients. The Illumina Infinium MethylationEPIC Beadchip was used to obtain DNA methylation profiles across approximately 850,000 CpGs in CD11b+CD33+CD15neg monocytes isolated from PBMCs of 17 healthy donors and 47 rheumatoid arthritis patients with different disease activity scores (DAS28).
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Project description:The objective of this study was to identify response-specific gene expression fluctuations in methotrexate /abatacept (Aba) treated rheumatoid arthritis patients : responders (R) VS no-responders (NR). Nineteen RA patients were received Abatacept. The drug efficacy was evaluated with the DAS28 score after 6 months of treatment according to the EULAR response criteria. Among 19 Aba RA patients, 14 were R and 5 were classified as NR. A blood sample was carried out in patients both at baseline (just before the first injection of ABA) and at 6 months in PaxGene tubes.
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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.
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Project description:Rheumatoid arthritis (RA) is a heterogeneous disease. We used cDNA microarray technology to subclassify RA patients and disclose disease pathways in rheumatoid synovium. Hierarchical clustering of gene expression data identified two main groups of tissues (RA-I and RA-II). A total of 121 genes were significantly higher expressed in the RA-I tissues, whereas 39 genes were overexpressed in the RA-II tissues. Among the 121 genes overexpressed in RA-I tissues, a relative majority of nine genes are located on chromosome 6p21.3. An interpretation of biological processes that take place revealed that the gene expression profile in RA-I tissues is indicative for an adaptive immune response. The RA-II group showed expression of genes suggestive for fibroblast dedifferentiation. Within the RA-I group, two subgroups could be distinguished; the RA-Ia group showed predominantly immune-related gene activity, while the RA-Ib group showed an additional higher activity of genes indicative for the classical pathway of complement activation. All tissues except the RA-Ia subgroup showed elevated expression of genes involved in tissue remodeling. These results confirm the heterogeneous nature of RA and suggest the existence of distinct pathogenic mechanisms that contribute to RA. The differences in expression profiles provide opportunities to stratify patients based on molecular criteria. An all pairs experiment design type is where all labeled extracts are compared to every other labeled extract. Keywords: all_pairs
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Project description:Rheumatoid arthritis (RA) is a heterogeneous disease. We used cDNA microarray technology to subclassify RA patients and disclose disease pathways in rheumatoid synovium. Hierarchical clustering of gene expression data identified two main groups of tissues (RA-I and RA-II). A total of 121 genes were significantly higher expressed in the RA-I tissues, whereas 39 genes were overexpressed in the RA-II tissues. Among the 121 genes overexpressed in RA-I tissues, a relative majority of nine genes are located on chromosome 6p21.3. An interpretation of biological processes that take place revealed that the gene expression profile in RA-I tissues is indicative for an adaptive immune response. The RA-II group showed expression of genes suggestive for fibroblast dedifferentiation. Within the RA-I group, two subgroups could be distinguished; the RA-Ia group showed predominantly immune-related gene activity, while the RA-Ib group showed an additional higher activity of genes indicative for the classical pathway of complement activation. All tissues except the RA-Ia subgroup showed elevated expression of genes involved in tissue remodeling. These results confirm the heterogeneous nature of RA and suggest the existence of distinct pathogenic mechanisms that contribute to RA. The differences in expression profiles provide opportunities to stratify patients based on molecular criteria. An all pairs experiment design type is where all labeled extracts are compared to every other labeled extract. Using regression correlation
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