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Sökning: WFRF:(Shchetynsky K)

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  • Houtman, Miranda, et al. (författare)
  • T cells are influenced by a long non-coding RNA in the autoimmune associated PTPN2 locus
  • 2018
  • Ingår i: ; 90, s. 28-38
  • Tidskriftsartikel (refereegranskat)abstract
    • Non-coding SNPs in the protein tyrosine phosphatase non-receptor type 2 (PTPN2) locus have been linked with several autoimmune diseases, including rheumatoid arthritis, type I diabetes, and inflammatory bowel disease. However, the functional consequences of these SNPs are poorly characterized. Herein, we show in blood cells that SNPs in the PTPN2 locus are highly correlated with DNA methylation levels at four CpG sites downstream of PTPN2 and expression levels of the long non-coding RNA (IncRNA) LINC01882 downstream of these CpG sites. We observed that LINC01882 is mainly expressed in T cells and that anti-CD3/CD28 activated naive CD4(+) T cells downregulate the expression of LINC01882. RNA sequencing analysis of LINC01882 knockdown in Jurkat T cells, using a combination of antisense oligo-nucleotides and RNA interference, revealed the upregulation of the transcription factor ZEB1 and kinase MAP2K4, both involved in IL-2 regulation. Overall, our data suggests the involvement of LINC01882 in T cell activation and hints towards an auxiliary role of these non-coding SNPs in autoimmunity associated with the PTPN2 locus. 
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  • Folkersen, Lasse, et al. (författare)
  • Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis : results from the COMBINE study.
  • 2016
  • Ingår i: ; 22, s. 322-328
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVE: In rheumatoid arthritis (RA) several recent efforts have sought to discover means of predicting which patients would benefit from treatment. However, results have been discrepant with few successful replications. Our objective was to build a biobank with DNA, RNA and protein measurements to test the claim that the current state-of-the-art precision medicine will benefit RA patients.METHODS: We collected 451 blood samples from 61 healthy individuals and 185 RA patients initiating treatment, before treatment initiation and at a 3 month follow-up time. All samples were subjected to high-throughput RNA sequencing, DNA genotyping, extensive proteomics and flow cytometry measurements, as well as comprehensive clinical phenotyping. Literature review identified 2 proteins, 52 single-nucleotide polymorphisms (SNPs) and 72 gene-expression biomarkers that had previously been proposed as predictors of TNF inhibitor response (∆DAS28-CRP).RESULTS: From these published TNFi biomarkers we found that 2 protein, 2 SNP and 8 mRNA biomarkers could be replicated in the 59 TNF initiating patients. Combining these replicated biomarkers into a single signature we found that we could explain 51% of the variation in ∆DAS28-CRP. This corresponds to a sensitivity of 0.73 and specificity of 0.78 for the prediction of three month ∆DAS28-CRP better than -1.2.CONCLUSIONS: The COMBINE biobank is currently the largest collection of multi-omics data from RA patients with high potential for discovery and replication. Taking advantage of this we surveyed the current state-of-the-art of drug-response stratification in RA, and identified a small set of previously published biomarkers available in peripheral blood which predicts clinical response to TNF blockade in this independent cohort.
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