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- Folkersen, Lasse, et al.
(författare)
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Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis : results from the COMBINE study.
- 2016
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Ingår i: Molecular Medicine. - : Springer Science and Business Media LLC. - 1076-1551 .- 1528-3658. ; 22, s. 322-328
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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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| 2. |
- Houtman, Miranda, et al.
(författare)
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T cells are influenced by a long non-coding RNA in the autoimmune associated PTPN2 locus
- 2018
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Ingår i: Journal of Autoimmunity. - : ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD. - 0896-8411 .- 1095-9157. ; 90, s. 28-38
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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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| 3. |
- Shchetynsky, Klementy
(författare)
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Genomic profiling and gene-gene interaction in rheumatoid arthritis
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Complex disease is characterized by the interplay of multiple genetic and environmental factors. Rheumatoid arthritis (RA) is a complex autoimmune disease with a pronounced genetic component, mainly due to HLA-DRB1 gene, but also a multitude of loci outside the HLA region. In this work we strive to contribute to the understanding of the functional involvement of these susceptibility loci in the pathogenesis of RA. This study is based on a large material of whole blood samples and peripheral blood mononuclear cells (PBMCs) from RA patients and matched healthy controls from Sweden. The main methods used in this work included probe-based genotyping and gene-expression assays, cell cultures, RNA-sequencing, gene-gene interaction and pathway analysis, as well as a plethora of common molecular genetics and bioinformatics methods. We investigated the role of expression of known genetic risk factors PTPN22 and PTPN2 in RA, with a special attention to the splicing profile of these genes. Our data indicates significant differences in the expression ratio of splice variants for PTPN22 in whole blood samples from RA patients and healthy controls. For PTPN2 we demonstrate a significant difference in the relative mRNA expression of' transcript TC48 in PBMCs of healthy controls and RA patients. Additionally, we identified new susceptibility SNPs in the PTPN2 locus: rs657555 and rs11080606, by addressing the interaction of PTPN2 variants with HLA-DRB1 shared-epitope (SE) alleles in autoantibody positive RA patients in two independent cohorts. In this work, we also address the functional genetic role of the members of the MAP signaling pathway upstream of p38 and JNK – crucial enzymes in RA – with a regard to splicing profile and their connection to HLA-DRB1. We found a significant statistical interaction for rs10468473 from MAP2K4 locus with SE alleles in autoantibody-positive RA. Importantly, individuals heterozygous for rs10468473 demonstrated higher expression of total MAP2K4 mRNA in blood, compared to A-allele homozygous. We also describe a novel, putatively translated RNA splice form of MAP2K4, that is differentially expressed in peripheral blood mononuclear cells from 88 RA cases and controls, and is modulated in response to TNF in Jurkat cell line. Finally, we performed an expression analysis of multiple validated RA risk loci, and pathway analysis to assess functional relationship between RA susceptibility genes and predict new potential study candidates. New candidate molecules suggested by the pathway analysis, genes ERBB2 and HSPB1, as well as HLA-DRB1, were differentially expressed between RA patients and healthy individuals in RNA-seq data. ERBB2 expression profile was similar in whole blood of both treated and untreated patients compared to healthy individuals. A similar expression profile was replicated for ERBB2 in PBMCs in an independent material. In this work, we approached the task of elucidating the functional aspects of genetic susceptibility of RA, by integrating genetic epidemiology, transcriptomics, proteomics, cellmodels, and bioinformatics. We maintain, that such integrative approach provides the rationale to prioritize genes and genetic events for further functional studies. Our findings also outline the need to consider potential clinical significance of alternative splicing in gene expression studies.
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