Dataset Information

Synovial fluid proteome in rheumatoid arthritis

ABSTRACT: Rheumatoid arthritis (RA) is a chronic autoinflammatory disorder that affects small joints. Despite intense efforts, there isno definitive marker yet for early diagnosis RA and for monitoring the progression of this disease. We sought to catalog the proteins present in the synovial fluid of patients with rheumatoid arthritis. To identify lower abundance proteins, we undertook two approaches – we depleted the abundant proteins using a multiple affinity removal system (MARS14) column and we enriched glycoproteins using a lectin affinity column. The peptides were analyzed by LC-MS/MS on a high resolution Fourier transform mass spectrometer.

INSTRUMENT(S): LTQ Orbitrap XL ETD

ORGANISM(S): Homo Sapiens (human)

DISEASE(S): Rheumatoid Arthritis

SUBMITTER: Akhilesh Pandey

LAB HEAD: Akhilesh Pandey

PROVIDER: PXD000740 | Pride | 2016-06-13

REPOSITORIES: Pride

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Synovial fluid proteome in rheumatoid arthritis.

Bhattacharjee Mitali M Balakrishnan Lavanya L Renuse Santosh S Advani Jayshree J Goel Renu R Sathe Gajanan G Keshava Prasad T S TS Nair Bipin B Jois Ramesh R Shankar Subramanian S Pandey Akhilesh A

Clinical proteomics 20160605

<h4>Background</h4>Rheumatoid arthritis (RA) is a chronic autoinflammatory disorder that affects small joints. Despite intense efforts, there are currently no definitive markers for early diagnosis of RA and for monitoring the progression of this disease, though some of the markers like anti CCP antibodies and anti vimentin antibodies are promising. We sought to catalogue the proteins present in the synovial fluid of patients with RA. It was done with the aim of identifying newer biomarkers, if ...[more]

PMID: 27274716

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Project description:Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000550. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Rheumatoid arthritis (RA) is an autoimmune disease that causes chronic inflammation of the joints involved with genetic and epigenetic aberrant. Recent evidence found more and more importance of the epigenetic contribution, especially the DNA methylation, to the pathogenesis of rheumatoid arthritis. To understand the extent and nature of dysregulated DNA methylation in rheumatoid arthritis T cells, we performed a genome-wide DNA methylation study in CD4+ T cells in 12 rheumatoid arthritis patients compared to 12 matched normal healthy controls. [Methods and Result] Cytosine methylation status was quantified with Illumina methylation 450K microarray (HM450K, 485512 CpG sites). We identified 810 hypomethylated and 392 hypermethylated CG sites in RA CD4+ T cells compared to normal controls, representing 383 and 785 genes hypermethylated and hypomethylated in RA patients (P<3.4*10-7). Cluster analysis based on significantly differential methylated loci showed distinct separation between RA and normal controls. Gene ontology analysis showed alternative splicing (P=1.2*10-7, FDR) and phosphoprotein (1.7*10-2, FDR) were significantly aberrant in RA patients, indicating the abnormal of transcript alternative splicing and protein modification mediated by DNA methylation might play important role in the pathogenesis of rheumatoid arthritis. What’s more, the result showed human leukocyte antigen (HLA) region was frequently hypomethylated in RA patients, including HLA-DRB6, HLA-DQA1 and HLA-E, however, HLA-DQB1 showed different methylation profiles with significant hypermethylation in CpG island region and hypomethylation in CpG shelf region. Outsite of the MHC region, the most hypermethylated genes in RA included HDAC4, NXN, TBCD and TMEM61 while the most significant hypomethylated genes included ITIH3, TCN2, PRDM16, SLC1A5 and GALNT9. [Conclusion] Genome-wide DNA methylation patterns revealed significant DNA methylation change in CD4+ T cells from patients with rheumatoid arthritis. 12 rheumatoid arthritis and 12 matched health individuals

Project description:Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis - Age Dependant This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000549. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

			Action	DRS
	RA_SCX_CID-LTQ_1.raw	Raw
	RA_SCX_CID-LTQ_10.raw	Raw
	RA_SCX_CID-LTQ_11.raw	Raw
	RA_SCX_CID-LTQ_12.raw	Raw
	RA_SCX_CID-LTQ_13.raw	Raw