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OP0309 Identification of A Predictive Microrna Signature of Progression from Pre-RA Systemic Autoimmunity to Development of RA Using Matched Serum Samples
  1. L. Ouboussad1,2,
  2. L. Hunt1,2,
  3. E.M. Hensor1,2,
  4. J. Nam1,2,
  5. C. Wong1,2,
  6. P. Emery1,2,
  7. M. McDermott1,2,
  8. M. Buch1,2
  1. 1Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds
  2. 2NIHR-Leeds Musculoskeletal Biomedical Research Unit (NIHR-LMBRU), Chapel Allerton Hospital, Leeds, United Kingdom


Background Recent EULAR [1] recommendations for terminology of rheumatoid arthritis (RA) at-risk groups recognise those with systemic autoimmunity associated with pre-clinical RA, characterised by the presence of ACPA. Identification of predictors of progression from this pre-RA state to the RA syndrome would have clinical utility. We have reported on a number of potential clinical and imaging markers [2]. MicroRNA (miRNA) are highly conserved small, non-coding RNA that serve as transcriptional negative regulators; with growing evidence that they contribute to the pathogenesis of human diseases, including RA.

Objectives Our study aimed to identify serum miRNA that predict progression in CCP+ individuals with no synovitis to RA using global profiling.

Methods Matched serum samples were used from the following groups: (i) 12 subjects presenting with CCP positivity only (CCP+) (with no synovitis, confirmed on ultrasound) that were followed to the point of development of RA (Very Early RA, VERA) (ii) 9 subjects with Early RA (ERA), symptom history of ≤12 months (iii) 12 healthy controls (control group, HC). TaqMan low density MicroRNA Array Cards was applied to examine the expression of 754 human miRNAs and controls in the 4 cohorts: miRNA with a 4-fold change in expression (down or up-regulation) were selected as candidate biomarkers for RA progression. Heat maps were plotted using unsupervised hierarchical clustering analysis, permitting separation of cohorts into groups according to miRNA expression levels. A validation analysis of the miRNAs of interest was conducted on a further 12 HC, 12 CCP+ individuals who did not progress and 12 CCP+ individuals that did progress, using custom miRNA array cards.

Results After adequate normalisation and data analysis, serum miRNA profiling identified 22 candidate miRNA that were dysregulated when comparing their relative expression from one of the studied cohorts to another. We identified a dysregulated four-miRNA signature between the matched CCP+ to VERA cohorts. In addition, hierarchical clustering revealed a clear differential miRNA expression between the cohorts (Figure 1). The validation study consists of evaluating expression levels of the 22 miRNA and also 9 miRNA that have been previously implicated in RA (such as miR-155 and miR-146a) using custom array cards in order to confirm their involvement in RA pathogenesis; the results of which are awaited.

Conclusions Using a comprehensive MicroRNA array approach this study is a first to use matched pre-RA and VERA serum samples to identify dysregulated miRNA expression as biomarkers predictive of progression along this transition phase. We have identified 4 miRNAs in particular that could be potential diagnostic markers of RA, which we are about to validate further.


  1. DM Gerlag et al, Ann Rheum Dis, 2012

  2. C Rakieh et al, Ann Rheum Dis, 2014

Disclosure of Interest None declared

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