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Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)
  1. Gloria Lliso-Ribera1,
  2. Frances Humby2,
  3. Myles Lewis3,
  4. Alessandra Nerviani1,
  5. Daniele Mauro1,
  6. Felice Rivellese1,
  7. Stephen Kelly4,
  8. Rebecca Hands5,
  9. Fabiola Bene3,
  10. Nandhini Ramamoorthi6,
  11. Jason A Hackney7,
  12. Alberto Cauli8,
  13. Ernest H Choy9,
  14. Andrew Filer10,
  15. Peter C Taylor11,
  16. Iain McInnes12,
  17. Michael J Townsend7,
  18. Costantino Pitzalis13
  1. 1 Centre of Experimental Medicine and Rheumatology, William Harvey Research Institute, London, UK
  2. 2 Centre for Experimental Medicine and Rheumatology, Barts and the London School of Medicine and Dentistry, London, UK
  3. 3 Queen Mary University of London—Charterhouse Square Campus, London, UK
  4. 4 Rheumatology, Barts Health NHS Trust, London, UK
  5. 5 Experimental Medicine and Rheumatology, Queen Marys University of London, London, UK
  6. 6 Biomarker Discovery OMNI, Genentech Research & Early Development, San Francisco, California, USA
  7. 7 ITGR Biomarker Discovery Group, Genentech, South San Francisco, California, USA
  8. 8 Rheumatology and Rheumatology Unit, University of Cagliari and AOU University Clinic of Cagliari, Monserrato, Italy
  9. 9 Institute of Infection and Immunity, Cardiff University School of Medicine, Cardiff, UK
  10. 10 Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
  11. 11 Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
  12. 12 Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK
  13. 13 Experimental Medicine and Rheumatology, William Harvey Research Institute, London, UK
  1. Correspondence to Professor Costantino Pitzalis, Experimental Medicine and Rheumatology, William Harvey Research Institute, London EC1M 6BQ, UK; c.pitzalis{at}


Objective To establish whether synovial pathobiology improves current clinical classification and prognostic algorithms in early inflammatory arthritis and identify predictors of subsequent biological therapy requirement.

Methods 200 treatment-naïve patients with early arthritis were classified as fulfilling RA1987 American College of Rheumatology (ACR) criteria (RA1987) or as undifferentiated arthritis (UA) and patients with UA further classified into those fulfilling RA2010 ACR/European League Against Rheumatism (EULAR) criteria. Treatment requirements at 12 months (Conventional Synthetic Disease Modifying Antirheumatic Drugs (csDMARDs) vs biologics vs no-csDMARDs treatment) were determined. Synovial tissue was retrieved by minimally invasive, ultrasound-guided biopsy and underwent processing for immunohistochemical (IHC) and molecular characterisation. Samples were analysed for macrophage, plasma-cell and B-cells and T-cells markers, pathotype classification (lympho-myeloid, diffuse-myeloid or pauci-immune) by IHC and gene expression profiling by Nanostring.

Results 128/200 patients were classified as RA1987, 25 as RA2010 and 47 as UA. Patients classified as RA1987 criteria had significantly higher levels of disease activity, histological synovitis, degree of immune cell infiltration and differential upregulation of genes involved in B and T cell activation/function compared with RA2010 or UA, which shared similar clinical and pathobiological features. At 12-month follow-up, a significantly higher proportion of patients classified as lympho-myeloid pathotype required biological therapy. Performance of a clinical prediction model for biological therapy requirement was improved by the integration of synovial pathobiological markers from 78.8% to 89%–90%.

Conclusion The capacity to refine early clinical classification criteria through synovial pathobiological markers offers the potential to predict disease outcome and stratify therapeutic intervention to patients most in need.

  • Early Rheumatoid Arthritis
  • Synovitis
  • Ultrasonography

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  • Handling editor Josef S Smolen

  • GL-R and FH contributed equally.

  • Contributors GL-R and FH contributed equally to this manuscript. All authors have contributed to different degrees to patients recruitment and or data generation and or data analysis and or writing the manuscript and or revising data and or manuscript.

  • Funding Funding for PEAC MRC: Grant code 36661. Funding Infrastructure support to EMR, Arthritis Research UK Experimental Treatment Centre: Grant code 20022.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval The study received local ethical approval (REC 05/Q0703/198).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available upon reasonable request.

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