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A6.37 The synovial tissue transcriptome reveals combinations of protein biomarkers for unambiguous identification of RA patients from synovial fluid and for quantification of disease activity in serum
  1. B Smiljanovic1,
  2. B Stuhlmüller1,
  3. M Bonin1,
  4. S Pade1,
  5. B Backhaus1,
  6. GR Burmester1,
  7. A Radbruch2,
  8. A Grützkau2,
  9. T Häupl1
  1. 1Department of Rheumatology and Clinical Immunology, Charité CCM, Berlin, Germany
  2. 2German Rheumatism Research Center, Berlin (DRFZ-Berlin), Germany


Background and objectives A main challenge in disease-management of rheumatoid arthritis (RA) is to establish criteria for molecular disease activity and therapeutic stratification of patients. The commonly used disease activity score 28 (DAS28), autoantibodies, or the joint ultrasound score US7 only insufficiently characterise the diversity of chronic inflammation in RA. To address these challenges we analysed synovial tissue transcriptomes, synovial fluid (SF) and serum proteome from long-lasting RA patients, and serum proteome from early RA patients.

Materials and methods Affymetrix HG-U133A transcriptomes were generated from synovial tissue biopsies of long-lasting RA (n = 10) and osteoarthritis (OA) (n = 10) patients. Multiplex-immunoassays and ELISA were used for marker validation at the protein level in SF and matched serum samples from long-lasting RA (n = 17) and OA (n = 16) patients. Prediction analysis for microarrays (PAM) identifies a minimum set of markers able to correctly classify RA. These markers were measured in serum from early RA patients (n = 10) before and after treatment with corticosteroids and methotrexate (MTX). Serum from healthy donors (ND; n = 14) was used as control.

Results Comparison between synovial tissue transcriptomes from long-lasting RA and OA patients revealed differential expression of 1200 genes. 28 candidate genes were selected based on high differential expression and extracellular release. When validated at the protein level, 23 markers revealed elevated concentration in SF and 16 markers in serum from long-lasting RA patients. The PAM algorithm identified combination of 5 markers as the minimum set of molecules for correct classification of long-lasting RA compared to OA. An RA-specific molecular score was determined as the sum of the normalised expression values for these 5 markers, which correlated with DAS28 (r = 0.6854). Evaluation of top candidates in early RA patients revealed that only one-third of patients exhibited this molecular pattern. Treatment of these patients with corticosteroids and MTX resulted in changes of DAS28, where 7 patients were considered to be good and 3 moderate responders. Reduced serum concentration of the 5 markers was accompanied with changes of RA-molecular scores, which also correlated with the change of DAS28 (r = 0.582).

Conclusion The synovial tissue transcriptome is an exceptional source for biomarker discovery. The tested synovial fluid proteome in long-lasting RA greatly resembles the transcriptome data for the secreted proteins. Serum from long-lasting RA also reflected the disease-specific characteristics of this multi-parameter pattern when compared to OA and ND. However, limited potential was observed when applied in early RA patients, suggesting that more sensitive approaches are needed.

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