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OP0128 Metabolic profiling of urine samples predicts response to anti-TNF therapy in patients with rheumatoid arthritis
  1. S.R. Kapoor1,2,
  2. A. Filer1,3,
  3. M. Fitzpatrick1,
  4. B.A. Fisher4,
  5. P.C. Taylor5,
  6. C. Buckley1,2,
  7. I. McInnes6,
  8. K. Raza1,2,
  9. S.P. Young1
  1. 1Rheumatology Research Group, University of Birmingham
  2. 2Rheumatology, University of Birmingham and Sandwell and West Birmingham NHS Trust
  3. 3Rheumatology, University Hospitals Birmingham NHS Foundation Trust, Birmingham
  4. 4Rheumatology, Imperial College, London
  5. 5Kennedy Institute of Rheumatology, University of Oxford, Oxford
  6. 6Institute of infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom

Abstract

Background Anti-TNFα therapies are highly effective in the treatment of rheumatoid arthritis (RA) but a significant proportion of patients have an inadequate response. TNFα has an important role in regulating systemic and localised metabolism.

Objectives We sought to determine if the metabolic profile of patients prior to therapy could be used to predict responses to anti-TNFα agents.

Methods Urine was collected from 16 patients with RA before and during therapy with infliximab or etanercept as part of a multicentre study. All patients were female and the mean age was 51.5. 14 patients were positive for rheumatoid factor and 14 for anti-CCP antibody. All had a DAS28>4 at baseline. Urine metabolic profiles were assessed using NMR spectroscopy. Relevant metabolites were identified, and the relationship between metabolic profiles and clinical outcomes was assessed (using partial least square discriminant analysis (PLSDA), principal component analysis using a genetic algorithm data selection (Galgo) and PLS-R (regression) analysis).

Results Baseline urine metabolic profiles discriminated between RA patients who did (7 patients) or did not (9 patients) have a good response to anti-TNFα therapy according to EULAR criteria with a sensitivity of 85.9% and specificity of 85.7% with several metabolites (in particular citrate, creatinine and cresol) contributing. A correlation between baseline metabolic profiles in the urine samples and the extent of change in DAS 28 was seen (PLS-R analysis p=0.04). In patients with RA who responded to TNFα antagonists, a good response to therapy was associated with changes in the following urinary metabolites: erythritol, phenylacetic acid, p-cresol, propionic acid, methylamine, citrate, hippuric acid and creatinine. Urine samples from 20 psoriatic arthritis (PsA) patients were also assessed. Similar metabolites were identified in the urine samples of the patients with PsA that responded to TNFα antagonists. We were unable to study the ability of baseline urinary metabolite profiles to predict response in PsA as all but one of the PsA patients responded according to predefined criteria.

Conclusions There are clear differences in the baseline urinary metabolic profiles of RA patients who respond well to anti-TNFα therapy. This may be relevant to the development of clinically useful predictive strategies.

Disclosure of Interest S. Kapoor: None Declared, A. Filer: None Declared, M. Fitzpatrick: None Declared, B. Fisher Grant/Research support from: Merck provided funding for the clinical study and associated sample collection (but not for the metabolomic analysis reported here)., P. Taylor Grant/Research support from: Merck provided funding for the clinical study and associated sample collection (but not for the metabolomic analysis reported here)., C. Buckley Grant/Research support from: Merck provided funding for the clinical study and associated sample collection (but not for the metabolomic analysis reported here)., I. McInnes Grant/Research support from: Merck provided funding for the clinical study and associated sample collection (but not for the metabolomic analysis reported here)., K. Raza: None Declared, S. Young: None Declared

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