학술논문

1H-NMR-Based Metabolomic Study for Identifying Serum Profiles Associated with the Response to Etanercept in Patients with Rheumatoid Arthritis.
Document Type
Article
Source
PLoS ONE. 11/11/2015, Vol. 10 Issue 10, p1-14. 14p.
Subject
*METABOLOMICS
*SERUM
*ETANERCEPT
*RHEUMATOID arthritis treatment
*RHEUMATOID arthritis
*BIOMARKERS
*NUCLEAR magnetic resonance spectroscopy
*PATIENTS
Language
ISSN
1932-6203
Abstract
Objective: A considerable proportion of patients with rheumatoid arthritis (RA) do not have a satisfactory response to biological therapies. We investigated the use of metabolomics approach to identify biomarkers able to anticipate the response to biologics in RA patients. Methods: Due to gender differences in metabolomic profiling, the analysis was restricted to female patients starting etanercept as the first biological treatment and having a minimum of six months’ follow-up. Each patient was evaluated by the same rheumatologist before and after six months of treatment. At this time, the clinical response (good, moderate, none) was determined according to the EUropean League Against Rheumatism (EULAR) criteria, based on both erythrocyte sedimentation rate (EULAR-ESR) and C-reactive protein (EULAR-CRP). Sera collected prior and after six months of etanercept were analyzed by 1H-nuclear magnetic resonance (NMR) spectroscopy in combination with multivariate data analysis. Results: Twenty-seven patients were enrolled: 18 had a good/moderate response and 9 were non responders according to both EULAR-ESR and EULAR-CRP after six months of etanercept. Metabolomic analysis at baseline was able to discriminate good, moderate, and non-responders with a very good predictivity (Q2 = 0.68) and an excellent sensitivity, specificity, and accuracy (100%). In good responders, we found an increase in isoleucine, leucine, valine, alanine, glutamine, tyrosine, and glucose levels and a decrease in 3-hydroxybutyrate levels after six months of treatment with etanercept with respect to baseline. Conclusion: Our study confirms the potential of metabolomic analysis to predict the response to biological agents. Changes in metabolic profiles during treatment may help elucidate their mechanism of action. [ABSTRACT FROM AUTHOR]