Metabolome and disease activity in rheumatoid arthritis
The Anti-Tumor Necrosis Factor (TNF) therapies aid in managing rheumatoid arthritis (RA) disease activity and restrict structural damage. Still, no predictive factor of response to anti-TNF has been recognized. The determination of metabolomic profile could substantially improve diagnosis and, consequently, prognosis as it is known to vary in response to different inflammatory rheumatisms.
A research was performed to apply mass spectrometry to reveal whether there was variation in the metabolome in patients treated with anti-TNF and whether any specific metabolomic profile can aid as a predictor of therapeutic response. Before commencement of anti-TNF treatment and after 6 months of Anti-TNF treatment, blood samples were assessed in 140 patients with active RA (100 good responders and 40 non-responders). Using the reverse-phase chromatography–QToF mass spectrometry, the plasma was deproteinized, extracted and assessed. Extracted and normalized ions were evaluated by univariate and ANOVA analysis followed by partial least-squares regression-discriminant analysis (PLS-DA). The Orthogonal Signal Correction (OSC) was also used to filter data from unwanted non-related consequences. Disease activity scores (DAS 28), acquired at 6 months were correlated with metabolome variation outcomes to reveal a metabolite that is predictive of therapeutic response to anti-TNF.
As per EULAR criteria, 100 patients were rated as good responders and 40 patients as non-responders after 6 months of anti-TNF therapy. The metabolomic investigations indicated two different metabolic fingerprints splitting the good-responders group and the non-responders group, without differences in anti-TNF therapies. Univariate analysis depicted 24 significant ions in positive mode (p < 0.05) and 31 significant ions in negative mode (p < 0.05). Once intersected with PLS results, only 35 ions persisted. Carbohydrate derivate evolved as strong candidate determinants of therapeutic response.
This is the first study showing the metabolic profiling as a result to anti-TNF treatments using plasma samples. Also, the two different metabolic profiles splitting good responders from non-responders were efficiently highlighted in this study.
Dr Amit and dr Preetha