Background/Purpose: We hypothesized that characterization of patients’ metabolic profiles, utilizing both high-resolution ¹H-nuclear magnetic resonance (NMR) and mass spectrometry (MS), might help predict response to rituximab therapy in rheumatoid arthritis (RA).  

Methods: 23 active seropositive RA patients on concomitant methotrexate were treated with rituximab (1g intravenously; days 0 and 14; without peri-infusional steroids). Clinical outcome was determined 6 months after treatment. Patients were classified as responders or non-responders according to the ACR20 responses. Blood was collected before (baseline) and at 6 months after rituximab therapy. A Bruker Avance 700 MHz spectrometer and a Thermo Scientific Q Exactive Hybrid Quadrupole-Orbitrap Mass Spectrometer were used on ultrafiltered peripheral blood samples at baseline and 6 months after rituximab therapy. Data processing and statistical analysis were performed in the MATLAB programming environment. Pathway analysis was performed using VANTED software. Significantly different metabolites were identified and the relationship between metabolites and clinical outcome was studied.

Results: Multivariate statistical analysis of the ¹H-NMR baseline spectra successfully discriminated between RA patients classified as rituximab responders (n = 14) and non-responders (n = 9), at baseline and 6 months after rituximab treatment. A two sample t-test produced p-values of less than 0.05 for seven metabolites which were decreased in responders: phenylalanine, 2-hydroxyvalerate, succinate, choline, glycine, acetoacetate, and tyrosine. Lipids analysis by MS also discriminated between RA patients. Prior to treatment, most observed classes of glycerophospholipids were downregulated in rituximab responders, including phosphatidylethanolamines, phosphatidylserines, and phosphatidylglycerol. Opposite trend was observed in phosphatidylinositols. Following treatment with rituximab, several of these trends were reversed in responders, suggesting that response to rituximab is related to shifts in phospholipid composition in responders.

Conclusion: The relationship between blood profiles and patient response to rituximab therapy suggests that the application of ¹H-NMR and MS profiling may be a promising clinical tool for RA therapy optimization. Additional metabolic profile studies are needed to determine if metabolic profiling can predict response to this and other biological therapies in RA patients.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/metabolomic-profiling-predicts-outcome-of-rituximab-therapy-in-rheumatoid-arthritis/