Metabolomics profiling predicts outcome of tocilizumab in rheumatoid arthritis: an exploratory study
Por:
Murillo-Saich, JD, Diaz-Torne, C, Ortiz, MA, Coras, R, Gil-Alabarse, P, Pedersen, A, Corominas, H, Vidal, S, Guma, M
Publicada:
1 sep 2021
Resumen:
Introduction To study metabolic signatures can be used to identify predictive biomarkers for a patient's therapeutic response. Objectives We hypothesized that the characterization of a patients' metabolic profile, utilizing one-dimensional nuclear magnetic resonance (H-1-NMR), may predict a response to tocilizumab in patients with rheumatoid arthritis (RA). Methods 40 active RA patients meeting the 2010 ACR/EULAR classification criteria initiating treatment with tocilizumab were recruited. Clinical outcomes were determined at baseline, and after six and twelve months of treatment. EULAR response criteria at 6 and 12 months to categorize patients as responders and non-responders. Blood was collected at baseline and after six months of tocilizumab therapy. H-1-NMR was used to acquire a spectra of plasma samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification. SPSS v.27 and MetaboAnalyst 4.0 were used for statistical and pathway analysis. Results Isobutyrate, 3-hydroxybutyrate, lysine, phenylalanine, sn-glycero-3-phosphocholine, tryptophan and tyrosine were significantly elevated in responders at the baseline. OPLS-DA at baseline partially discriminated between RA responders and non-responders. A multivariate diagnostic model showed that concentrations of 3-hydroxybutyrate and phenylalanine improved the ability to specifically predict responders classifying 77.1% of the patients correctly. At 6 months, levels of methylamine, sn-glycero-3-phosphocholine and tryptophan tended to still be low in non-responders. Conclusion The relationship between plasma metabolic profiles and the clinical response to tocilizumab suggests that H-1-NMR may be a promising tool for RA therapy optimization. More studies are needed to determine if metabolic profiling can predict the response to biological therapies in RA patients.
Filiaciones:
Murillo-Saich, JD:
Univ Calif San Diego, Sch Med, Dept Med, 9500 Gilman Dr, San Diego, CA 92093 USA
Diaz-Torne, C:
Inst Rec Hosp Santa Creu & Sant Pau, Grp Inflammatory Dis, Carrer Sant Quinti 89, Barcelona 08041, Spain
Ortiz, MA:
Inst Rec Hosp Santa Creu & Sant Pau, Grp Inflammatory Dis, Carrer Sant Quinti 89, Barcelona 08041, Spain
Coras, R:
Univ Calif San Diego, Sch Med, Dept Med, 9500 Gilman Dr, San Diego, CA 92093 USA
Autonomous Univ Barcelona, Dept Med, Barcelona 08193, Spain
Gil-Alabarse, P:
VA San Diego Healthcare Syst, 3350 La Jolla Village Dr, San Diego, CA 92161 USA
Pedersen, A:
Univ Gothenburg, Swedish NMR Ctr, Medicinaregatan 5C, S-41390 Gothenburg, Sweden
Corominas, H:
Inst Rec Hosp Santa Creu & Sant Pau, Grp Inflammatory Dis, Carrer Sant Quinti 89, Barcelona 08041, Spain
Vidal, S:
Inst Rec Hosp Santa Creu & Sant Pau, Grp Inflammatory Dis, Carrer Sant Quinti 89, Barcelona 08041, Spain
Guma, M:
Univ Calif San Diego, Sch Med, Dept Med, 9500 Gilman Dr, San Diego, CA 92093 USA
Autonomous Univ Barcelona, Dept Med, Barcelona 08193, Spain
Open Access
|