Variations in the metabolome in response to disease activity of rheumatoid arthritis

Autor: Carole Migné, Mélanie Pétéra, Jacques Tebib, Hubert Marotte, Martin Soubrier, Estelle Pujos Guillot, Thierry Lequerré, Zuzana Tatar, Philippe Gaudin
Přispěvatelé: Rhumatologie, CHU Strasbourg, Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), CHU Bois-Guillaume, U 1059, Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon, Hospital and Clinical Research Program, Passerelle 2012 founding (Pfizer), Unité de Nutrition Humaine (UNH), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Institut National de la Recherche Agronomique (INRA), CHU Clermont-Ferrand, CHU Grenoble, CHU Rouen, Normandie Université (NU), Physiopathologie et biothérapies des maladies inflammatoires et autoimmunes, Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon (COMUE), Centre Hospitalier Universitaire de Lyon, Tatar, Zuzana, Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, ProdInra, Archive Ouverte
Jazyk: angličtina
Rok vydání: 2016
Předmět:
0301 basic medicine
Male
rheumatoid arthritis
Necrosis
[SDV]Life Sciences [q-bio]
Bioinformatics
Mass Spectrometry
drug response biomarkers
Etanercept
Arthritis
Rheumatoid
0302 clinical medicine
Orthopedics and Sports Medicine
anti-TNF-alpha therapy
ComputingMilieux_MISCELLANEOUS
Chromatography
Reverse-Phase
[SDV.MHEP] Life Sciences [q-bio]/Human health and pathology
facteur de nécrose tumorale
Discriminant Analysis
drug treatment
échantillon de plasma
Middle Aged
Prognosis
metabolomics
3. Good health
Treatment Outcome
Rheumatoid arthritis
Antirheumatic Agents
Alimentation et Nutrition
Metabolome
Tumor necrosis factor alpha
Female
medicine.symptom
metabolomics and rheumatoid arthritis (RA)
profil métabolique
Research Article
Adult
medicine.medical_specialty
anti-TNF therapy
Médecine humaine et pathologie
Disease activity
03 medical and health sciences
Metabolomics
Rheumatology
Internal medicine
medicine
Humans
Food and Nutrition
In patient
Aged
030203 arthritis & rheumatology
business.industry
Tumor Necrosis Factor-alpha
Adalimumab
biomarkers
medicine.disease
Infliximab
Surgery
[SDV.AEN] Life Sciences [q-bio]/Food and Nutrition
030104 developmental biology
Human health and pathology
business
[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Zdroj: BMC Musculoskeletal Disorders
BMC Musculoskeletal Disorders, BioMed Central, 2016, 17 (1), 7 p. ⟨10.1186/s12891-016-1214-5⟩
Arthritis and Rheumatology
2015 ACR/ARHP Annual Meeting
2015 ACR/ARHP Annual Meeting, Nov 2015, San-Francisco, United States
BMC Musculoskeletal Disorders 1 (17), 7 p.. (2016)
BMC Musculoskeletal Disorders, 2016, 17 (1), 7 p. ⟨10.1186/s12891-016-1214-5⟩
ISSN: 1471-2474
DOI: 10.1186/s12891-016-1214-5⟩
Popis: Background Anti-Tumor Necrosis Factor (TNF) therapies are able to control rheumatoid arthritis (RA) disease activity and limit structural damage. Yet no predictive factor of response to anti-TNF has been identified. Metabolomic profile is known to vary in response to different inflammatory rheumatisms so determining it could substantially improve diagnosis and, consequently, prognosis. The aim of this study was to use mass spectrometry to determine whether there is variation in the metabolome in patients treated with anti-TNF and whether any particular metabolomic profile can serve as a predictor of therapeutic response. Methods Blood samples were analyzed in 140 patients with active RA before initiation of anti-TNF treatment and after 6 months of Anti-TNF treatment (100 good responders and 40 non-responders). Plasma was deproteinized, extracted and analyzed by reverse-phase chromatography–QToF mass spectrometry. Extracted and normalized ions were tested by univariate and ANOVA analysis followed by partial least-squares regression-discriminant analysis (PLS-DA). Orthogonal Signal Correction (OSC) was also used to filter data from unwanted non-related effects. Disease activity scores (DAS 28) obtained at 6 months were correlated with metabolome variation findings to identify a metabolite that is predictive of therapeutic response to anti-TNF. Results After 6 months of anti-TNF therapy, 100 patients rated as good responders and 40 patients as non-responders according to EULAR criteria. Metabolomic investigations suggested two different metabolic fingerprints splitting the good-responders group and the non-responders group, without differences in anti-TNF therapies. Univariate analysis revealed 24 significant ions in positive mode (p
Databáze: OpenAIRE
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