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1H NMR Spectroscopy-Based Interventional Metabolic Phenotyping: A Cohort Study of Rheumatoid Arthritis Patients

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Faculty of Life Sciences, University of Copenhagen, Copenhagen, Denmark, Center for Sensory-Motor Interaction, Aalborg University, Aalborg, Denmark, The Parker Institute, Copenhagen University Hospital, Frederiksberg, Denmark, Institute of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark, Faculty of Health & Science, University of Copenhagen, Copenhagen, Denmark, Oregon Health & Sciences University, Portland, Oregon, Faculty of Medicine, Imperial College London, London, United Kingdom, Department of Heamatology, The Finsen Centre, Rigshospitalet, Copenhagen, Denmark, and Faculty of Pharmaceutical Sciences, University of Copenhagen, Copenhagen, Denmark
* To whom correspondence should be addressed. Henning Bliddal, The Parker Institute, Copenhagen University Hospital, Frederiksberg, Denmark. E-mail: [email protected]
†Faculty of Life Sciences, University of Copenhagen.
‡Aalborg University.
§Copenhagen University Hospital.
∥University of Southern Denmark.
⊥Faculty of Health & Science, University of Copenhagen.
#Oregon Health & Sciences University.
∇Imperial College London.
¶The Finsen Centre.
◆Faculty of Pharmaceutical Sciences, University of Copenhagen.
Cite this: J. Proteome Res. 2010, 9, 9, 4545–4553
Publication Date (Web):August 11, 2010
https://doi.org/10.1021/pr1002774
Copyright © 2010 American Chemical Society
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    Abstract

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    1H NMR spectroscopy-based metabolic phenotyping was used to identify biomarkers in the plasma of patients with rheumatoid arthritis (RA). Forty-seven patients with RA (23 with active disease at baseline and 24 in remission) and 51 healthy subjects were evaluated during a one-year follow-up with assessments of disease activity (DAS-28) and 1H NMR spectroscopy of plasma samples. Discriminant analysis provided evidence that the metabolic profiles predicted disease severity. Cholesterol, lactate, acetylated glycoprotein, and lipid signatures were found to be candidate biomarkers for disease severity. The results also supported the link between RA and coronary artery disease. Repeated assessment using mixed linear models showed that the predictors obtained from metabolic profiles of plasma at baseline from patients with active RA were significantly different from those of patients in remission (P = 0.0007). However, after 31 days of optimized therapy, the two patient groups were not significantly different (P = 0.91). The metabolic profiles of both groups of RA patients were different from the healthy subjects. 1H NMR-based metabolic phenotyping of plasma samples in patients with RA is well suited for discovery of biomarkers and may be a potential approach for disease monitoring and personalized medication for RA therapy.

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    Back-scaled loading plots obtained from OPLS-DA models of age and gender are available for comparison to the back-scaled loading plot from the OPLS-DA model of RA. This material is available free of charge via the Internet at http://pubs.acs.org.

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