TY - JOUR

T1 - 1H NMR spectroscopy-based interventional metabolic phenotyping

T2 - a cohort study of rheumatoid arthritis patients

AU - Lauridsen, Michael B

AU - Bliddal, Henning

AU - Christensen, Robin

AU - Danneskiold-Samsøe, Bente

AU - Bennett, Robert

AU - Keun, Hector

AU - Lindon, John C

AU - Nicholson, Jeremy K

AU - Dorff, Mikkel H

AU - Jaroszewski, Jerzy W

AU - Hansen, Steen Honore

AU - Cornett, Claus

N1 - Keywords: metabonomics, phenotyping, NMR, rheumatoid arthritis, chemometrics, disease monitoring, personalized medicine

PY - 2010/9/3

Y1 - 2010/9/3

N2 - 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.

AB - 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.

KW - Faculty of Health and Medical Sciences

U2 - 10.1021/pr1002774

DO - 10.1021/pr1002774

M3 - Journal article

C2 - 20701312

VL - 9

SP - 4545

EP - 4553

JO - Journal of Proteome Research

JF - Journal of Proteome Research

SN - 1535-3893

IS - 9

ER -