4.6 Article

Exploration of the serum metabolite signature in patients with rheumatoid arthritis using gas chromatography-mass spectrometry

期刊

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpba.2016.02.004

关键词

Rheumatoid arthritis; Metabolomics; Serum; GC-MS; Disease-associated metabolites

资金

  1. Science and Technology Planning Project of Zhejiang Province [2015C37045]
  2. National Basic Research Program of China (973 Program) [2014CB543001]
  3. National Natural Science Foundation of China [81403269]
  4. Scientific Research Fund of Zhejiang Provincial Education Department [Y201431059]

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Rheumatoid arthritis (RA) is a systemic autoimmune disease with complicated pathogeny. There could be obvious alterations of metabolism in the patients with RA and the discovery of metabolic signature may be helpful for the accurate diagnosis of RA. In order to explore the distinctive metabolic patterns in RA patients, a gas chromatography-mass spectrometry (GC-MS) method was employed. Serum samples from 33 RA patients and 32 healthy controls were collected and analyzed. Acquired metabolic data were assessed by the principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), and the data analysis results showed RA patients and healthy controls have very different metabolic profiles. Variable importance for project values (VIP) and Student's t-test were combined to screen the significant metabolic changes caused by RA. Serums from RA patients were featured by decreased levels of amino acids and glucose, increased levels of fatty acids and cholesterol, which were primarily associated with glycolytic pathway, fatty acid and amino acid metabolism, and other related pathways including TCA cycle and the urea cycle. These preliminary results suggest that GC-MS based metabolic profiling study appears to be a useful tool in the exploration of the metabolic signature of RA, and the revealed disease-associated metabolic perturbations could help to elucidate the pathogenesis of RA and provide a probable aid for the accurate diagnosis of RA. (C) 2016 Elsevier B.V. All rights reserved.

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