Zhou Jia, Chen Jiao, Hu Changfeng, Xie Zhijun, Li Haichang, Wei Shuangshuang, Wang Dawei, Wen Chengping, Xu Guowang
College of Basic Medical, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310053, China.
College of Basic Medical, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310053, China.
J Pharm Biomed Anal. 2016 Aug 5;127:60-7. doi: 10.1016/j.jpba.2016.02.004. Epub 2016 Feb 4.
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.
类风湿关节炎（RA）是一种病因复杂的全身性自身免疫性疾病。RA患者可能存在明显的代谢改变，发现代谢特征可能有助于RA的准确诊断。为了探索RA患者独特的代谢模式，采用了气相色谱-质谱联用（GC-MS）方法。收集并分析了33例RA患者和32例健康对照者的血清样本。通过主成分分析（PCA）和偏最小二乘判别分析（PLS-DA）对获得的代谢数据进行评估，数据分析结果显示RA患者和健康对照者具有非常不同的代谢谱。结合变量投影重要性（VIP）值和学生t检验筛选出由RA引起的显著代谢变化。RA患者血清的特点是氨基酸和葡萄糖水平降低，脂肪酸和胆固醇水平升高，这主要与糖酵解途径、脂肪酸和氨基酸代谢以及其他相关途径（包括三羧酸循环和尿素循环）有关。这些初步结果表明，基于GC-MS的代谢谱研究似乎是探索RA代谢特征的有用工具，所揭示的与疾病相关的代谢紊乱有助于阐明RA的发病机制，并为RA的准确诊断提供可能的帮助。
