Integrated GC–MS and LC–MS plasma metabonomics analysis of ankylosing spondylitis

Peng Gao; Chen Lu; Fengxia Zhang; Ping Sang; Dawei Yang; Xiang Li; Hongwei Kong; Peiyuan Yin; Jing Tian; Xin Lu; Aiping Lu; Guowang Xu

doi:10.1039/B807369D

Integrated GC–MS and LC–MS plasma metabonomics analysis of ankylosing spondylitis†

Peng Gao,^a Chen Lu,^b Fengxia Zhang,^ac Ping Sang,^ad Dawei Yang,^ad Xiang Li,^a Hongwei Kong,^a Peiyuan Yin,^a Jing Tian,^ad Xin Lu,^a Aiping Lu*^b and Guowang Xu*^a

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^a National Chromatographic R. & A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
E-mail: xugw@dicp.ac.cn
Fax: ++86-411-84379559
Tel: +86-411-84379530

^b Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China
E-mail: lap64067611@126.com
Fax: +86-10-64013896
Tel: +86-10-64067611

^c Shenyang Pharmaceutical University, Shenyang 110016, China

^d Department of Modern Technology, Dalian Polytechnic University, Dalian 116034, China

Abstract

Ankylosing spondylitis (AS) is a chronic inflammatory arthritis that predominantly affects the axial skeleton in adolescent patients. The natural history of the disease remains poorly characterized. In this study, we combined GC–MS and LC–MS techniques to evaluate the major metabolic changes in the plasma of AS patients in view of metabonomics. Univariate and multivariate analysis were employed for altered metabolite comparison and pattern recognition. Application of supervised partial least-squares discrminant analysis to either GC–MS or LC–MS data allowed accurate discrimination of AS patients from normal controls, demonstrating its potential diagnostic utilization. In addition, AS patients presented elevated plasma concentrations of proline, glucose, phosphate, urea, glycerol, phenylalanine and homocysteine but reduced levels of phosphocholines, tryptophan and a bipeptide – phenylalanyl-phenylalanine. In the context of their involved metabolic pathways, the identified metabolites were discussed accordingly. This investigation primarily proved that integrated chromatography–mass spectrometry and integrated uni- and multi-variate statistical analysis facilitated metabonomics to be a more promising tool in disease research.

This article is part of the themed collection: Highlighting analytical science in China

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Integrated GC–MS and LC–MS plasma metabonomics analysis of ankylosing spondylitis†

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