Metabolomic study for monitoring of biomarkers in mouse plasma with asthma by gas chromatography-mass spectrometry.

Abstract

Asthma is a multifaceted chronic disease caused by an alteration of various genetic and environmental factors that is increasing in incidence worldwide. However, the biochemical mechanisms regarding asthma are not completely understood. Thus, we performed of metabolomic study for understanding of the biochemical events by monitoring of altered metabolism and biomarkers in asthma. In mice plasma, 27 amino acids(AAs), 24 fatty acids(FAs) and 17 organic acids(OAs) were determined by ethoxycarbonyl(EOC)/methoxime(MO)/tert-butyldimethylsilyl(TBDMS) derivatives with GC-MS. Their percentage composition normalized to the corresponding mean levels of control group. They then plotted as star symbol patterns for visual monitoring of altered metabolism, which were characteristic and readily distinguishable in control and asthma groups. The Mann-Whitney test revealed 25 metabolites, including eight AAs, nine FAs and eight OAs, which were significantly different (p<0.05), and orthogonal partial least-squares-discriminant analysis revealed a clear separation of the two groups. In classification analysis, palmitic acid and methionine were the main metabolites for discrimination between asthma and the control followed by pipecolic, lactic, α-ketoglutaric, and linoleic acids for high classification accuracy as potential biomarkers. These explain the metabolic disturbance in asthma for AAs and FAs including intermediate OAs related to the energy metabolism in the TCA cycle.

DOI: 10.1016/j.jchromb.2017.08.039

Cite this paper

@article{Seo2017MetabolomicSF, title={Metabolomic study for monitoring of biomarkers in mouse plasma with asthma by gas chromatography-mass spectrometry.}, author={Chan Hee Seo and Yun-Ho Hwang and Hyeon-Seong Lee and YoungBae Kim and Tae Hwan Shin and Gwang Lee and Young-Jin Son and Hangun Kim and Sung-Tae Yee and Ae Kyung Park and M Paik}, journal={Journal of chromatography. B, Analytical technologies in the biomedical and life sciences}, year={2017}, volume={1063}, pages={156-162} }