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

  • Chan Seo
  • , Yun Ho Hwang
  • , Hyeon Seong Lee
  • , Youngbae Kim
  • , Tae Hwan Shin
  • , Gwang Lee
  • , Young Jin Son
  • , Hangun Kim
  • , Sung Tae Yee
  • , Ae Kyung Park
  • , Man Jeong Paik*
  • *Corresponding author for this work
  • Sunchon National University
  • Ajou University

Research output: Contribution to journalJournal articlepeer-review

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.

Original languageEnglish
Pages (from-to)156-162
Number of pages7
JournalJournal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
Volume1063
DOIs
StatePublished - 2017.09.15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Asthma
  • Gas chromatography–mass spectrometry
  • Metabolomics
  • Profiling analysis
  • Star graphic pattern analysis

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