Abstract
Introduction: Recently, the relationship between polyamine (PA) metabolism and asthma has been studied in severe asthmatic therapy, but systematic PA metabolism including their acetylated derivatives was not fully understood. Objectives: Profiling analysis of polyamines (PAs) was performed to understand the biochemical events and monitor altered PA metabolism in lung tissue of mice with asthma. Methods: Polyamine profiling of lung tissue of mice with asthma was performed without derivatization by liquid chromatography–tandem mass spectrometry (LC–MS/MS) combined with star pattern recognition analysis. The PA levels between control and asthma groups were evaluated by multivariate analysis. Results: In mouse lung tissue, seven PAs were determined by LC–MS/MS in multiple reaction monitoring (MRM) mode. Their levels were normalized to the corresponding mean levels of the control group for star pattern analysis, which showed distorted heptagonal shapes with characteristic and readily distinguishable patterns for each group. Levels of putrescine (p < 0.0034), N 1 -acetylputrescine (p < 0.0652), and N 8 -acetylspermidine (p < 0.0827) were significantly increased in asthmatic lung tissue. The separation of the two groups was evaluated using multivariate analysis. In unsupervised learning, acetylated PAs including N 1 -acetylspermine were the main metabolites for discrimination. In supervised learning, putrescine and N 1 -acetylputrescine were evaluated as important metabolites. Conclusions: The present results provide basic data for understanding polyamine metabolism in asthma and may help to improve the therapy for severe asthma patients.
| Original language | English |
|---|---|
| Article number | 8 |
| Journal | Metabolomics |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2019.01.1 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Acetylated polyamines
- Asthma
- Liquid chromatography–tandem mass spectrometry
- Lung tissue
- Metabolomics
- Polyamine profiling analysis
- Star pattern recognition analysis
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