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Updated: Mar 21, 2026

Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults
Published on: April 22, 2022
Metabolomic study of aging in mouse plasma by gas chromatography-mass spectrometry
Chan Seo1, Yun-Ho Hwang1, Youngbae Kim1
1College of Pharmacy, Sunchon National University, Suncheon, Republic of Korea.
Abstract:
Metabolomic analysis of aging was performed in plasma samples of young (8 weeks) and old (72 weeks) mice as ethoxycarbonyl/methoxime/tert-butyldimethylsilyl derivatives by gas chromatography-mass spectrometry (GC-MS). As new approaches, study of altered metabolism from aging was attempted by simultaneous profiling analysis of amino acids (AAs), organic acids (OAs) and fatty acids (FAs) by GC-MS in a single run combined with pattern analysis. As a result, 27 amino acids (AAs), 17 organic acids (OAs) and 24 fatty acids (FAs) were positively screened with large variations in plasma samples. Among altered metabolites, levels of six AAs (proline, methionine, 4-hydroxyproline, pipecolic acid, glutamic acid, α-aminoadipic acid) as neurotransmetters and nutrients, five OAs (2-hydroxybutyric acid, 2-hydroxyglutaric acid, cis-aconitic acid citric acid, isocitric acid) including intermediate metabolites in the TCA cycle, and three n-3 polyunsaturated FAs (PUFAs) of α-octadecatrienoic acid, eicosapentaenoic acid and docosahexaenoic acid as potential biomarkers were significantly different between young and old groups. Their levels were normalized to the corresponding mean values of the young group and then plotted into star symbol patterns, which were clearly distinct compared with numerical data and readily distinguishable for young and old groups. Thus, the present metabolomic screening and the star pattern recognition method might be useful for understanding the complexity of biochemical events in aging.
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