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Metabolomics study of type 2 diabetes using ultra-performance LC-ESI/quadrupole-TOF high-definition MS coupled with pattern recognition methods

Authors
  • Zhang, Ai-hua1
  • Sun, Hui1
  • Yan, Guang-li1
  • Yuan, Ye1
  • Han, Ying1
  • Wang, Xi-jun1
  • 1 Heilongjiang University of Chinese Medicine, National TCM Key Lab of Serum Pharmacochemistry, Key Lab of Chinmedomics, Key Pharmacometabolomic Platform of Chinese Medicines, Department of Pharmaceutical Analysis, Heping Road 24, Harbin, 150040, China , Harbin (China)
Type
Published Article
Journal
Journal of Physiology and Biochemistry
Publisher
Springer Netherlands
Publication Date
Aug 24, 2013
Volume
70
Issue
1
Pages
117–128
Identifiers
DOI: 10.1007/s13105-013-0286-z
Source
Springer Nature
Keywords
License
Yellow

Abstract

Type 2 diabetes (T2D), called the burden of the twenty-first century, is growing with an epidemic rate. Here, we explored the differences in metabolite concentrations between T2D patients and healthy volunteers. Metabolomics represents an emerging discipline concerned with comprehensive analysis of small molecule metabolites and provides a powerful approach to discover biomarkers in biological systems. The acquired data were analyzed by ultra-performance liquid chromatography–electrospray ionization/quadrupole time-of-flight high-definition mass spectrometry coupled with pattern recognition approach [principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA)] to identify potential disease-specific biomarkers. PCA showed satisfactory clustering between patients and healthy volunteers. Biomarkers reflected the biochemical events associated with early stages of T2D which were observed in PLS-DA loading plots. These urinary differential metabolites, such as adiponectin, acylcarnitines, citric acid, kynurenic acid, 3-indoxyl sulfate, urate, and glucose, were identified involving several key metabolic pathways such as taurine and hypotaurine metabolism; cysteine and methionine metabolism; valine, leucine, and isoleucine biosynthesis metabolism, etc. Our data suggest that robust metabolomics has the potential as a noninvasive strategy to evaluate the early diagnosis of T2D patients and provides new insight into pathophysiologic mechanisms and may enhance the understanding of its cause of disease.

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