4.5 Article

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

Journal

JOURNAL OF PHYSIOLOGY AND BIOCHEMISTRY
Volume 70, Issue 1, Pages 117-128

Publisher

SPRINGER
DOI: 10.1007/s13105-013-0286-z

Keywords

Metabolomics; Type 2 diabetes Biomarkers; Diagnosis; Pattern recognition approach; UPLC-ESI-Q-TOF-MS

Funding

  1. Key Program of Natural Science Foundation of State [90709019, 81173500, 81302905, 81202639]
  2. National Key Technology Research and Development Program of the Ministry of Science and Technology of China [2011BAI03B03, 2011BAI03B06, 2011BAI03B08]
  3. Key Science and Technology Program of Heilongjiang Province, China [GC06C501, GA08C303, GA06C30101]
  4. National Specific Program on the Subject of Public Welfare [200807014]
  5. National Key Subject of Drug Innovation [2009ZX09502-005]
  6. Foundation of Heilongjiang University of Chinese Medicine [201209]
  7. Key Project of Chinese Ministry of Education [212044]

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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 robustmetabolomics 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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