Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10723
Title: Plasma fatty acid metabolic profiling and biomarkers of type 2 diabetes mellitus based on GC/MS and PLS-LDA
Authors: Yi, LZ
He, J
Liang, YZ
Yuan, DL
Chau, FT
Keywords: Biomarker
Fatty acid profiling
Partial least squares-linear discrimination analysis (PLS-LDA)
Rosiglitazone
Type 2 diabetes mellitus
Issue Date: 2006
Source: FEBS letters, 2006, v. 580, no. 30, p. 6837-6845 How to cite?
Journal: FEBS Letters 
Abstract: Metabolic profiling has increasingly been used as a probe in disease diagnosis and pharmacological analysis. Herein, plasma fatty acid metabolic profiling including non-esterified fatty acid (NEFA) and esterified fatty acid (EFA) was investigated using gas chromatography/mass spectrometry (GC/MS) followed by multivariate statistical analysis. Partial least squares-linear discrimination analysis (PLS-LDA) model was established and validated to pattern discrimination between type 2 diabetic mellitus (DM-2) patients and health controls, and to extract novel biomarker information. Furthermore, the PLS-LDA model visually represented the alterations of NEFA metabolic profiles of diabetic patients with abdominal obesity in the treated process with rosiglitazone. The GC/MS-PLS-LDA analysis allowed comprehensive detection of plasma fatty acid, enabling fatty acid metabolic characterization of DM-2 patients, which included biomarkers different from health controls and dynamic change of NEFA profiles of patients after treated with medicine. This method might be a complement or an alternative to pathogenesis and pharmacodynamics research.
URI: http://hdl.handle.net/10397/10723
ISSN: 0014-5793
DOI: 10.1016/j.febslet.2006.11.043
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