Plasma fatty acid metabolic profiling and biomarkers of type 2 diabetes mellitus based on GC/MS and PLS-LDA.
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.
Yi
Lun-Zhao
LZ
Research Center of Modernization of Chinese Medicines, Central South University, Changsha 410083, PR China.
He
Jun
J
Liang
Yi-Zeng
YZ
Yuan
Da-Lin
DL
Chau
Foo-Tim
FT
D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D003924:Diabetes Mellitus, Type 2 / Q000378:metabolism*; D005227:Fatty Acids / Q000097:blood* / Q000737:chemistry*; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D006262:Health; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D013696:Temperature
D015415:Biomarkers; D005227:Fatty Acids