Abstract: A simple metabolic profiling approach for quantitative analysis of free fatty acids (FFAs) in human plasma by high performance liquid chromatography was described and validated, using α-bromoacetophenone as the derivative reagent and heptadecanoic acid (C17:0) as the internal standard. The quantitations of 6 predominant FFAs and 6 trace FFAs were achieved. Plasma fatty acid metabolic profiling of 75 diabetic patients was investigated, and then analyzed by multivariate statistical analysis. The linear discriminant analysis (LDA) model was established and validated for the pattern discrimination between Qi-deficiency and Qi and Yin-deficiency, with the hit ratio 94.3%. Stepwise discriminant analysis (SDA) model indicated that arachidonic acid (C20:4) and oleic acid (C18:1) contained the important information on the two syndromes above, and can be used as potential biomarkers of traditional Chinese medicine (TCM) syndrome. It is of great significance to systematically study the relationship between fatty acid metabolic profiling and TCM syndrome using metabolomics methods, and to improve the credibility and repeatability of clinical diagnosis and treatment system.

Key words: diabetes, free fatty acids (FFAs), traditional Chinese medicine (TCM) syndromes , metabonomics