Plasma fatty acid metabolic profiles for traditional Chinese medicine syndrome differentiation in diabetic patients using uncorrelated linear discriminant analysis

Diabetes is a common metabolic syndrome which presents a serious threat to human health.Traditional Chinese medicine(TCM) has been widely paid attention to its advantages and characteristics in the diagnosis and the treatment of diabetes.A strategy of classifying five TCM syndromes in diabetes(Qi-deficiency,Yin-deficiency,Qi-and Yin-deficiency,Damp heat and Blood stasis) was employed based on plasma fatty acid metabolic profiles,lipid metabolism indicators and chemometrics methods.Using orthogonal signal correction-partial least squares(OSC-PLS) method,the five syndromes were obviously distinguished from those of the health control,which confirmed there existed metabolite differences in different traditional Chinese medicine syndromes.Furthermore,a new method,uncorrelated linear discriminant analysis(ULDA),was applied in the discrimination of health control,TCM deficiency syndromes(Qi-deficiency,Yin-deficiency,Qi-and Yin-deficiency) and TCM empirical syndromes(Damp heat,Blood stasis),which demonstrated better clustering results,the correct rate reached 95.7%.The four potential biomarkers,C20∶2,C20∶5,triglycerides(TG) and high density lipoprotein(HDL),performed large contributions to the classification which can provide important information assisting TCM clinical diagnosis.