In this study, patients with prehypertensive liver-fire hyperactivity syndrome(LFHS) were selected as the research objects. The plasma samples of healthy volunteers and patients with prehypertensive LFHS were analyzed by non-targeted metabolomics based on UPLC-Q-Exactive MS. The differential biomarkers and metabolic pathways were screened out by multivariate statistics and metabolic pathway analysis, which revealed the characteristics of metabolic patterns of the syndrome. Thirty-three potential biomarkers such as androsterone and lysophosphatidylcholine and 16 related metabolic pathways such as steroid hormone metabolism and lipid metabolism were identified, and a partial least squares-discriminant analysis(PLS-DA) model of traditional Chinese medicine(TCM) syndromes was preliminarily constructed: Y =-0.070X_(13)-0.006X_8+ 0.040X_5-0.152X_1+0.131X_(10)+0.036X_(11)+0.043X_(23)+0.076X_(16)+0.132X_(20)+0.081X_(19)-0.101X_(31)+0.082X_(15)-0.038X_9+0.079X_(24). The predictive value of the model was 88.1%, and the explanatory power was 88.4%. In this study, the characteristic metabolic pattern of the prehypertensive LFHS was distinguished and revealed by metabolomics. The constructed PLS-DA model is expected to provide an objective basis for the identification of TCM syndromes in prehypertension, and inspiration for exploring the biological basis of TCM syndromes at small-molecular and overall levels.
Keywords: liver-fire hyperactivity syndrome(LFHS); metabolomics; prehypertension.