Comparative serum metabolomic profiling of hypertension in different traditional Chinese medicine syndromes.

Background: Hypertension is a crucial risk factor for cardiovascular diseases. Previous studies have revealed the serum metabolic profiles of patients with hypertension, laying the groundwork for accurate diagnosis and potential therapeutic target identification. While hypertension has well-documented biochemical signatures, TCM classifies it into distinct syndromes based on patterns of clinical manifestations and underlying pathophysiological concepts. From the perspective of Traditional Chinese Medicine (TCM), hypertension can be classified into several distinct syndromes, including Liver Yang Rising (LYR), Internal Phlegm-Dampness Accumulation (IPDA), and Liver-Kidney Yin Deficiency (LKYD). The present study aimed to identify the metabolic biomarkers for TCM syndromes by metabolomic analysis. Methods: Metabolomic profiling of LYR, IPDA, and LKYD was performed (10 cases per group, sampled randomly) among thirty hypertensive patients and ten healthy controls recruited from the First Hospital of Hunan University of Chinese Medicine, Changsha, China. Hypertension and TCM syndrome classification were confirmed by clinicians, and participants with severe organ dysfunction or acute illnesses were excluded. Ultra-performance liquid chromatography-tandem mass spectrometry was used to identify differentially expressed metabolites (DEMs), weighted correlation network analysis (WGCNA) was applied to construct syndrome-associated networks, and multivariate ROC-based exploratory analysis identified key biomarkers with high diagnostic performance. Results: Thirty-seven DEMs were identified for each syndrome comparison (LYR vs. control, IPDA vs. control, and LKYD vs. control), with 26 shared DEMs enriched in multiple metabolic pathways. Pairwise comparisons among TCM syndromes revealed distinct metabolic profiles, including glycated amino acids and tryptophan derivatives. WGCNA identified hub metabolites such as p-Xylene and Octinoxate. Multivariate ROC analysis yielded ten biomarkers with high diagnostic accuracy (AUC = 0.944), offering potential for distinguishing TCM-based hypertension subtypes and guiding targeted interventions. Conclusion: Distinct metabolic signatures of TCM-based hypertension syndromes were identified, along with serum biomarkers showing high diagnostic accuracy. These findings support more precise syndrome differentiation and offer potential targets for personalized hypertension management.