NMR-based metabolomics in a clinical cohort: deciphering the metabolic characteristics of gout with the dampness-heat syndrome and elucidate the efficacy of Simiao Pill

作者：Yu Hu, Le Yang, Guangli Yan, Ye Sun, Maojie Wang, Ling Kong, Hui Sun, Xueping Zhao, Xinya Zhang, Runyue HUANG, Chang Liu, Ying Han, Xijun Wang · 发表于：Chinese Medicine · 年份：2026 · DOI：10.1186/s13020-025-01289-6 · 被引用次数：1 · 研究领域：Gout, Hyperuricemia, Uric Acid、Metabolomics and Mass Spectrometry Studies、Tryptophan and brain disorders

BACKGROUND: Gout is an inflammatory arthritis caused by purine metabolism disorders. The gout with the dampness-heat syndrome (GDHS) is a common Traditional Chinese Medicine (TCM) syndrome in this kind of disease, yet its modern scientific basis remains poorly understood. Simiao Pill (SMP), a classic formula in treating GDHS, has an unclear mechanism of action. METHODS: We conducted a targeted Nuclear Magnetic Resonance (NMR)-based metabolomic analysis on serum and urine samples from 197 GDHS patients and 101 healthy controls. Multiple machine learning algorithms, including support vector machine (SVM), random forest (RF), and least absolute shrinkage and selection operator (LASSO), were employed to identify potential biomarkers for GDHS. The Apriori algorithm was applied to uncover associations between TCM syndrome manifestations and metabolomic biomarkers. A subgroup of 50 GDHS patients received a 4-week SMP treatment, and their metabolomic profiles were compared pre- and post- intervention. RESULTS: GDHS patients exhibited a significant remodeled metabolome, characterized by disruptions in pyruvate, amino acid metabolism, and energy metabolism. A panel of 12 biomarkers with high diagnostic power was identified. Association rule mining further highlighted triglycerides and glycine as central nodes showing extensive connections to TCM syndromes. SMP intervention significantly reversed the level of 10 biomarkers (e.g., citrate, glycine, lactate), effectively normalizing pertu...