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Updated: Jan 17, 2026
Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults
Published on: April 22, 2022
Plasma metabolomics analysis reveals potential metabolic biomarkers for predicting mushroom poisoning
Yuanping Gu1, Hao Cui2, Zhuange Shi3
1Department of Cardiac Surgery, Fuwai Yunnan Hospital, Chinese Academy of Medical Sciences, Affiliated Cardiovascular Hospital of Kunming Medical University, Kunming, 650102, China; State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China.
Abstract:
The diagnosis of mushroom poisoning (MP) typically relies on patient-reported symptoms and biochemical indicators. However, when patients are in the early stage of poisoning or present with atypical clinical manifestations, traditional diagnostic methods become difficult. Metabolic biomarkers may play a key role in individualized monitoring and early detection. This study aims to identify biomarkers associated with MP using metabolomics to support early clinical diagnosis. Plasma samples were collected from 58 MP patients, 30 healthy controls (HC), and 25 patients with severe traumatic infections (SI). A non-targeted metabolomics analysis was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), detecting 1142 metabolites. Various statistical methods were applied to identify differential metabolites and analyze their correlations with clinical biochemical indicators. Plasma metabolomics analysis revealed significant metabolic differences between MP patients and both HC and SI groups. In total, 34 differential metabolites were identified between MP and HC, and 91 between MP and SI, while 112 differential metabolites were found between SI and HC. Metabolic abnormalities in MP patients were mainly related to cell membrane damage, oxidative stress, inflammatory responses, and lipid metabolism disorders. Among the three groups, 11 metabolites were significantly upregulated and 4 significantly downregulated in MP patients. Notably, four metabolites exhibited excellent predictive capabilities, with AUC values all exceeding 0.9, demonstrating strong discriminatory power for MP. This study identified several metabolites strongly associated with MP, including 5-Oxo-L-norvaline, L-Ergothioneine, Valylvaline, and 2-Arachidonyl Glycerol Ether. These biomarkers demonstrated outstanding predictive performance, providing crucial evidence to support the early diagnosis of mushroom poisoning. This study did not classify mushroom poisoning by type, but used a general analysis method. Whether this approach is useful in practice needs further study.
