{"title":"Plasma Metabolomics Analysis Reveals Potential Metabolic Biomarkers for Predicting Mushroom Poisoning.","authors":"Yuanping Gu, Hao Cui, Zhuange Shi, Hao Jia, Yifan Wang, Siyuan Huang, Xiulin Zhang, Jing Han, Hongmei Wang, Xiao Chen, Guobing Chen, Jiangping Song","doi":"10.1016/j.toxicon.2025.108591","DOIUrl":null,"url":null,"abstract":"<p><p>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 1,142 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.</p>","PeriodicalId":23289,"journal":{"name":"Toxicon","volume":" ","pages":"108591"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxicon","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.toxicon.2025.108591","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
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 1,142 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.
蘑菇中毒的诊断通常依赖于患者报告的症状和生化指标。然而，当患者处于中毒早期或出现不典型临床表现时，传统的诊断方法变得困难。代谢生物标志物可能在个体化监测和早期发现中发挥关键作用。本研究旨在利用代谢组学鉴定与MP相关的生物标志物，以支持早期临床诊断。收集58例MP患者、30例健康对照（HC）和25例严重创伤性感染（SI）患者的血浆样本。采用液相色谱-串联质谱（LC-MS/MS）进行非靶向代谢组学分析，检测到1142种代谢物。采用各种统计学方法鉴定差异代谢物，并分析其与临床生化指标的相关性。血浆代谢组学分析显示MP患者与HC组和SI组之间存在显著的代谢差异。MP和HC之间共鉴定出34种差异代谢物，MP和SI之间鉴定出91种差异代谢物，SI和HC之间鉴定出112种差异代谢物。MP患者代谢异常主要与细胞膜损伤、氧化应激、炎症反应、脂质代谢紊乱有关。三组中，MP患者的11种代谢物显著上调，4种显著下调。值得注意的是，4种代谢物的预测能力优异，AUC值均超过0.9，对MP具有较强的鉴别能力。本研究确定了几种与MP密切相关的代谢物，包括5- o- l -正缬氨酸、l -麦角硫因、缬氨酸和2-花生四烯酰基甘油醚。这些生物标志物表现出出色的预测性能，为支持蘑菇中毒的早期诊断提供了重要证据。本研究不按类型对蘑菇中毒进行分类，而是采用一般分析方法。这种方法在实践中是否有用还有待进一步研究。
期刊介绍：
Toxicon has an open access mirror Toxicon: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. An introductory offer Toxicon: X - full waiver of the Open Access fee.
Toxicon''s "aims and scope" are to publish:
-articles containing the results of original research on problems related to toxins derived from animals, plants and microorganisms
-papers on novel findings related to the chemical, pharmacological, toxicological, and immunological properties of natural toxins
-molecular biological studies of toxins and other genes from poisonous and venomous organisms that advance understanding of the role or function of toxins
-clinical observations on poisoning and envenoming where a new therapeutic principle has been proposed or a decidedly superior clinical result has been obtained.
-material on the use of toxins as tools in studying biological processes and material on subjects related to venom and antivenom problems.
-articles on the translational application of toxins, for example as drugs and insecticides
-epidemiological studies on envenoming or poisoning, so long as they highlight a previously unrecognised medical problem or provide insight into the prevention or medical treatment of envenoming or poisoning. Retrospective surveys of hospital records, especially those lacking species identification, will not be considered for publication. Properly designed prospective community-based surveys are strongly encouraged.
-articles describing well-known activities of venoms, such as antibacterial, anticancer, and analgesic activities of arachnid venoms, without any attempt to define the mechanism of action or purify the active component, will not be considered for publication in Toxicon.
-review articles on problems related to toxinology.
To encourage the exchange of ideas, sections of the journal may be devoted to Short Communications, Letters to the Editor and activities of the affiliated societies.
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