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Data_Sheet_1_Serum metabolic signatures for acute pulmonary embolism identified by untargeted metabolomics.PDF

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frontiersin.figshare.com2023-06-02 更新2025-03-22 收录
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https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Serum_metabolic_signatures_for_acute_pulmonary_embolism_identified_by_untargeted_metabolomics_PDF/23281898/1
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Background and aimsThe important metabolic features of acute pulmonary embolism (APE) risk stratification and their underlying biological basis remain elusive. Our study aims to develop early diagnostic models and classification models by analyzing the plasma metabolic profile of patients with APE.Materials and methodsSerum samples were collected from 68 subjects, including 19 patients with confirmed APE, 35 patients with confirmed NSTEMI, and 14 healthy individuals. A comprehensive metabolic assessment was performed using ultra-performance liquid chromatography-mass spectrometry based on an untargeted metabolomics approach. In addition, an integrated machine learning strategy based on LASSO and logistic regression was used for feature selection and model building.ResultsThe metabolic profiles of patients with acute pulmonary embolism and NSTEMI is significantly altered relative to that of healthy individuals. KEGG pathway enrichment analysis revealed differential metabolites between acute pulmonary embolism and healthy individuals mainly involving glycerophosphate shuttle, riboflavin metabolism, and glycerolipid metabolism. A panel of biomarkers was defined to distinguish acute pulmonary embolism, NSTEMI, and healthy individuals with an area under the receiver operating characteristic curve exceeding 0.9 and higher than that of D-dimers.ConclusionThis study contributes to a better understanding of the pathogenesis of APE and facilitates the discovery of new therapeutic targets. The metabolite panel can be used as a potential non-invasive diagnostic and risk stratification tool for APE.

背景与目标:急性肺栓塞(APE)的重要代谢特征及其潜在的生物学基础尚不明确。本研究旨在通过分析APE患者的血浆代谢谱,开发早期诊断模型和分类模型。材料与方法:从68名受试者中收集血清样本,包括19名确诊为APE的患者、35名确诊为非ST段抬高型心肌梗死(NSTEMI)的患者和14名健康个体。采用基于非靶向代谢组学的超高效液相色谱-质谱联用技术进行全面的代谢评估。此外,采用基于LASSO和逻辑回归的集成机器学习策略进行特征选择和模型构建。结果:与健康个体相比,急性肺栓塞和非ST段抬高型心肌梗死患者的代谢谱发生显著改变。KEGG通路富集分析揭示了急性肺栓塞与健康个体之间的差异代谢物,主要涉及甘油磷酸穿梭、核黄素代谢和甘油酯代谢。定义了一系列生物标志物,以区分急性肺栓塞、非ST段抬高型心肌梗死和健康个体,其受试者工作特征曲线下面积超过0.9,且高于D-二聚体。结论:本研究有助于更深入地理解APE的发病机制,并促进了新的治疗靶点的发现。代谢物面板可作为潜在的无创诊断和风险分层工具,用于急性肺栓塞。
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