Discovering the metabolic pathway of liver disease by breath mass spectrometry combined with machine learning

IF 3.1 3区 医学 Q2 CHEMISTRY, ANALYTICAL
Xuanzhu Li , Wenbo Zhang , Tongtong Yang , Ying Zhang , Rui Su
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引用次数: 0

Abstract

On account of the low concentration and complex background, most methods for detecting VOCs in exhaled breath samples required preconcentration prior to instrumental analysis. In the current study, a simple and rapid method is developed for analyzing the volatile organic compounds (VOCs) in exhaled breath by extractive electrospray ionization mass spectrometry (EESI-MS). Partial least square discriminant analysis (PLS-DA) using full scan mass spectrum data was used to distinguish exhaled breath of healthy volunteers, chronic hepatitis B patients, and liver failure patients. More VOCs were detected in exhaled breath samples from the volunteers including healthy adults, chronic hepatitis B patients, and liver failure patients by the enclosed EESI-MS method without any sample pretreatment in comparison to the traditional methods. The 9 new breath markers, including 2-hydroxyethanal, 2-methylpropene, butan-2-one, 2,5-dimethylfuran, 2-ethylprop-2-enoic acid, 2,4-dimethylpyridine, 2-methylbutanoic acid, cyclopentanone and 5-hexanolactone, were identified using high resolution tandem mass spectrometry, and some highly correlated metabolic pathways including tryptophan metabolism, tyrosine metabolism, butanoate metabolism, and fatty acid biosynthesis were found. EESI-MS2 method, a promising non-invasive diagnostic tool, is robust and suitable for analysis of VOCs, and may provide further insight into the pathophysiologic processes and pathways leading to chronic hepatitis B and its complications.
呼吸质谱结合机器学习发现肝脏疾病的代谢途径
由于低浓度和复杂的背景,大多数检测呼出样本中挥发性有机化合物的方法都需要在仪器分析之前进行预浓缩。本研究建立了一种简单、快速的萃取电喷雾质谱(EESI-MS)分析呼出气体中挥发性有机化合物(VOCs)的方法。采用全扫描质谱数据的偏最小二乘判别分析(PLS-DA)来区分健康志愿者、慢性乙型肝炎患者和肝功能衰竭患者的呼出气体。未经预处理的封闭EESI-MS法在健康成人、慢性乙型肝炎患者和肝功能衰竭患者的呼气样本中检测到的挥发性有机化合物含量高于传统方法。采用高分辨率串联质谱法鉴定了9种新的呼吸标志物,包括2-羟乙烷、2-甲基丙烯、丁酮-2- 1、2,5-二甲基呋喃、2-乙基丙烯酸、2,4-二甲基吡啶、2-甲基丁酸、环戊酮和5-己内酯,并发现了色氨酸代谢、酪氨酸代谢、丁酸盐代谢和脂肪酸生物合成等高度相关的代谢途径。EESI-MS2方法是一种很有发展前景的无创诊断工具,其功能强大,适合于VOCs的分析,可以进一步了解慢性乙型肝炎及其并发症的病理生理过程和途径。
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来源期刊
CiteScore
6.70
自引率
5.90%
发文量
588
审稿时长
37 days
期刊介绍: This journal is an international medium directed towards the needs of academic, clinical, government and industrial analysis by publishing original research reports and critical reviews on pharmaceutical and biomedical analysis. It covers the interdisciplinary aspects of analysis in the pharmaceutical, biomedical and clinical sciences, including developments in analytical methodology, instrumentation, computation and interpretation. Submissions on novel applications focusing on drug purity and stability studies, pharmacokinetics, therapeutic monitoring, metabolic profiling; drug-related aspects of analytical biochemistry and forensic toxicology; quality assurance in the pharmaceutical industry are also welcome. Studies from areas of well established and poorly selective methods, such as UV-VIS spectrophotometry (including derivative and multi-wavelength measurements), basic electroanalytical (potentiometric, polarographic and voltammetric) methods, fluorimetry, flow-injection analysis, etc. are accepted for publication in exceptional cases only, if a unique and substantial advantage over presently known systems is demonstrated. The same applies to the assay of simple drug formulations by any kind of methods and the determination of drugs in biological samples based merely on spiked samples. Drug purity/stability studies should contain information on the structure elucidation of the impurities/degradants.
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