利用超高效液相色谱-串联质谱分析肝内胆管结石的代谢特征。

Cong Wang, Jun Yang, Enliang Li, Shuaiwu Luo, Chi Sun, Yuting Liao, Min Li, Jin Ge, Jun Lei, Fan Zhou, Linquan Wu, Wenjun Liao
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引用次数: 1

摘要

背景与目的:肝内胆管结石的代谢组学研究尚未开展。本研究的目的是利用代谢组学方法表征代谢物的特征,并确定肝结石的潜在生物标志物。方法:采用超高效液相色谱-串联质谱法对30例肝内胆管结石患者和20例健康人的血清代谢物进行了综合分析。统计分析采用单变量(学生t检验)和多变量(正交偏最小二乘判别分析)统计和R语言进行。进行受试者操作特征(ROC)曲线分析,以确定肝内结石的潜在预测因素。结果:鉴定出277种代谢物在肝结石血清组与健康对照组之间存在显著差异。这些代谢物主要是脂质和类脂分子以及氨基酸代谢物。肝内胆管结石血清组类固醇激素生物合成途径丰富。在所有特异性代谢物中,肝结石血清组有75种代谢物过表达。60种代谢物AUC值超过0.70,18-β-甘草次酸、FMH、利福平、PC(4:0/16:2) 4种代谢物AUC值超过0.90。结论:我们首次确定了与肝结石相关的血清代谢物。结果表明,18-β-甘草次酸、FMH、利福平和PC(4:0/16:2)可能在肝内结石治疗中具有潜在的临床应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Metabolic signatures of hepatolithiasis using ultra-high performance liquid chromatography-tandem mass spectrometry.

Background & aims: A metabolomic study of hepatolithiasis has yet to be performed. The purpose of the present study was to characterize the metabolite profile and identify potential biomarkers of hepatolithiasis using a metabolomic approach.

Methods: We comprehensively analyzed the serum metabolites from 30 patients with hepatolithiasis and 20 healthy individuals using ultra-high performance liquid chromatography-tandem mass spectrometry operated in negative and positive ionization modes. Statistical analyses were performed using univariate (Student's t-test) and multivariate (orthogonal partial least-squares discriminant analysis) statistics and R language. Receiver operator characteristic (ROC) curve analysis was performed to identify potential predictors of hepatolithiasis.

Results: We identified 277 metabolites that were significantly different between hepatolithiasis serum group and healthy control serum group. These metabolites were principally lipids and lipid-like molecules and amino acid metabolites. The steroid hormone biosynthesis pathway was enriched in hepatolithiasis serum group. In all specific metabolites, 75 metabolites were over-expressed in hepatolithiasis serum group. The AUC values for 60 metabolites exceeded 0.70, 4 metabolites including 18-β-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) exceeded 0.90.

Conclusions: We have identified serum metabolites that are associated with hepatolithiasis for the first time. 60 potential metabolic biomarkers were identified, 18-β-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) may have the potential clinical utility in hepatolithiasis.

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