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Novel Method for Simultaneously Untargeted Metabolome and Targeted Exposome Analysis in One Injection

暴露的 化学 代谢组 代谢组学 计算生物学 色谱法 药理学 环境卫生 医学 生物
作者
Pengwei Guan,Yuting Wang,Tiantian Chen,H. J. Yang,Xiaolin Wang,Guowang Xu,Xinyu Liu
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:97 (7): 3996-4004
标识
DOI:10.1021/acs.analchem.4c05565
摘要

Serum endogenous metabolites and coexisting exogenous compounds are closely related to human health. Metabolomics often uses high-resolution mass spectrometry (HRMS), but current exposomics studies typically rely on triple quadrupole tandem mass spectrometry due to lower concentrations in the body. As a result, metabolome-exposome-wide association studies (mEWAS) require a combination of untargeted metabolomics and several targeted exposomics methods to measure more exposures, leading to increased time and sample consumption. In this study, a novel method was proposed by leveraging the advantages of recently introduced Zeno MRMHR technology; it allows for the simultaneous acquisition of the metabolome in HRMS and the exposome in multiple reaction monitoring (MRM) modes in one injection. The signal responses for exogenous compounds in MRM were comparable to those of metabolites in HRMS. This method was rigorously validated, and all exogenous standards had relative standard deviations (RSDs) below 20% for intraday and interday repeatability. Over 90% of metabolic features exhibited RSDs below 20% in these assessments. The method also had a broad quantification range, with lower limits of quantification (LLOQ) from 0.1 to 25 ng/mL and higher limits of quantification (HLOQ) from 2.5 to 1000 ng/mL. This approach was demonstratively applied to a type 2 diabetes mellitus cohort to identify serum risk factors and study the metabolome-exposome association. To our knowledge, this study is the first implementation of a unified method for the simultaneous analysis of endogenous metabolites in the untargeted mode and 210 exogenous compounds in the targeted mode in one injection, offering a novel tool for mEWAS research.
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