Life Sciences Mass Spectrometry, Department of Inorganic and Analytical Chemistry, University of Geneva, Quai Ernest Ansermet 24, 1211 Geneva, Switzerland.
Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, The Netherlands.
J Clin Epidemiol. 2021 Jul;135:10-16. doi: 10.1016/j.jclinepi.2021.02.008. Epub 2021 Feb 9.
The objective of this study was to investigate whether clinical metabolomics, which is increasingly applied in population-based and epidemiological studies, can be used to provide analytical evidence of exposures, and whether such information can be useful to strengthen and/or complement corresponding clinical database entries, taking drug use as an example.
Liquid chromatography-mass spectrometry (LC-MS) metabolomics analyses were performed on urine from 100 randomly-selected control subjects (50% females) from the TransplantLines Food and Nutrition Biobank and Cohort Study (NCT identifier 'NCT02811835'), and drugs were identified through spectral library searching and targeted signal extraction.
In 83 subjects for whom drug use information was available, 22 expected and 26 unexpected prescription-only drugs were identified, while 28 expected prescription-only drugs remained undetected. In addition, 7 prescription-only drugs were found in 17 subjects for whom drug use information was unavailable, and 58 over-the-counter drugs were identified in all 100 subjects.
Molecular evidence for many drugs could be retrieved from LC-MS metabolomics data, which could be useful to complement and strengthen epidemiological databases given that considerable discrepancies were found between analytically-identified drugs and drugs listed in the available clinical database.
本研究旨在探讨临床代谢组学（越来越多地应用于基于人群和流行病学研究）是否可用于提供暴露的分析证据，以及此类信息是否可用于加强和/或补充相应的临床数据库条目，以药物使用为例。
对来自 TransplantLines 食品和营养生物库和队列研究（NCT 标识符“NCT02811835”）的 100 名随机选择的对照受试者（50%为女性）的尿液进行液相色谱-质谱（LC-MS）代谢组学分析，并通过光谱库搜索和靶向信号提取来识别药物。
在有药物使用信息的 83 名受试者中，鉴定出 22 种预期和 26 种非预期的处方药，而 28 种预期的处方药仍未检出。此外，在有药物使用信息不可用的 17 名受试者中发现了 7 种处方药，在所有 100 名受试者中鉴定出 58 种非处方药。
从 LC-MS 代谢组学数据中可以检索到许多药物的分子证据，鉴于分析鉴定的药物与现有临床数据库中列出的药物之间存在相当大的差异，这些证据可用于补充和加强流行病学数据库。
