Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA), and Faculty of Pharmacy and Food Sciences, University of Barcelona, 08028 Barcelona, Spain.
CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Barcelona, Spain.
Anal Chem. 2020 Oct 20;92(20):13767-13775. doi: 10.1021/acs.analchem.0c02008. Epub 2020 Sep 30.
The exposome, defined as the cumulative measure of external exposures and associated biological responses throughout the lifespan, has emerged in recent years as a cornerstone in biomedical sciences. Metabolomics stands out here as one of the most powerful tools for investigating the interplay between the genetic background, exogenous, and endogenous factors within human health. However, to address the complexity of the exposome, novel methods are needed to characterize the human metabolome. In this work, we have optimized and validated a multianalyte metabolomics platform for large-scale quantitative exposome research in plasma and urine samples, based on the use of simple extraction methods and high-throughput metabolomic fingerprinting. The methodology enables, for the first time, the simultaneous characterization of the endogenous metabolome, food-related metabolites, pharmaceuticals, household chemicals, environmental pollutants, and microbiota derivatives, comprising more than 1000 metabolites in total. This comprehensive and quantitative investigation of the exposome is achieved in short run times, through simple extraction methods requiring small-sample volumes, and using integrated quality control procedures for ensuring data quality. This metabolomics approach was satisfactorily validated in terms of linearity, recovery, matrix effects, specificity, limits of quantification, intraday and interday precision, and carryover. Furthermore, the clinical potential of the methodology was demonstrated in a dietary intervention trial as a case study. In summary, this study describes the optimization, validation, and application of a multimetabolite platform for comprehensive and quantitative metabolomics-based exposome research with great utility in large-scale epidemiological studies.
近年来,外核组学作为生物医学科学的基石之一出现,其被定义为整个生命周期中外源暴露和相关生物反应的累积度量。代谢组学在此类研究中是一个强有力的工具,它可以用于研究遗传背景、外源性和内源性因素之间的相互作用,从而促进人类健康。然而,为了解决外核组的复杂性,需要新的方法来描述人类代谢组。在这项工作中,我们基于简单的提取方法和高通量代谢组指纹图谱,优化并验证了一种用于在血浆和尿液样本中进行大规模定量外核组学研究的多分析物代谢组学平台。该方法首次能够同时描述内源性代谢组、与食物相关的代谢物、药物、家用化学品、环境污染物和微生物衍生代谢物,总共涵盖了 1000 多种代谢物。通过使用小样本量的简单提取方法和集成的质量控制程序来确保数据质量,这种代谢组学方法可以在短时间内实现对外核组的综合和定量研究。该代谢组学方法在直线性、回收率、基质效应、特异性、定量限、日内和日间精密度以及交叉污染方面都得到了令人满意的验证。此外,该方法的临床应用潜力还通过一个饮食干预试验进行了案例研究。总之,本研究描述了一种用于综合和定量基于代谢组学的外核组学研究的多代谢物平台的优化、验证和应用,该方法在大规模流行病学研究中具有广泛的应用价值。