Go Young-Mi, Walker Douglas I, Liang Yongliang, Uppal Karan, Soltow Quinlyn A, Tran ViLinh, Strobel Frederick, Quyyumi Arshed A, Ziegler Thomas R, Pennell Kurt D, Miller Gary W, Jones Dean P
*Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia 30322;
*Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia 30322; †Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155;
Toxicol Sci. 2015 Dec;148(2):531-43. doi: 10.1093/toxsci/kfv198. Epub 2015 Sep 9.
The exposome is the cumulative measure of environmental influences and associated biological responses throughout the lifespan, including exposures from the environment, diet, behavior, and endogenous processes. A major challenge for exposome research lies in the development of robust and affordable analytic procedures to measure the broad range of exposures and associated biologic impacts occurring over a lifetime. Biomonitoring is an established approach to evaluate internal body burden of environmental exposures, but use of biomonitoring for exposome research is often limited by the high costs associated with quantification of individual chemicals. High-resolution metabolomics (HRM) uses ultra-high resolution mass spectrometry with minimal sample preparation to support high-throughput relative quantification of thousands of environmental, dietary, and microbial chemicals. HRM also measures metabolites in most endogenous metabolic pathways, thereby providing simultaneous measurement of biologic responses to environmental exposures. The present research examined quantification strategies to enhance the usefulness of HRM data for cumulative exposome research. The results provide a simple reference standardization protocol in which individual chemical concentrations in unknown samples are estimated by comparison to a concurrently analyzed, pooled reference sample with known chemical concentrations. The approach was tested using blinded analyses of amino acids in human samples and was found to be comparable to independent laboratory results based on surrogate standardization or internal standardization. Quantification was reproducible over a 13-month period and extrapolated to thousands of chemicals. The results show that reference standardization protocol provides an effective strategy that will enhance data collection for cumulative exposome research. In principle, the approach can be extended to other types of mass spectrometry and other analytical methods.
暴露组是指个体在其整个生命周期中所接触到的环境影响及相关生物学反应的累积量度,包括来自环境、饮食、行为和内源性过程的暴露。暴露组研究面临的一个主要挑战在于开发强大且经济实惠的分析程序,以测量个体在一生中所经历的广泛暴露及其相关的生物学影响。生物监测是一种用于评估体内环境暴露负荷的既定方法,但在暴露组研究中使用生物监测通常受到与单个化学物质定量相关的高成本限制。高分辨率代谢组学(HRM)使用超高分辨率质谱仪,只需进行最少的样品制备,即可支持对数千种环境、饮食和微生物化学物质进行高通量相对定量分析。HRM还能测量大多数内源性代谢途径中的代谢物,从而同时测量对环境暴露的生物学反应。本研究探讨了定量策略,以提高HRM数据在累积暴露组研究中的实用性。研究结果提供了一种简单的参考标准化方案,即通过与同时分析的、已知化学物质浓度的混合参考样品进行比较,来估计未知样品中单个化学物质的浓度。该方法通过对人类样品中的氨基酸进行盲法分析进行了测试,结果发现与基于替代标准化或内标标准化的独立实验室结果相当。在13个月的时间内,定量结果具有可重复性,并可外推至数千种化学物质。结果表明,参考标准化方案提供了一种有效的策略,将增强累积暴露组研究的数据收集。原则上,该方法可扩展到其他类型的质谱分析和其他分析方法。