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.
Keywords: amino acids; analytical chemistry; environment; mass spectrometry; metabolomics.
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