• Toby AthersuchEmail author


The exposome concept places substantial weight on the internal chemical milieu of individuals, as this is the primary integrator of the human genome and the wider external environment. Small molecule metabolites of both endogenous and exogenous origin are involved in a plethora of cellular and systemic functions, and collectively contribute to the mechanistic linkage of exposures, responses, and associated adverse outcomes. Temporal and spatial responses of metabolic phenotypes to various environmental stimuli provide a direct report on multiple interacting and conditional processes that are modulated by numerous factors including diet, lifestyle, pharmaceutical use, microbial activity, age, sex, and many others. Measuring and integrating information about the human metabolome represents a critical part of the path toward understanding the environmental determinants of chronic disease.

The size and diversity of the chemical space that metabolites occupy means that measuring the human metabolome via serum, urine, or other biofluids or tissues represents a huge analytical challenge, addressed by the application of high-resolution platforms, typically incorporating liquid- and/or gas-chromatography for separation, and nuclear magnetic resonance spectroscopy and/or mass spectrometry for detection. Advances in the performance of these platforms now permit the measurement of many hundreds or thousands of metabolites, in either targeted or untargeted assays. The focus of this chapter is on the utility of the different analytical platforms, their complementarity, and application to large-scale sample set analysis. Considerations for data analysis and integration with other omics, exposure, and outcome data are discussed, alongside approaches for interpreting findings in the context of the human exposome.


Metabonomics Analytical platforms to measure the exposome NMR Mass spectrometry 


Conflict of Interest

The author confirms no conflict of interest.


TJA is supported by the EU FP7 EXPOsOMICS (grant agreement: 308610) and HELIX (grant agreement: 308333) projects.


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© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of MedicineImperial College LondonLondonUK

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