## Journal article: The exposome : a new approach for risk assessment

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2020
##### Editors
Sillé, Fenna C. M.
Karakitsios, Spyros
Kleensang, Andre
Koehler, Kirsten
Maertens, Alexandra
Miller, Gary W.
Prasse, Carsten
Quiros-Alcala, Lesliam
Ramachandran, Gurumurthy
681002
Journal article
Published
##### Abstract
Complementing the human genome with an exposome reflects the increasingly obvious impact of environmental exposure, which far exceeds the role of genetics, on human health. Considering the complexity of exposures and, in addition, the reactions of the body to exposures - i.e., the exposome - reverses classical exposure science where the precise measurement of single or few exposures is associated with specific health or environmental effects. The complete description of an individual's exposome is impossible; even less so is that of a population. We can, however, cast a wider net by foregoing some rigor in assessment and compensating with the statistical power of rich datasets. The advent of omics technologies enables a relatively cheap, high-content description of the biological effects of substances, especially in tissues and biofluids. They can be combined with many other rich data-streams, creating big data of exposure and effect. Computational methods increasingly allow data integration, discerning the signal from the noise and formulating hypotheses of exposure-effect relationships. These can be followed up in a targeted way. With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure (interactions) and health/environment effect associations. This may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an expo-sure-driven approach. Technological developments and synergies between approaches, quality assurance (ultimately as Good Exposome Practices), and the integration of mechanistic thinking will advance this approach.
##### Subject (DDC)
570 Biosciences, Biology
##### Published in
Alternatives to Animal Experimentation : ALTEX ; 37 (2020), 1. - pp. 3-23. - Springer Spektrum. - ISSN 1868-596X. - eISSN 1868-8551
##### Cite This
ISO 690SILLÉ, Fenna C. M., Spyros KARAKITSIOS, Andre KLEENSANG, Kirsten KOEHLER, Alexandra MAERTENS, Gary W. MILLER, Carsten PRASSE, Lesliam QUIROS-ALCALA, Gurumurthy RAMACHANDRAN, Thomas HARTUNG, 2020. The exposome : a new approach for risk assessment. In: Alternatives to Animal Experimentation : ALTEX. Springer Spektrum. 37(1), pp. 3-23. ISSN 1868-596X. eISSN 1868-8551. Available under: doi: 10.14573/altex.2001051
BibTex
@article{Sille2020expos-51111,
year={2020},
doi={10.14573/altex.2001051},
title={The exposome : a new approach for risk assessment},
number={1},
volume={37},
issn={1868-596X},
journal={Alternatives to Animal Experimentation : ALTEX},
pages={3--23},
author={Sillé, Fenna C. M. and Karakitsios, Spyros and Kleensang, Andre and Koehler, Kirsten and Maertens, Alexandra and Miller, Gary W. and Prasse, Carsten and Quiros-Alcala, Lesliam and Ramachandran, Gurumurthy and Hartung, Thomas}
}

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<dcterms:abstract xml:lang="eng">Complementing the human genome with an exposome reflects the increasingly obvious impact of environmental exposure, which far exceeds the role of genetics, on human health. Considering the complexity of exposures and, in addition, the reactions of the body to exposures - i.e., the exposome - reverses classical exposure science where the precise measurement of single or few exposures is associated with specific health or environmental effects. The complete description of an individual's exposome is impossible; even less so is that of a population. We can, however, cast a wider net by foregoing some rigor in assessment and compensating with the statistical power of rich datasets. The advent of omics technologies enables a relatively cheap, high-content description of the biological effects of substances, especially in tissues and biofluids. They can be combined with many other rich data-streams, creating big data of exposure and effect. Computational methods increasingly allow data integration, discerning the signal from the noise and formulating hypotheses of exposure-effect relationships. These can be followed up in a targeted way. With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure (interactions) and health/environment effect associations. This may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an expo-sure-driven approach. Technological developments and synergies between approaches, quality assurance (ultimately as Good Exposome Practices), and the integration of mechanistic thinking will advance this approach.</dcterms:abstract>
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Yes
Yes