Literature DB >> 32672951

Is It Realistic to Propose Determination of a Lifetime Internal Exposome?

Gabriele Sabbioni1,2, Jean-Daniel Berset1, Billy W Day3,4.   

Abstract

Biomonitoring of xenobiotics has been performed for many years in occupational and environmental medicine. It has revealed hidden exposures and the exposure of workers could be reduced. Although most of the toxic effects of chemicals on humans were discovered in workers, the scientific community has more recently focused on environmental samples. In several countries, urinary and blood samples have been collected and analyzed for xenobiotics. Health, biochemical, and clinical parameters were measured in the biomonitoring program of the Unites States. The data were collected and evaluated as group values, comparing races, ages, and gender. The term exposome was created in order to relate chemical exposure to health effects together with the terms genome, proteome, and transcriptome. Internal exposures were mostly established with snapshot measurements, which can lead to an obvious misclassification of the individual exposures. Albumin and hemoglobin adducts of xenobiotics reflect the exposure of a larger time frame, up to 120 days. It is likely that only a small fraction of xenobiotics form such adducts. In addition, adduct analyses are more work intensive than the measurement of xenobiotics and metabolites in urine and/or blood. New technology, such as high-resolution mass spectrometry, will enable the discovery of new compounds that have been overlooked in the past, since over 300,000 chemicals are commercially available and most likely also present in the environment. Yet, quantification will be challenging, as it was for the older methods. At this stage, determination of a lifetime internal exposome is very unrealistic. Instead of an experimental approach with a large number of people, which is economically and scientifically not feasible, in silico methods should be developed further to predict exposure, toxicity, and potential health effects of mixtures. The computer models will help to focus internal exposure investigations on smaller groups of people and smaller number of chemicals.

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Year:  2020        PMID: 32672951     DOI: 10.1021/acs.chemrestox.0c00092

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


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