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The Metabolomic Approach Identifies a Biological Signature of Low-dose Chronic Exposure to Cesium 137

Authors
  • Grison, Stéphane
  • Martin, Jean-Charles
  • Grandcolas, Line
  • BANZET, Nathalie
  • Blanchardon, Eric
  • Tourlonias, Elie
  • Defoort, Catherine
  • Fave, Gaelle
  • Bott, Romain
  • Dublineau, Isabelle
  • Gourmelon, Patrick
  • Souidi, Maamar
Publication Date
Jan 01, 2012
Identifiers
DOI: 10.1269/jrr.11071
OAI: oai:HAL:hal-02651611v1
Source
HAL-Descartes
Keywords
Language
English
License
Unknown
External links

Abstract

Reports have described apparent biological effects of Cs-137 (the most persistent dispersed radionuclide) irradiation in people living in Chernobyl-contaminated territory. The sensitive analytical technology described here should now help assess the relation of this contamination to the observed effects. A rat model chronically exposed to Cs-137 through drinking water was developed to identify biomarkers of radiation-induced metabolic disorders, and the biological impact was evaluated by a metabolomic approach that allowed us to detect several hundred metabolites in biofluids and assess their association with disease states. After collection of plasma and urine from contaminated and non-contaminated rats at the end of the 9-months contamination period, analysis with a LC-MS system detected 742 features in urine and 1309 in plasma. Biostatistical discriminant analysis extracted a subset of 26 metabolite signals (2 urinary, 4 plasma non-polar, and 19 plasma polar metabolites) that in combination were able to predict from 68 up to 94% of the contaminated rats, depending on the prediction method used, with a misclassification rate as low as 5.3%. The difference in this metabolic score between the contaminated and non-contaminated rats was highly significant (P = 0.019 after ANOVA cross-validation). In conclusion, our proof-of-principle study demonstrated for the first time the usefulness of a metabolomic approach for addressing biological effects of chronic low-dose contamination. We can conclude that a metabolomic signature discriminated Cs-137-contaminated from control animals in our model. Further validation is nevertheless required together with full annotation of the metabolic indicators.

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