著者

Stéphane GRISON Jean-Charles MARTIN Line GRANDCOLAS Nathalie BANZET Eric BLANCHARDON Elie TOURLONIAS Catherine DEFOORT Gaëlle FAVÉ Romain BOTT Isabelle DUBLINEAU Patrick GOURMELON Maâmar SOUIDI

出版者

Journal of Radiation Research Editorial Committee

雑誌

Journal of Radiation Research (ISSN:04493060)

巻号頁・発行日

vol.53, no.1, pp.33-43, 2012 (Released:2012-02-02)

参考文献数

52

被引用文献数

20 9

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Reports have described apparent biological effects of 137Cs (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 137Cs 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 137Cs-contaminated from control animals in our model. Further validation is nevertheless required together with full annotation of the metabolic indicators.