The metabolomic approach identifies a biological signature of low-dose chronic exposure to cesium 137

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.