Increasing burden of natural background radiation and terrestrial radionuclides is a big threat of radiation exposure to the population at large. It is necessary to develop biomarker of ionizing radiation exposure that can be used for mass screening in the event of a radiological mass casuality incident¹. Metabolomics has already been proven as an excellent developing prospect for capturing diseases specific metabolic signatures as possible biomarkers². Urine analysis provides insights into metabolic perturbations associated with radiation exposure. Our previous studies demonstrated radiation induced pathophysiological perturbation using ¹H NMR based metabolomics of urine³. The aim of the present study is to evaluate the sensitivity and specificity of the urinary metabolites after whole body radiation exposure which can further be used as early predictive marker. A total of 55 C57 male mice (8 to 10 weeks old) were taken and acclimatized for 48 h in polypropylene cages under standard temperature, humidity conditions prior to group allocation and treatment. Twenty seven animals were given 7.5 Gy whole body radiation through Tele ⁶⁰Co irradiation facility (Bhabhatron II) with source operating at 2.496 Gy/min. The remaining 28 animals served as sham irradiated controls. All animal handling and experimental protocols were performed in strict accordance with the guidelines of the Institutional Animal Ethics Committee. Urine samples were collected only at 24 h post irradiation and placed at -80⁰C till NMR Spectroscopy was carried out. 350 µl of centrifuged urine sample was added to 250 µl of deuterated phosphate buffer (pH= 7.4) containing 1 mM TSP and transferred to 5 mm NMR tube. ¹H NMR spectra were acquired at 700 MHz NMR (Varian) spectrometer at 298 K. 1D NOESYPR pulse sequence was used to achieve satisfactory water suppression on all urine samples. Typically 64 scans were acquired with a relaxation delay of 5 s, flip angle of 90° and spectral width 10 ppm. All data sets were zero-filled to 64 K data points and FID was weighted by an exponential function with a 0.3 Hz line broadening prior to Fourier transformation. NMR spectra were segmented into region of 0.04 ppm width. The data was normalized using mean centering and pareto-scaling. Following data normalization multivariate analysis was carried out. Multivariate analysis and Partial least squares-discriminant analysis (PLS-DA) based receiver-operating characteristic (ROC) curve for detection of early predictive marker of radiation was carried out using metaboanalyst software (http://www.metaboanalyst.ca/Metaboanalyst/faces/Home.jsp).The PLS-DA score plot showed clear demarcation of control and irradiated group (Figure. 1). Out of the 24 metabolite identified the most significant metabolites having a Variable Importance of Projection (VIP) score >1 were taurine, citrate, trimethyl amine oxide (TMAO), trimethyl amine (TMA), creatine, α-ketoglutarate (α-KG) (Figure. 2). There was significant reduction in the level of energy metabolites while taurine, TMAO and creatine were found to be increased. To assess the predictive performance of the selected metabolites in the radiation group, the area under curve (AUC) value was calculated. When the combination of all the six metabolites were considered the AUC value was found to be 0.989 (Figure. 3). Among the above 6 metabolites taurine was identified as top ranked candidates, with AUC value of 0.996 and with 100% sensitivity and 90% specificity on the basis of PLS-DA based ROC curve (Figure. 4). The consequences of accidental radiation exposure can be extensive, both physically and physiologically. Radiation injuries affect the body at cellular, molecular, tissue and organ level leading to metabolic perturbations. By employing ¹H NMR based metabolomics and statistical tools, our results demonstrated that biomarker of whole body γ irradiation can be detected and validated. PLS-DA-based ROC curves employed in the present study showed that among the six metabolites identified taurine with highest AUC value could potentially serve as a biomarker for early radiation injury. Similar finding of increase in the level of taurine only in 8 Gy irradiated mice was illustrated in one of the earlier study using UPLC-TOFMS¹. Our previous finding also illustrated increase in the level of taurine in dose dependent manner⁴. Taurine is a well known urinary metabolite of radiation exposure, but its elevation in response to radiation is unknown. Radiation induced tissue injury may results in higher level of circulating sulfur-containing amino acids and thus excess taurine is excreted⁵. The PLS-DA based ROC curve depicted taurine as a biomarker of early radiation injury. This study along with other ‘omics’ technique will be useful to help design strategies for non-invasive radiation biodosimetry through metabolomics in human populations.