Dai Qingchi,Xi Cong,Yan Yukang,et al.Untargeted metabolomics-based selection and validation of radiation-sensitive metabolites in rat plasma[J].Chinese Journal of Radiological Medicine and Protection,2026,46(6):555-563
Untargeted metabolomics-based selection and validation of radiation-sensitive metabolites in rat plasma
Received:December 24, 2025  
DOI:10.3760/cma.j.cn112271-20251224-00445
KeyWords:Ionizing radiation|Untargeted metabolomics|Absolute quantification|Biomarker|Metabolic pathway
FundProject:国家自然科学基金(82003393);中国疾控中心辐射安全所青年科学研究所长基金(2023-02)
Author NameAffiliationE-mail
Dai Qingchi China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Xi Cong China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Yan Yukang China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Li Shuang China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Cai Tianjing China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Lu Xue China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Wang Xiaorui China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Liu Qingjie China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China  
Zhao Hua China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing 100088, China zhaohua@nirp.chinacdc.cn 
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Abstract::
      Objective To select and preliminarily validate radiation-sensitive metabolites in the plasma of rats exposed to total-body irradiation (TBI), aiming to provide an experimental basis for research on radiation biomarkers. Methods Models of rats subjected to TBI were established using 60Co γ-rays at doses of 0, 4, 8, and 12 Gy. Plasma samples were then collected from these rats at 6 h post-irradiation. Using untargeted metabolomics, differential metabolites were selected from the plasma samples, followed by pathway enrichment analysis. Stable metabolites were then identified and validated using the targeted absolute quantification. Results A total of 323 differential metabolites were identified through untargeted analysis, and they were primarily enriched in pathways such as pyrimidine metabolism. In combination with a literature review, three stable candidate metabolites were selected: taurine, hexanoylcarinitine, and butyrylcarnitine. Targeted absolute quantification result indicate that the three metabolites followed trends consistent with those observed in the untargeted analysis. Among these, taurine exhibited a dose-dependent upregulation, and the fitted dose-effect model was y = 2.337x + 37.54 (F = 6.76, P < 0.05). These metabolites all demonstrated high classification accuracy (AUC > 0.7) in discriminating between the 0 Gy and > 0 Gy irradiation groups. Conclusions Metabolites in rat plasma change significantly at 6 h post-TBI. As radiation-sensitive metabolites, taurine, hexanoylcarnitine, and butyrylcarnitine are relatively stable. Notably, taurine exhibits a clear dose-effect relationship. The combination of untargeted metabolomics-based selection and validation using targeted absolute quantification offers a reliable method for identifying radiation biomarkers.
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