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Updated: May 1, 2026

Measuring DNA Damage and Repair in Mouse Splenocytes After Chronic In Vivo Exposure to Very Low Doses of Beta- and Gamma-Radiation
Published on: July 3, 2015
Targeted lipidomics-based study of radiation-induced metabolite profiles changes in plasma of total body irradiation
Qi Chen1,2, Hua Zhao1, Cong Xi1
1China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, P.R. China.
Purpose:
Lipidomics is an important tool for triaging exposed individuals, and helps early adoption of prevention and control strategies. The purpose of this study was to screen significantly perturbed lipids between pre- and post-irradiation of human plasma samples after total body irradiation (TBI) and explore potential radiation biomarkers for early radiation classification.
Methods:
Plasma samples were collected before and after irradiation from 22 hospitalized cases of acute myeloid leukemia (AML) prepared for bone marrow transplantation. Acute total-body γ irradiation was performed at doses of 0, 4, 8, and 12 Gy. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) with multiple reaction monitoring (MRM) method was utilized. Self-paired studies before and after irradiation were performed to screen potential lipid categorization markers and markers of dose-response relationships for radiation perturbation in humans. Based on the screened potential markers, a human TBI dose estimation model was developed.
Results:
In total, 426 individual lipids from 14 major classes were quantified and 152 potential biomarkers with categorical characteristics were screened. A total of 80 lipids (32 TGs, 29 SMs, 9 FAs, 5 CEs, 5 PIs) were upregulated at 4 Gy, and a total of 91 lipids (39 SMs, 18 TGs, 15 HexCers, 7 CEs, 6 Cers, 3 LacCers, 2 LPEs, 1 PI) were upregulated at 12 Gy. Comparison of the ROC curves between the non-exposed and exposed groups at different doses showed AUC values ranging from 0.807 to 0.876. The metabolic pathways of potential lipid markers are mainly sphingolipid and glycerolipid metabolism, unsaturated fatty acid biosynthesis, fatty acid degradation and biosynthesis. Among the 13 dose-dependent radiosensitive lipids, CE (20:5), CE (18:1) and PI (18:2/18:2) were gradually incorporated into the TBI dose estimation model.
Conclusion:
This study suggested that it was feasible to acquire quantitative lipid biomarker panels using targeted lipidomics platforms for rapid, high-throughput triage. Lipidomics strategies for radiation biodosimetry in humans were established with lipid biomarkers with good dose-response relationship.
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