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A Serum Small Molecule Biosignature of Radiation Exposure from Total Body Irradiated Patients.

ABSTRACT: The potential for radiological accidents and nuclear terrorism has increased the need for the development of new rapid biodosimetry methods. In addition, in a clinical setting the issue of an individual's radiosensitivity should be taken into consideration during radiotherapy. We utilized metabolomics and lipidomics to investigate changes of metabolites in serum samples following exposure to total body ionizing radiation in humans. Serum was collected prior to irradiation, at 3-8 h after a single dose of 1.25-2 Gy, and at 24 h with a total delivered dose of 2-3.75 Gy. Metabolomics revealed perturbations in glycerophosphocholine, phenylalanine, ubiquinone Q2, and oxalic acid. Alterations were observed in circulating levels of lipids from monoacylglycerol, triacylglycerol, phosphatidylcholine, and phosphatidylglycerol lipid classes. Polyunsaturated fatty acids were some of the most dysregulated lipids, with increased levels linked to proinflammatory processes. A targeted metabolomics approach for eicosanoids was also employed. The results showed a rapid response for proinflammatory eicosanoids, with a dampening of the signal at the later time point. Sex differences were observed in the markers from the untargeted approach but not the targeted method. The ability to identify and quantify small molecules in blood can therefore be utilized to monitor radiation exposure in human populations.

SUBMITTER: Laiakis EC

PROVIDER: S-EPMC5757309 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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A Serum Small Molecule Biosignature of Radiation Exposure from Total Body Irradiated Patients.

Laiakis Evagelia C EC Pannkuk Evan L EL Chauthe Siddheshwar Kisan SK Wang Yi-Wen YW Lian Ming M Mak Tytus D TD Barker Christopher A CA Astarita Giuseppe G Fornace Albert J AJ

Journal of proteome research 20170831 10

The potential for radiological accidents and nuclear terrorism has increased the need for the development of new rapid biodosimetry methods. In addition, in a clinical setting the issue of an individual's radiosensitivity should be taken into consideration during radiotherapy. We utilized metabolomics and lipidomics to investigate changes of metabolites in serum samples following exposure to total body ionizing radiation in humans. Serum was collected prior to irradiation, at 3-8 h after a singl ...[more]

PMID: 28825479

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Project description:In the event of a radiological or nuclear attack, advanced clinical countermeasures are needed for screening and medical management of the exposed population. In such a scenario, minimally invasive biomarkers that can accurately quantify radiation exposure would be useful for triage management by first responders. In this murine study, we evaluated the efficacy of a novel combination of radiation responsive proteins, Flt3 ligand (FL), serum amyloid A (SAA), matrix metalloproteinase 9 (MMP9), fibrinogen beta (FGB) and pentraxin 3 (PTX3) to predict the received dose after whole- or partial-body irradiation. Ten-week-old female C57BL6 mice received a single whole-body or partial-body dose of 18 Gy from a Pantak X-ray source at a dose rate of 2.28 Gy/min. Plasma was collected by cardiac puncture at 24, 48, 72 h and 1 week postirradiation. Plasma protein levels were determined via commercially available ELISA assay. A multivariate discriminant analysis was utilized to generate best-fit dose prediction models for whole-body exposures using the selected biomarker panel and its potential application to partial-body exposures was examined. The combination of values from FL, SAA, MMP9, FGB and PTX3 between 24 h and 1 week postirradiation yielded novel dose-response relationships. For day 1 postirradiation, the best-fit model yielded a predictive accuracy of 81% utilizing FL alone. The use of additional proteins did not enhance the model accuracy whereas, at day 2 postirradiation, the addition of PTX3 and FGB to FL increased the accuracy to 100%. At day 3 the use of FL and PTX3 yielded a predictive accuracy of 93% and at day 7 use of FL and SAA had an accuracy of 90%. Dose prediction of partial-body exposures based on the TBI model had a higher predictive accuracy when the percentage of the body exposed to radiation increased. Our findings indicate that this novel combination of radiation responsive biomarker proteins are an efficient method for predicting radiation exposure and are more accurate when used in concert compared to using any single biomarker protein alone.

Project description:Total body irradiation (TBI) has been demonstrated to alter the intestinal microbiome, but the effects of successful small molecule ionizing radiation mitigators on the intestinal microbiome are not well-known. Our survival experiments examined the effects of anti-cell death radiation mitigators on and in conjunction with the host's microbiota. Mice received 9.25 Gy TBI and then were administered radiation mitigators 24 hours later. Passed stool were collected pre-irradiation, then on days 1, 3, 5, 7, 10, 14, 21, and 30 post-irradiation for 16S rRNA gene (V4 region) sequencing. The Cox proportional hazards (CPH) model was fit with taxonomic composition (time varying covariates) and treatment as predictors. In the first experiment, mice were administered drugs for "granulocyte stimulation and anti-apoptosis" in four protocol combinations: JP4-039 (anti-apoptosis), granulocyte colony-stimulating factor (G-CSF, granulopoietic precursor cell stimulator), both mitigators, and control. Survival improved relative to control (30.0%) for G-CSF (80%, p-value = 0.025), G-CSF/JP4-039 (70%, p-value = 0.084), but not for JP4-039 (50.0%). In the second experiment, mice were administered mitigation drugs "inhibiting programmed cell death" pathways: JP4-039 (anti-apoptosis), necrostatin-1 (anti-necroptosis), and baicalein (anti-ferroptosis), in eight combinations. The survival of JP4-039/baicalein (60.0%, p-value = 0.010) and JP4-039/baicalein/necrostatin-1 (60.0%, p-value = 0.06) treatment combinations were significantly different from the control (26.7%). The JP4-039/necrostatin-1 (46.7%) and baicalein/necrostatin-1 (40.0%) and singlet treatment combinations (26.7%) were not significantly different from the control. Despite differences between the baseline microbiota compositions of the two experiments, consistent changes in composition after irradiation were found: Lactobacillus decreased post-irradiation, relative to baseline. By day 7, microbiota perturbations had incompletely reversed, and no drug-specific differences were identifiable. The CPH model identified Lactobacillus and members of Ruminococcaceae, including Ruminococcus, as protective and Akkermansia as deleterious. By day 30, the microbiota of surviving mice had not returned to baseline, but the differences between experiments suggest the resultant microbiota composition of the survivors are stochastic or batch specific in nature, rather than a requirement for survival. In conclusion, the study determined that key taxa identified in fecal samples, when applied towards the prediction of TBI survival, improves the survival model relative to treatment information alone.

Project description:Introduction Novel biodosimetry assays are needed in the event of radiological/nuclear emergencies for both immediate triage and identifying delayed effects of acute radiation exposure. Genetically engineered mouse models are used to assess how genotypic variation in the general population may affect post-irradiation classification performance. Here, we used a mouse model that lacks the T-cell receptor specific alternative p38 pathway (p38αβY323F, double knock-in [DKI] mice) to determine how attenuated autoimmune and inflammatory responses may affect dose reconstruction. Objectives To determine if deficient alternative p38 activation differentially affects biofluid metabolic signatures post-irradiation compared to wild-type (WT). Methods Untargeted global metabolomics was used to assess biofluid signatures between WT and DKI mice (8 – 10 weeks old) after exposure to total body radiation (0, 2, or 7 Gy). Urine was analyzed in the first week (1, 3, and 7 d) and serum at 1 d. Spectral features of interest were identified using the machine learning algorithm Random Forests and MetaboLyzer. Validated metabolite panels were constructed and classification performance was assessed by determining the area under the receiver operating characteristic curve (AUROC). Results A multidimensional scaling plot showed excellent separation of IR exposed groups in WT with slightly dampened responses in DKI mice. For both urine and serum, excellent sensitivity and specificity (AUROC > 0.90) was observed for 0 Gy vs. 7 Gy groups irrespective of genotype using identical metabolite panels. Similarly, excellent to fair classification (AUROC > 0.75) was observed for ≤ 2 Gy vs. 7 Gy post-irradiation mice for both genotypes, however, model performance declined (AUROC < 0.75) between genotypes post-irradiation. Conclusion Overall, these results suggest less influence of the alternative p38 activation pathway for dose reconstruction compared to other radiosensitive genotypes.

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A Serum Small Molecule Biosignature of Radiation Exposure from Total Body Irradiated Patients.

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A Serum Small Molecule Biosignature of Radiation Exposure from Total Body Irradiated Patients.

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