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Radiotherapy (RT) is a major part of cancer treatment. The reported variability in patient response to this modality can interfere with the continuation of best-possible care, promote side effects, and lead to long-term morbidity. Tools to predict a patient's response to radiation could be highly useful in improving therapeutic outcomes while minimizing unnecessary and toxic exposure to radiation. This study investigates the potential of using molecular biomarkers as predictors of radiosensitivity in clinical practice. We review relative studies researching the positive correlation between various molecular biomarkers and patient radiosensitivity, including DNA damage response and repair proteins, inflammation and apoptosis markers, cell cycle regulators, and other biological markers. The clinical perspectives and applicability of these biomarkers in the prediction of radiosensitivity are also critically discussed. Conclusively, we underline the dynamics of molecular biomarkers to improve the efficacy and safety of radiotherapy in clinical practice and highlight the need for further research in this field. Identification of the most prominent markers is crucial for the personalization of therapies entailing ionizing radiation. [ABSTRACT FROM AUTHOR]

There is a persistent risk of a large-scale malicious or accidental exposure to ionizing radiation that may affect a large number of people. Exposure will consist of both a photon and neutron component, which will vary in magnitude between individuals and is likely to have profound impacts on radiation-induced diseases. To mitigate these potential disasters, there exists a need for novel biodosimetry approaches that can estimate the radiation dose absorbed by each person based on biofluid samples, and predict delayed effects. Integration of several radiation-responsive biomarker types (transcripts, metabolites, blood cell counts) by machine learning (ML) can improve biodosimetry. Here we integrated data from mice exposed to various neutron + photon mixtures, total 3 Gy dose, using multiple ML algorithms to select the strongest biomarker combinations and reconstruct radiation exposure magnitude and composition. We obtained promising results, such as receiver operating characteristic curve area of 0.904 (95% CI: 0.821, 0.969) for classifying samples exposed to ≥ 10% neutrons vs. < 10% neutrons, and R2 of 0.964 for reconstructing photon-equivalent dose (weighted by neutron relative biological effectiveness) for neutron + photon mixtures. These findings demonstrate the potential of combining various -omic biomarkers for novel biodosimetry. [ABSTRACT FROM AUTHOR]

Novel biodosimetry assays for use in preparedness and response to potential malicious attacks or nuclear accidents would ideally provide accurate dose reconstruction independent of the idiosyncrasies of a complex exposure to ionizing radiation. Complex exposures will consist of dose rates spanning the low dose rates (LDR) to very high-dose rates (VHDR) that need to be tested for assay validation. Here, we investigate how a range of relevant dose rates affect metabolomic dose reconstruction at potentially lethal radiation exposures (8 Gy in mice) from an initial blast or subsequent fallout exposures compared to zero or sublethal exposures (0 or 3 Gy in mice) in the first 2 days, which corresponds to an integral time individuals will reach medical facilities after a radiological emergency. Biofluids (urine and serum) were collected from both male and female 9–10-week-old C57BL/6 mice at 1 and 2 days postirradiation (total doses of 0, 3 or 8 Gy) after a VHDR of 7 Gy/s. Additionally, samples were collected after a 2-day exposure consisting of a declining dose rate (1 to 0.004 Gy/min) recapitulating the 7:10 rule-of-thumb time dependency of nuclear fallout. Overall similar perturbations were observed in both urine and serum metabolite concentrations irrespective of sex or dose rate, with the exception of xanthurenic acid in urine (female specific) and taurine in serum (VHDR specific). In urine, we developed identical multiplex metabolite panels (N6, N6,N6-trimethyllysine, carnitine, propionylcarnitine, hexosamine-valine-isoleucine, and taurine) that could identify individuals receiving potentially lethal levels of radiation from the zero or sublethal cohorts with excellent sensitivity and specificity, with creatine increasing model performance at day 1. In serum, individuals receiving a 3 or 8 Gy exposure could be identified from their pre-irradiation samples with excellent sensitivity and specificity, however, due to a lower dose response the 3 vs. 8 Gy groups could not be distinguished from each other. Together with previous results, these data indicate that dose-rate-independent small molecule fingerprints have potential in novel biodosimetry assays. [ABSTRACT FROM AUTHOR]

Novel biodosimetry assays for use in preparedness and response to potential malicious attacks or nuclear accidents would ideally provide accurate dose reconstruction independent of the idiosyncrasies of a complex exposure to ionizing radiation. Complex exposures will consist of dose rates spanning the low dose rates (LDR) to very high-dose rates (VHDR) that need to be tested for assay validation. Here, we investigate how a range of relevant dose rates affect metabolomic dose reconstruction at potentially lethal radiation exposures (8 Gy in mice) from an initial blast or subsequent fallout exposures compared to zero or sublethal exposures (0 or 3 Gy in mice) in the first 2 days, which corresponds to an integral time individuals will reach medical facilities after a radiological emergency. Biofluids (urine and serum) were collected from both male and female 9–10-week-old C57BL/6 mice at 1 and 2 days postirradiation (total doses of 0, 3 or 8 Gy) after a VHDR of 7 Gy/s. Additionally, samples were collected after a 2-day exposure consisting of a declining dose rate (1 to 0.004 Gy/min) recapitulating the 7:10 rule-of-thumb time dependency of nuclear fallout. Overall similar perturbations were observed in both urine and serum metabolite concentrations irrespective of sex or dose rate, with the exception of xanthurenic acid in urine (female specific) and taurine in serum (VHDR specific). In urine, we developed identical multiplex metabolite panels (N6, N6,N6-trimethyllysine, carnitine, propionylcarnitine, hexosamine-valine-isoleucine, and taurine) that could identify individuals receiving potentially lethal levels of radiation from the zero or sublethal cohorts with excellent sensitivity and specificity, with creatine increasing model performance at day 1. In serum, individuals receiving a 3 or 8 Gy exposure could be identified from their pre-irradiation samples with excellent sensitivity and specificity, however, due to a lower dose response the 3 vs. 8 Gy groups could not be distinguished from each other. Together with previous results, these data indicate that dose-rate-independent small molecule fingerprints have potential in novel biodosimetry assays. [ABSTRACT FROM AUTHOR]

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less are known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD. The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events (KEs) of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix (ECM), and vascular remodeling. The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure, and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes. [ABSTRACT FROM AUTHOR]

NASA's planned mission to Mars will result in astronauts being exposed to ~350 mSv/yr of Galactic Cosmic Radiation (GCR). A growing body of data from ground-based experiments indicates that exposure to space radiation doses (approximating those that astronauts will be exposed to on a mission to Mars) impairs a variety of cognitive processes, including cognitive flexibility tasks. Some studies report that 33% of individuals may experience severe cognitive impairment. Translating the results from ground-based rodent studies into tangible risk estimates for astronauts is an enormous challenge, but it would be germane for NASA to use the vast body of data from the rodent studies to start developing appropriate countermeasures, in the expectation that some level of space radiation (SR) -induced cognitive impairment could occur in astronauts. While some targeted studies have reported radiation-induced changes in the neurotransmission properties and/or increased neuroinflammation within space radiation exposed brains, there remains little information that can be used to start the development of a mechanism-based countermeasure strategy. In this study, we have employed a robust label-free mass spectrometry (MS)-based untargeted quantitative proteomic profiling approach to characterize the composition of the medial prefrontal cortex (mPFC) proteome in rats that have been exposed to 15 cGy of 600 MeV/n28Si ions. A variety of analytical techniques were used to mine the generated expression data, which in such studies is typically hampered by low and variable sample size. We have identified several pathways and proteins whose expression alters as a result of space radiation exposure, including decreased mitochondrial function, and a further subset of proteins differs in rats that have a high level of cognitive performance after SR exposure in comparison with those that have low performance levels. While this study has provided further insight into how SR impacts upon neurophysiology, and what adaptive responses can be invoked to prevent the emergence of SR-induced cognitive impairment, the main objective of this paper is to outline strategies that can be used by others to analyze sub-optimal data sets and to identify new information. [ABSTRACT FROM AUTHOR]

Radiation biodosimetry based on transcriptomic analysis of peripheral blood is a valuable tool to detect radiation exposure after a radiological/nuclear event and obtain useful biological information that could predict tissue and organismal injury. However, confounding factors, including chronic inflammation or immune suppression, can potentially obscure the predictive power of the method. Members of the p38 mitogen-activated protein kinase (MAPK) family respond to pro-inflammatory signals and environmental stresses, whereas genetic ablation of the p38 signaling pathway in mice leads to reduced susceptibility to collagen-induced arthritis and experimental autoimmune encephalomyelitis that model human rheumatoid arthritis and multiple sclerosis, respectively. p38 is normally regulated by the MAP3K-MAP2K pathway in mammalian cells. However, in T cells there is an alternative pathway for p38 activation that plays an important role in antigen-receptor-activated T cells and participates in immune and inflammatory responses. To examine the role of p38 in response to radiation, we used two mouse models expressing either a p38α dominant negative (DN) mutation that globally suppresses p38 signaling or a p38αβ double-knock-in (DKI) mutant, which inhibits specifically T-cell receptor activation. We exposed p38 wild-type (p38WT) and mutant male mice to 7 Gy X rays and 24 h later whole blood was isolated subjected to whole-genome microarray and gene ontology analysis. Irradiation of p38WT mice led to a significant overrepresentation of pathways associated with morbidity and mortality, as well as organismal cell death. In contrast, these pathways were significantly underrepresented in p38DN and p38DKI mutant mice, suggesting that p38 attenuation may protect blood cells from the deleterious effects of radiation. Furthermore, radiation exposure in p38 mutant mice resulted in an enrichment of phagocytosis-related pathways, suggesting a role for p38 signaling in restricting phagocytosis of apoptotic cells after irradiation. Finally, despite the significant changes in gene expression, it was still feasible to identify a panel of genes that could accurately distinguish between irradiated and control mice, irrespective of p38 status. [ABSTRACT FROM AUTHOR]

Several diagnostic biodosimetry tools have been in development that may aid in radiological/nuclear emergency responses. Of these, correlating changes in non-invasive biofluid small-molecule signatures to tissue damage from ionizing radiation exposure show promise for inclusion in predictive biodosimetry models. Integral to dose reconstruction has been determining how genotypic variation in the general population will affect model 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. We exposed adult male DKI mice (8–10 weeks old) to 2 and 7 Gy in parallel with wild-type mice and assessed perturbations in urine (days 1, 3, 7) and serum (day 1) using a global metabolomics approach. A multidimensional scaling plot showed excellent separation of radiation-exposed groups in wild-type mice with slightly dampened responses in DKI mice. Validated metabolite panels were developed for urine [N6,N6,N6-trimethyllysine (TML), N1-acetylspermidine, spermidine, carnitine, acylcarnitine C21H35NO5, aminohippuric acid] and serum [phenylalanine, glutamine, propionylcarnitine, lysophosphatidylcholine (LysoPC 14:0), LysoPC (22:5)] to determine the area under the receiver operating characteristic curve (AUROC). 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 mice for both genotypes, however, model performance declined (AUROC < 0.75) between genotypes after irradiation. Overall, these results suggest immunosuppression should not compromise small molecule multiplex panels used in dose reconstruction for biodosimetry. [ABSTRACT FROM AUTHOR]

High-throughput biodosimetry methods to determine exposure to ionizing radiation (IR) that can also be easily scaled to multiple testing sites in emergency situations are needed in the event of malicious attacks or nuclear accidents that may involve a substantial number of civilians. In the event of an improvised nuclear device (IND), a complex IR exposure will have a very high-dose rate (VHDR) component from an initial blast. We have previously addressed low-dose rate (LDR, ≤1 Gy/day) exposures from internal emitters on biofluid small molecule signatures, but further research on the VHDR component of the initial blast is required. Here, we exposed 8- to 10-week-old male C57BL/6 mice to an acute dose of 3 Gy using a reference dose rate of 0.7 Gy/min or a VHDR of 7 Gy/s, collected urine and serum at 1 and 7 d, then compared the metabolite signatures using either untargeted (urine) or targeted (serum) approaches with liquid chromatography mass spectrometry platforms. A Random Forest classification approach showed strikingly similar changes in urinary signatures at 1 d post-irradiation with VHDR samples grouping closer to control samples at 7 d. Identical metabolite panels (carnitine, trigonelline, xanthurenic acid, N6,N6,N6-trimethyllysine, spermine, and hexosamine-valine-isoleucine-OH) could differentiate IR exposed individuals with high sensitivity and specificity (area under the receiver operating characteristic (AUROC) curves 0.89–1.00) irrespective of dose rate at both days. For serum, the top 25 significant lipids affected by IR exposure showed slightly higher perturbations at 0.7 Gy/min vs. 7 Gy/s; however, identical panels showed excellent sensitivity and specificity at 1 d (three hexosylceramides (16:0), (18:0), (24:0), sphingomyelin [26:1], lysophosphatidylethanolamine [22:1]). Mice could not be differentiated from control samples at 7 d for a 3 Gy exposure based on serum lipid signatures. As with LDR exposures, we found that identical biofluid small molecule signatures can identify IR exposed individuals irrespective of dose rate, which shows promise for more universal applications of metabolomics for biodosimetry. [ABSTRACT FROM AUTHOR]

Mass casualty exposure scenarios from an improvised nuclear device are expected to be far more complex than simple photons. Based on the proximity to the explosion and potential shielding, a mixed field of neutrons and photons comprised of up to approximately 30% neutrons of the total dose is anticipated. This presents significant challenges for biodosimetry and for short-term and long-term medical treatment of exposed populations. In this study we employed untargeted metabolomic methods to develop a biosignature in urine and serum from C57BL/6 mice to address radiation quality issues. The signature was developed in males and applied to samples from female mice to identify potential sex differences. Thirteen urinary (primarily amino acids, vitamin products, nucleotides) and 18 serum biomarkers (primarily mitochondrial and fatty acid β oxidation intermediates) were selected and evaluated in samples from day 1 and day 7 postirradiation. Sham-irradiated groups (controls) were compared to an equitoxic dose (3 Gy X-ray equivalent) from X rays (1.2 Gy/min), neutrons (∼1 Gy/h), or neutrons-photons. Results showed a time-dependent increase in the efficiency of the signatures, with serum providing the highest levels of accuracy in distinguishing not only between exposed from non-exposed populations, but also between radiation quality (photon exposures vs. exposures with a neutron component) and in between neutron-photon exposures (5, 15 or 25% of neutrons in the total dose) for evaluating the neutron contribution. A group of metabolites known as acylcarnitines was only responsive in males, indicating the potential for different mechanisms of action in baseline levels and of neutron-photon responses between the two sexes. Our findings highlight the potential of metabolomics in developing biodosimetric methods to evaluate mixed exposures with high sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Mass casualty exposure scenarios from an improvised nuclear device are expected to be far more complex than simple photons. Based on the proximity to the explosion and potential shielding, a mixed field of neutrons and photons comprised of up to approximately 30% neutrons of the total dose is anticipated. This presents significant challenges for biodosimetry and for short-term and long-term medical treatment of exposed populations. In this study we employed untargeted metabolomic methods to develop a biosignature in urine and serum from C57BL/6 mice to address radiation quality issues. The signature was developed in males and applied to samples from female mice to identify potential sex differences. Thirteen urinary (primarily amino acids, vitamin products, nucleotides) and 18 serum biomarkers (primarily mitochondrial and fatty acid β oxidation intermediates) were selected and evaluated in samples from day 1 and day 7 postirradiation. Sham-irradiated groups (controls) were compared to an equitoxic dose (3 Gy X-ray equivalent) from X rays (1.2 Gy/min), neutrons (∼1 Gy/h), or neutrons-photons. Results showed a time-dependent increase in the efficiency of the signatures, with serum providing the highest levels of accuracy in distinguishing not only between exposed from non-exposed populations, but also between radiation quality (photon exposures vs. exposures with a neutron component) and in between neutron-photon exposures (5, 15 or 25% of neutrons in the total dose) for evaluating the neutron contribution. A group of metabolites known as acylcarnitines was only responsive in males, indicating the potential for different mechanisms of action in baseline levels and of neutron-photon responses between the two sexes. Our findings highlight the potential of metabolomics in developing biodosimetric methods to evaluate mixed exposures with high sensitivity and specificity. [ABSTRACT FROM AUTHOR]

White-nose syndrome (WNS) is an emergent wildlife fungal disease of cave-dwelling, hibernating bats that has led to unprecedented mortalities throughout North America. A primary factor in WNS-associated bat mortality includes increased arousals from torpor and premature fat depletion during winter months. Details of species and sex-specific changes in lipid metabolism during WNS are poorly understood and may play an important role in the pathophysiology of the disease. Given the likely role of fat metabolism in WNS and the fact that the liver plays a crucial role in fatty acid distribution and lipid storage, we assessed hepatic lipid signatures of little brown bats (Myotis lucifugus) and big brown bats (Eptesicus fuscus) at an early stage of infection with the etiological agent, Pseudogymnoascus destructans (Pd). Differences in lipid profiles were detected at the species and sex level in the sham-inoculated treatment, most strikingly in higher hepatic triacylglyceride (TG) levels in E. fuscus females compared to males. Interestingly, several dominant TGs (storage lipids) decreased dramatically after Pd infection in both female M. lucifugus and E. fuscus. Increases in hepatic glycerophospholipid (structural lipid) levels were only observed in M. lucifugus, including two phosphatidylcholines (PC [32:1], PC [42:6]) and one phosphatidylglycerol (PG [34:1]). These results suggest that even at early stages of WNS, changes in hepatic lipid mobilization may occur and be species and sex specific. As pre-hibernation lipid reserves may aid in bat persistence and survival during WNS, these early perturbations to lipid metabolism could have important implications for management responses that aid in pre-hibernation fat storage. [ABSTRACT FROM AUTHOR]

Cardiac disease is a frequent and significant adverse event associated with radiotherapy for cancer. Identifying the underlying mechanism responsible for radiation injury to the heart will allow interventions to be developed. In the present study, we tested if local kidney irradiation results in remodeling of the shielded, nontargeted heart. One kidney, two kidneys, or the total body of male WAG and Dahl SS rats were irradiated with 10 Gy of X‐rays. Local kidney irradiation resulted in systemic hypertension, increased BUN, infiltration of T lymphocytes, natural killer cells, and macrophages into the renal cortex and medulla, and renal fibrosis. Local irradiation of kidneys in WAG rats resulted in remodeling in the nontargeted heart after 120 days, manifested by perivascular fibrosis and increased interventricular septal thickness, but was not seen in Dahl SS rats due to a high baseline level of fibrosis in the sham‐irradiated animals. Genetic depletion of T cells mitigated the nephropathy after local kidney irradiation, indicating a role for the immune system in mediating this outcome. Local kidney irradiation resulted in a cascade of pro‐inflammatory cytokines and low‐molecular weight metabolites into the circulation associated with transmission of signals resulting in pathologic remodeling in the nontargeted heart. A new model is proposed whereby radiation‐induced cardiac remodeling in susceptible animals is indirect, with lower hemi body organs such as the kidney exporting factors into the circulation that cause remodeling outside of the irradiated field in the shielded, nontargeted heart. This nontargeted effect appears to be mediated, in part, by the immune system. [ABSTRACT FROM AUTHOR]

Threats of nuclear terrorism coupled with potential unintentional ionizing radiation exposures have necessitated the need for large-scale response efforts of such events, including high-throughput biodosimetry for medical triage. Global metabolomics utilizing mass spectrometry (MS) platforms has proven an ideal tool for generating large compound databases with relative quantification and structural information in a short amount of time. Determining metabolite panels for biodosimetry requires experimentation to evaluate the many factors associated with compound concentrations in biofluids after radiation exposures, including temporal changes, pre-existing conditions, dietary intake, partial- vs. total-body irradiation (TBI), among others. Here, we utilize a nonhuman primate (NHP) model and identify metabolites perturbed in serum after 7.2 Gy TBI without supportive care [LD70/60, hematologic (hematopoietic) acute radiation syndrome (HARS) level H3] at 24, 36, 48 and 96 h compared to preirradiation samples with an ultra-performance liquid chromatography quadrupole time-of-flight (UPLC-QTOF) MS platform. Additionally, we document changes in cytokine levels. Temporal changes observed in serum carnitine, acylcarnitines, amino acids, lipids, deaminated purines and increases in pro-inflammatory cytokines indicate clear metabolic dysfunction after radiation exposure. Multivariate data analysis shows distinct separation from preirradiation groups and receiver operator characteristic curve analysis indicates high specificity and sensitivity based on area under the curve at all time points after 7.2 Gy irradiation. Finally, a comparison to a 6.5 Gy (LD50/60, HARS level H2) cohort after 24 h postirradiation revealed distinctly increased separations from the 7.2 Gy cohort based on multivariate data models and higher compound fold changes. These results highlight the utility of MS platforms to differentiate time and absorbed dose after a potential radiation exposure that may aid in assigning specific medical interventions and contribute as additional biodosimetry tools. [ABSTRACT FROM AUTHOR]

Exposures to ionizing radiation (IR) may either be accidental or intentional, for medical purposes or even through terrorist actions. As certain populations emerge to be more radiosensitive than others, it is imperative to assess those individuals and treat them accordingly. To demonstrate the feasibility of rapid identification of such cases, we utilized the highly radiosensitive mouse model Atm–/– in the C57BL/6 background, and evaluated the urinary responses in 8–10 week old male mice at early time points (4, 24, and 72 h) after exposure to their respective LD50/30 doses [4 Gy for Atm–/–, and 8 Gy for wild type (WT)]. Urinary profiles from heterozygous animals exhibited remarkably similar responses to WT before and after radiation exposure. However, genotypic differences (WT or Atm–/–) were the primary driver to responses to radiation. Putative metabolites were validated through tandem mass spectrometry and included riboflavin, uric acid, d‐ribose, d‐glucose, pantothenic acid, taurine, kynurenic acid, xanthurenic acid, 2‐oxoadipic acid, glutaric acid, 5′‐deoxy‐5′‐methylthioadenosine, and hippuric acid. These metabolites mapped to several interconnected metabolic pathways which suggest that radiosensitive mouse models have underlying differences significantly impacting overall metabolism. This was further amplified by ionizing radiation at different time points. This study further emphasizes that genetically based radiosensitivity is reflected in the metabolic processes, and can be directly observed in urine. These differences in turn can potentially be used to identify individuals that may require altered medical treatment in an emergency radiological situation or modification of a regimen during a radiotherapy session. Environ. Mol. Mutagen. 59:576–585, 2018. © 2018 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Acetylcarnitine has been identified as one of several urinary biomarkers indicative of radiation exposure in adult rhesus macaque monkeys (non-human primates, NHPs). Previous work has demonstrated an up-regulated dose-response profile in a balanced male/female NHP cohort. As a contribution toward the development of metabolomics-based radiation biodosimetry in human populations and other applications of acetylcarnitine screening, we have developed a quantitative, high-throughput method for the analysis of acetylcarnitine. We employed the Sciex SelexIon DMS-MS/MS QTRAP 5500 platform coupled to flow injection analysis (FIA), thereby allowing for fast analysis times of less than 0.5 minutes per injection with no chromatographic separation. Ethyl acetate is used as a DMS modifier to reduce matrix chemical background. We have measured NHP urinary acetylcarnitine from the male cohorts that were exposed to the following radiation levels: control, 2, 4, 6, 7, and 10 Gy. Biological variability, along with calibration accuracy of the FIA-DMS-MS/MS method, indicates LOQ of 20 µM, with observed biological levels on the order of 600 µM and control levels near 10 µM. There is an apparent onset of intensified response in the transition from 6 to 10 Gy. The results demonstrate that FIA-DMS-MS/MS is a rapid, quantitative technique that can be utilized for the analysis of urinary biomarker levels for radiation biodosimetry. [ABSTRACT FROM AUTHOR]

There is a current interest in the development of biodosimetric methods for rapidly assessing radiation exposure in the wake of a large-scale radiological event. This work was initially focused on determining the exposure dose to an individual using biological indicators. Gene expression signatures show promise for biodosimetric application, but little is known about how these signatures might translate for the assessment of radiological injury in radiosensitive individuals, who comprise a significant proportion of the general population, and who would likely require treatment after exposure to lower doses. Using Parp1-/- mice as a model radiation-sensitive genotype, we have investigated the effect of this DNA repair deficiency on the gene expression response to radiation. Although Parp1 is known to play general roles in regulating transcription, the pattern of gene expression changes observed in Parp1-/- mice 24 h postirradiation to a LD50/30 was remarkably similar to that in wild-type mice after exposure to LD50/30. Similar levels of activation of both the p53 and NFκB radiation response pathways were indicated in both strains. In contrast, exposure of wild-type mice to a sublethal dose that was equal to the Parp1-/- LD50/30 resulted in a lower magnitude gene expression response. Thus, Parp1-/- mice displayed a heightened gene expression response to radiation, which was more similar to the wild-type response to an equitoxic dose than to an equal absorbed dose. Gene expression classifiers trained on the wild-type data correctly identified all wild-type samples as unexposed, exposed to a sublethal dose or exposed to an LD50/30. All unexposed samples from Parp1-/- mice were also correctly classified with the same gene set, and 80% of irradiated Parp1-/- samples were identified as exposed to an LD50/30. The results of this study suggest that, at least for some pathways that may influence radiosensitivity in humans, specific gene expression signatures have the potential to accurately detect the extent of radiological injury, rather than serving only as a surrogate of physical radiation dose. [ABSTRACT FROM AUTHOR]

In the event of an improvised nuclear device or 'dirty bomb' in a highly populated area, potentially hundreds of thousands of people will require screening to ensure that exposed individuals receive appropriate treatment. For this reason, there is a need to develop tools for high-throughput radiation biodosimetry. Gene expression represents an emerging approach to biodosimetry and could potentially provide an estimate of both absorbed dose and individual radiation-induced injury. Since approximately 2-4% of humans are thought to be radiosensitive, and would suffer greater radiological injury at a given dose than members of the general population, it is of interest to explore the potential impact of such sensitivity on the biodosimetric gene expression signatures being developed. In this study, we used wild-type mice and genetically engineered mouse models deficient in two DNA repair pathways that can contribute to radiation sensitivity to estimate the maximum effect of differences in radiosensitivity. We compared gene expression in response to a roughly equitoxic (LD50/30) dose of gamma rays in wild-type C57BL/6 (8 Gy) and DNA double-strand break repair-deficient Atm-/- (4 Gy) and Prkdcscid (3 Gy) mutants of C57BL/6. Overall, 780 genes were significantly differentially expressed in wild-type mice one day postirradiation, 232 in Atm-/- and 269 in Prkdcscid. Upstream regulators including TP53 and NFκB were predicted to be activated by radiation exposure in the wild-type mice, but not in either of the DNA repair-deficient mutant strains. There was also a significant muting of the apparent inflammatory response triggered by radiation in both mutant strains. These differences impacted the ability of gene expression signatures developed in wild-type mice to detect potentially fatal radiation exposure in the DNA repair-deficient mice, with the greatest impact on Atm-/- mice. However, the inclusion of mutant mice in gene selection vastly improved performance of the classifiers. [ABSTRACT FROM AUTHOR]

Purpose: Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease. Conclusions: Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research. [ABSTRACT FROM AUTHOR]

The increased threat of terrorism across the globe has raised fears that certain groups will acquire and use radioactive materials to inflict maximum damage. In the event that an improvised nuclear device (IND) is detonated, a potentially large population of victims will require assessment for radiation exposure. While photons will contribute to a major portion of the dose, neutrons may be responsible for the severity of the biologic effects and cellular responses. We investigated differences in response between these two radiation types by using metabolomics and lipidomics to identify biomarkers in urine and blood of wild-type C57BL/6 male mice. Identification of metabolites was based on a 1 Gy dose of radiation. Compared to X rays, a neutron spectrum similar to that encountered in Hiroshima at 1-1.5 km from the epicenter induced a severe metabolic dysregulation, with perturbations in amino acid metabolism and fatty acid β-oxidation being the predominant ones. Urinary metabolites were able to discriminate between neutron and X rays on day 1 as well as day 7 postirradiation, while serum markers showed such discrimination only on day 1. Free fatty acids from omega-6 and omega-3 pathways were also decreased with 1 Gy of neutrons, implicating cell membrane dysfunction and impaired phospholipid metabolism, which should otherwise lead to release of those molecules in circulation. While a precise relative biological effectiveness value could not be calculated from this study, the results are consistent with other published studies showing higher levels of damage from neutrons, demonstrated here by increased metabolic dysregulation. Metabolomics can therefore aid in identifying global perturbations in blood and urine, and effectively distinguishing between neutron and photon exposures. [ABSTRACT FROM AUTHOR]

Metabolomic analysis of easily accessible biofluids has provided numerous biomarkers in urine and blood for biodosimetric purposes. In this pilot study we assessed saliva for its utility in biodosimetry using a mouse model. Mice were exposed to 0.5, 3 and 8 Gy total-body gamma irradiation and saliva was collected on day 1 and 7 postirradiation. Global metabolomic profiling was conducted through liquid chromatography mass spectrometry and metabolites were positively identified using tandem mass spectrometry. Multivariate data analysis revealed distinct metabolic profiles for all groups at day 1, whereas at day 7 the two lower dose profiles appeared to have minimal differences. Metabolites that were identified include amino acids and fatty acids, and intermediates of the nicotinate and nicotinamide metabolism. The specificity and sensitivity of the radiation signature, as expected, was higher for the 8 Gy dose at both time points, as determined through generation of receiver operating characteristic curves. To the best of our knowledge, this is the first metabolomics study in saliva of irradiated mice to demonstrate the utility of this biofluid as a potential matrix for identification of radiation and dose-specific biomarkers. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to link both numeric and structural chromosomal aberrations to the effectiveness of radiotherapy in chemotherapy refractory tumor cells. Materials and methods: Neuroblastoma (LAN-1) and 79HF6 glioblastoma cells derived from patients and their chemoresistant sublines were artificially cultured as neurospheres and irradiated by X-rays and heavy ions sources. All the cell lines were irradiated by Carbon-SIS with LET of 100 keV/μm. However, 79HF6 cells and LAN-1 cells were also irradiated by Carbon-UNILAC with LET of 168 keV/μm and Nickel ions with LET of 174 keV/μm, respectively. The effect of radiation on the survival and proliferation of cells was addressed by standard clonogenic assays. In order to analyze cell karyotype standard Giemsa staining, multicolor fluorescence in situ hybridization (mFISH) and multicolor banding (mBAND) techniques were applied. results: Relative biological effectiveness values of heavy ion beams relative to X-rays at the D10 values were found between 2.3 and 2.6 with Carbon-SIS and Nickel for LAN-1 and between 2.5 and 3.4 with Carbon-SIS and Carbon-UNILAC for 79HF6 cells. Chemorefractory LAN-1RETO cells were found more radioresistant than untreated LAN- 1WT cells. 79HF6RETO glioblastoma cells were found more radiosensitive than cytostatic sensitive cells 79HF6WT. Sphere formation assay showed that LAN-1RETO cells were able to form spheres in serum-free culture, whereas 79HF6 cells could not. Most of 79HF6WT cells revealed a number of 71-90 chromosomes, whereas 79HF6RETO revealed a number of 52-83 chromosomes. The majority of LAN-1WT cells revealed a number of 40-44 chromosomes. mFISH analysis showed some stable aberrations, especially on chromosome 10 as judged by the impossibility to label this region with specific probes. This was corroborated using mBAND analysis. conclusion: Heavy ion irradiation was more effective than X-ray in both cytostatic naive cancer and chemoresistant cell lines. LAN-1RETO chemoresistant neuroblastoma cells were found to be more radioresistant than the cytostatic naive cells (LAN-1WT), whereas this effect was not found in 79HF6 cells. [ABSTRACT FROM AUTHOR]

A reliable radiation risk assessment in space is a mandatory step for the development of countermeasures and long-duration mission planning in human spaceflight. Research in radiobiology provides information about possible risks linked to radiation. In addition, for a meaningful risk evaluation, the radiation exposure has to be assessed to a sufficient level of accuracy. Consequently, both the radiation models predicting the risks and the measurements used to validate such models must have an equivalent precision. Corresponding measurements can be performed both with passive and active devices. The former is easier to handle, cheaper, lighter, and smaller but they measure neither the time dependence of the radiation environment nor some of the details useful for a comprehensive radiation risk assessment. Active detectors provide most of these details and have been extensively used in the International Space Station. To easily access such an amount of data, a single point access is becoming essential. This review presents an ongoing work on the development of a tool that allows obtaining information about all relevant measurements performed with active detectors providing reliable inputs for radiation model validation. [ABSTRACT FROM AUTHOR]

Due to concerns surrounding potential large-scale radiological events, there is a need to determine robust radiation signatures for the rapid identification of exposed individuals, which can then be used to guide the development of compact field deployable instruments to assess individual dose. Metabolomics provides a technology to process easily accessible biofluids and determine rigorous quantitative radiation biomarkers with mass spectrometry (MS) platforms. While multiple studies have utilized murine models to determine radiation biomarkers, limited studies have profiled nonhuman primate (NHP) metabolic radiation signatures. In addition, these studies have concentrated on short-term biomarkers (i.e., <72 h). The current study addresses the need for biomarkers beyond 72 h using a NHP model. Urine samples were collected at 7 days postirradiation (2, 4, 6, 7 and 10 Gy) and processed with ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight (QTOF) MS, acquiring global metabolomic radiation signatures. Multivariate data analysis revealed clear separation between control and irradiated groups. Thirteen biomarkers exhibiting a dose response were validated with tandem MS. There was significantly higher excretion of l-carnitine, l-acetylcarnitine, xanthine and xanthosine in males versus females. Metabolites validated in this study suggest perturbation of several pathways including fatty acid β oxidation, tryptophan metabolism, purine catabolism, taurine metabolism and steroid hormone biosynthesis. In this novel study we detected long-term biomarkers in a NHP model after exposure to radiation and demonstrate differences between sexes using UPLC-QTOF-MS-based metabolomics technology. [ABSTRACT FROM AUTHOR]

Background: Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer deaths worldwide with less than a 6% 5-year survival rate. PDAC is associated with poor prognosis based on the late stage diagnosis of the disease. Current diagnostic tests lack the sensitivity and specificity to identify markers of early staging. Metabolomics has provided biomarkers for various diseases, stressors, and environmental exposures. In this study we utilized the p48-Cre/LSL-KrasG12D mouse model with age-matched wild type mice. This model shows malignant progression to PDAC analogous to the human disease stages via early and late pancreatic intra-epithelial neoplasia (PanIN) lesions. Results: Serum was collected from mice with early PanIN lesions (at 3-5 months) and with late PanIN or invasive PDAC lesions (13-16 months), as determined by histopathology. Metabolomics analysis of the serum samples was conducted through UPLC-TOFMS (Ultra Performance Liquid Chromatography coupled to Time-of-flight Mass Spectrometry). Multivariate data analysis revealed distinct metabolic patterns in serum samples collected during malignant progression towards invasive PDAC. Animals with early or late stage lesions were distinguished from their respective controls with 82.1% and 81.5% accuracy, respectively. This also held up for randomly selected subgroups in the late stage lesion group that showed less variability between animals. One of the metabolites, citrate, was validated through tandem mass spectrometry and showed increased levels in serum with disease progression. Furthermore, serum metabolite signatures from animals with early stage lesions identified controls and animals with late stage lesions with 81.5% accuracy (p<0.01) and vice-versa with 73.2% accuracy (p<0.01). Conclusions: We conclude that metabolomics analysis of serum samples can identify the presence of early and late stage pancreatic cancer. [ABSTRACT FROM AUTHOR]

As space travel is expanding to include private tourism and travel beyond low-Earth orbit, so is the risk of exposure to space radiation. Galactic cosmic rays and solar particle events have the potential to expose space travelers to significant doses of radiation that can lead to increased cancer risk and other adverse health consequences. Metabolomics has the potential to assess an individual's risk by exploring the metabolic perturbations in a biofluid or tissue. In this study, C57BL/6 mice were exposed to 0.5 and 2 Gy of 1 GeV/nucleon of protons and the levels of metabolites were evaluated in urine at 4 h after radiation exposure through liquid chromatography coupled to time-of-flight mass spectrometry. Significant differences were identified in metabolites that map to the tricarboxylic acid (TCA) cycle and fatty acid metabolism, suggesting that energy metabolism is severely impacted after exposure to protons. Additionally, various pathways of amino acid metabolism (tryptophan, tyrosine, arginine and proline and phenylalanine) were affected with potential implications for DNA damage repair and cognitive impairment. Finally, presence of products of purine and pyrimidine metabolism points to direct DNA damage or increased apoptosis. Comparison of these metabolomic data to previously published data from our laboratory with gamma radiation strongly suggests a more pronounced effect on metabolism with protons. This is the first metabolomics study with space radiation in an easily accessible biofluid such as urine that further investigates and exemplifies the biological differences at early time points after exposure to different radiation qualities. [ABSTRACT FROM AUTHOR]

Background: Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer deaths worldwide with less than a 6% 5-year survival rate. PDAC is associated with poor prognosis based on the late stage diagnosis of the disease. Current diagnostic tests lack the sensitivity and specificity to identify markers of early staging. Metabolomics has provided biomarkers for various diseases, stressors, and environmental exposures. In this study we utilized the p48-Cre/LSL-KrasG12D mouse model with age-matched wild type mice. This model shows malignant progression to PDAC analogous to the human disease stages via early and late pancreatic intra-epithelial neoplasia (PanIN) lesions. Results: Serum was collected from mice with early PanIN lesions (at 3-5 months) and with late PanIN or invasive PDAC lesions (13-16 months), as determined by histopathology. Metabolomics analysis of the serum samples was conducted through UPLC-TOFMS (Ultra Performance Liquid Chromatography coupled to Time-of-flight Mass Spectrometry). Multivariate data analysis revealed distinct metabolic patterns in serum samples collected during malignant progression towards invasive PDAC. Animals with early or late stage lesions were distinguished from their respective controls with 82.1% and 81.5% accuracy, respectively. This also held up for randomly selected subgroups in the late stage lesion group that showed less variability between animals. One of the metabolites, citrate, was validated through tandem mass spectrometry and showed increased levels in serum with disease progression. Furthermore, serum metabolite signatures from animals with early stage lesions identified controls and animals with late stage lesions with 81.5% accuracy (p<0.01) and vice-versa with 73.2% accuracy (p<0.01). Conclusions: We conclude that metabolomics analysis of serum samples can identify the presence of early and late stage pancreatic cancer. [ABSTRACT FROM AUTHOR]

The emergence of the threat of radiological terrorism and other radiological incidents has led to the need for development of fast, accurate and noninvasive methods for detection of radiation exposure. The purpose of this study was to extend radiation metabolomic biomarker discovery to humans, as previous studies have focused on mice. Urine was collected from patients undergoing total body irradiation at Memorial Sloan-Kettering Cancer Center prior to hematopoietic stem cell transplantation at 4-6 h postirradiation (a single dose of 1.25 Gy) and 24 h (three fractions of 1.25 Gy each). Global metabolomic profiling was obtained through analysis with ultra performance liquid chromatography coupled to time-of-flight mass spectrometry (TOFMS). Prior to further analyses, each sample was normalized to its respective creatinine level. Statistical analysis was conducted by the nonparametric Kolmogorov-Smirnov test and the Fisher's exact test and markers were validated against pure standards. Seven markers showed distinct differences between pre- and post-exposure samples. Of those, trimethyl- l-lysine and the carnitine conjugates acetylcarnitine, decanoylcarnitine and octanoylcarnitine play an important role in the transportation of fatty acids across mitochondria for subsequent fatty acid β-oxidation. The remaining metabolites, hypoxanthine, xanthine and uric acid are the final products of the purine catabolism pathway, and high levels of excretion have been associated with increased oxidative stress and radiation induced DNA damage. Further analysis revealed sex differences in the patterns of excretion of the markers, demonstrating that generation of a sex-specific metabolomic signature will be informative and can provide a quick and reliable assessment of individuals in a radiological scenario. This is the first radiation metabolomics study in human urine laying the foundation for the use of metabolomics in biodosimetry and providing confidence in biomarker identification based on the overlap between animal models and humans. [ABSTRACT FROM AUTHOR]

Metabolomics on easily accessible biofluids has the potential to provide rapid identification and distinction between stressors and inflammatory states. In the event of a radiological event, individuals with underlying medical conditions could present with similar symptoms to radiation poisoning, prominently nausea, diarrhea, vomiting and fever. Metabolomics of radiation exposure in mice has provided valuable biomarkers, and in this study we aimed to identify biomarkers of lipopolysaccharide (LPS) exposure to compare and contrast with ionizing radiation. LPS treatment leads to a severe inflammatory response and a cytokine storm, events similar to radiation exposure, and LPS exposure can recapitulate many of the responses seen in sepsis. Urine from control mice, LPS-treated mice, and mice irradiated with 3, 8 and 15 Gy of γ rays was analyzed by LCMS, and markers were extracted using SIMCA-P++ and Random Forests. Markers were validated through tandem mass spectrometry against pure chemicals. Five metabolites, cytosine, cortisol, adenine, O-propanoylcarnitine and isethionic acid, showed increased excretion at 24 h after LPS treatment ( P < 0.0001, 0.0393, 0.0393, <0.0001 and 0.0004, respectively). Of these, cytosine, adenine and O-propanoylcarnitine showed specificity to LPS treatment when compared to radiation. On the other hand, increased excretion of cortisol after LPS and radiation treatments indicated a rapid systemic response to inflammatory agents. Isethionic acid excretion, however, showed elevated levels not only after LPS treatment but also after a very high dose of radiation (15 Gy), while additional metabolites showed responsiveness to radiation but not LPS. Metabolomics therefore has the potential to distinguish between different inflammatory responses based on differential ion signatures. It can also provide quick and reliable assessment of medical conditions in a mass casualty radiological scenario and aid in effective triaging. [ABSTRACT FROM AUTHOR]

Purpose: Radiation exposure triggers a complex network of molecular and cellular responses that impacts metabolic processes and alters the levels of metabolites. Such metabolites have potential as biomarkers for radiation dosimetry. This review provides an overview of radiation signalling and metabolism, of metabolomic approaches used in the discovery phase, and of instrumentation with the potential to assess radiation injury in the field. Approach: Recent developments in fast, high-resolution chromatography and mass spectrometry and new data analysis methods allow the quantitative assessment of thousands of metabolites based on biofluids obtained non-invasively. This complex analysis leads to the discovery-phase identification of groups of metabolites useful for screening and biodosimetry by targeted quantitative measurement. Instrumentation for target analysis can be simpler than that used for discovery, so we examine current technologies based on ion mobility. Conclusions: Recent published results and ongoing studies examine the complex changes in the levels of many metabolites caused by radiation exposure, and identify groups of small-molecule biomarkers for radiation biodosimetry. Based on results showing separation orthogonal to mass, chemical noise suppression, and high sensitivity, differential mobility mass spectrometry (DMS-MS) ion mobility spectrometry appears highly promising for the development of deployable instrumentation. [ABSTRACT FROM AUTHOR]

Background: Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a highburden setting. Methodology/Principal Findings: Eleven children with World Health Organization (WHO)-defined severe pneumonia of non-homogeneous aetiology were selected in The Gambia, West Africa, along with community controls. Metabolomic analysis of matched plasma and urine samples was undertaken using Ultra Performance Liquid Chromatography (UPLC) coupled to Time-of-Flight Mass Spectrometry (TOFMS). Biomarker extraction was done using SIMCA-P+ and Random Forests (RF). 'Unsupervised' (blinded) data were analyzed by Principal Component Analysis (PCA), while 'supervised' (unblinded) analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures (OPLS). Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05) between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5'-diphosphate (ADP) were lower; uric acid and L-histidine were lower in urine from cases. The key limitation of this study is its small size. Conclusions/Significance: Metabolomic analysis clearly distinguished severe pneumonia patients from community controls. The metabolites identified are important for the host response to infection through antioxidant, inflammatory and antimicrobial pathways, and energy metabolism. Larger studies are needed to determine whether these findings are pneumonia-specific and to distinguish organism-specific responses. Metabolomics has considerable potential to improve diagnostics for childhood pneumonia. [ABSTRACT FROM AUTHOR]

In the long term, 137Cs is probably the most biologically important agent released in many accidental (or malicious) radiation disasters. It can enter the food chain, and be consumed, or, if present in the environment (e.g. from fallout), can provide external irradiation over prolonged times. In either case, due to the high penetration of the energetic γ rays emitted by 137Cs, the individual will be exposed to a low dose rate, uniform, whole body, irradiation. The VADER (VAriable Dose-rate External 137Cs irradiatoR) allows modeling these exposures, bypassing many of the problems inherent in internal emitter studies. Making use of discarded 137Cs brachytherapy seeds, the VADER can provide varying low dose rate irradiations at dose rates of 0.1 to 1.2 Gy/day. The VADER includes a mouse "hotel", designed to allow long term simultaneous residency of up to 15 mice. Two source platters containing ~ 250 mCi each of 137Cs brachytherapy seeds are mounted above and below the "hotel" and can be moved under computer control to provide constant low dose rate or a varying dose rate mimicking 137Cs biokinetics in mouse or man. We present the VADER design and characterization of its performance over 18 months of use. [ABSTRACT FROM AUTHOR]

Our laboratory and others have use radiation metabolomics to assess responses in order to develop biomarkers reflecting exposure and level of injury. To expand the types of exposure and compare to previously published results, metabolomic analysis has been carried out using serum samples from mice exposed to 137Cs internal emitters. Animals were injected intraperitoneally with 137CsCl solutions of varying radioactivity, and the absorbed doses were calculated. To determine the dose rate effect, serum samples were collected at 2, 3, 5, 7, and 14 days after injection. Based on the time for each group receiving the cumulative dose of 4 Gy, the dose rate for each group was determined. The dose rates analyzed were 0.16 Gy/day (low), 0.69 Gy/day (medium), and 1.25 Gy/day (high). The results indicated that at a cumulative dose of 4 Gy, the low dose rate group had the least number of statistically significantly differential spectral features. Some identified metabolites showed common changes for different dose rates. For example, significantly altered levels of oleamide and sphingosine 1-phosphate were seen in all three groups. On the other hand, the intensity of three amino acids, Isoleucine, Phenylalanine and Arginine, significantly decreased only in the medium dose rate group. These findings have the potential to be used in assessing the exposure and the biological effects of internal emitters. [ABSTRACT FROM AUTHOR]

Due to risks from potential exposures to ionizing radiation (IR), improved radiological countermeasures are required, as well as rapid high-throughput biodosimetry. Genotypic variation in the general population contributes to differences in radiosensitivity that may affect biodosimetry accuracy. Previous studies utilized radiosensitive mutant mouse models (Parp1−/− and Atm−/−) to determine the effects of genotypic deficiency on radiation signatures. Here, we extend this approach by examining changes in the urinary metabolome in a hematopoietic (HP) resistant mouse model (p53−/−) after IR exposure. As p53 is a primary regulator in radiation response and apoptosis, limited hematopoietic stem cell apoptosis leads to reduced mortality at doses of ~8–10 Gy but increased mortality at higher doses (>15 Gy) due to mitotic catastrophe in gastrointestinal (GI) crypt cells. Urine was collected from mice (wild-type (WT), p53+/−, and p53−/−) pre-irradiation and at 4 and 24 h after total body irradiation (TBI) (WT: 8 and 10 Gy; p53−/−: 10 Gy) for metabolic phenotyping using an ultra-performance liquid chromatography mass spectrometry (UPLC-MS) platform. Minimal differences were detected between unirradiated WT, p53+/−, and p53−/− mice. While similar perturbations were observed for metabolites involved in tryptophan, vitamin B6, and histamine pathways, glycine conjugation, and redox metabolism for WT and p53−/− mice after TBI, an overall dampened response was observed in p53-deficient mice. Despite comparable metabolite patterns between genotypes, differentiation was achieved through receiver operating characteristic curve analysis with high specificity and sensitivity for carnitine, N1-acetylspermidine, and creatine. These studies highlight that both attenuated and dampened metabolic responses due to genetic variability in the general population need to be addressed in biodosimetry frameworks. [ABSTRACT FROM AUTHOR]

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper. [ABSTRACT FROM AUTHOR]

Background: Ionizing Radiation (IR) is a known pro-inflammatory agent and in the process of development of biomarkers for radiation biodosimetry, a chronic inflammatory disease condition could act as a confounding factor. Hence, it is important to develop radiation signatures that can distinguish between IR-induced inflammatory responses and pre-existing disease. In this study, we compared the gene expression response of a genetically modified mouse model of inflammatory bowel disease (Il10−/−) with that of a normal wild-type mouse to potentially develop transcriptomics-based biodosimetry markers that can predict radiation exposure in individuals regardless of pre-existing inflammatory condition. Results: Wild-type (WT) and Il10−/− mice were exposed to whole body irradiation of 7 Gy X-rays. Gene expression responses were studied using high throughput whole genome microarrays in peripheral blood 24 h post-irradiation. Analysis resulted in identification of 1962 and 1844 genes differentially expressed (p < 0.001, FDR < 10%) after radiation exposure in Il10−/− and WT mice respectively. A set of 155 genes was also identified as differentially expressed between WT and Il10−/− mice at the baseline pre-irradiation level. Gene ontology analysis revealed that the 155 baseline differentially expressed genes were mainly involved in inflammatory response, glutathione metabolism and collagen deposition. Analysis of radiation responsive genes revealed that innate immune response and p53 signaling processes were strongly associated with up-regulated genes, whereas B-cell development process was found to be significant amongst downregulated genes in the two genotypes. However, specific immune response pathways like MHC based antigen presentation, interferon signaling and hepatic fibrosis were associated with radiation responsive genes in Il10−/− mice but not WT mice. Further analysis using the IPA prediction tool revealed significant differences in the predicted activation status of T-cell mediated signaling as well as regulators of inflammation between WT and Il10−/− after irradiation. Conclusions: Using a mouse model we established that an inflammatory disease condition could affect the expression of many radiation responsive genes. Nevertheless, we identified a panel of genes that, regardless of disease condition, could predict radiation exposure. Our results highlight the need for consideration of pre-existing conditions in the population in the process of development of reliable biodosimetry markers. [ABSTRACT FROM AUTHOR]

Whole body exposure to ionizing radiation damages tissues leading to physical symptoms which contribute to acute radiation syndrome. Radiation biodosimetry aims to determine characteristic early biomarkers indicative of radiation exposure and is necessary for effective triage after an unanticipated radiological incident. Radiation metabolomics can address this aim by assessing metabolic perturbations following exposure. Gas chromatography–mass spectrometry (GC-MS) is a standardized platform ideal for compound identification. We performed GC time-of-flight MS for the global profiling of nonhuman primate urine and serum samples up to 60 d after a single 4 Gy γ-ray total body exposure. Multivariate statistical analysis showed higher group separation in urine vs. serum. We identified biofluid markers involved in amino acid, lipid, purine, and serotonin metabolism, some of which may indicate host microbiome dysbiosis. Sex differences were observed for amino acid fold changes in serum samples. Additionally, we explored mitochondrial dysfunction by tricarboxylic acid intermediate analysis in the first week with a GC tandem quadrupole MS platform. By adding this temporal component to our previous work exploring dose effects at 7 d, we observed the highest fold changes occurring at 3 d, returning closer to basal levels by 7 d. These results emphasize the utility of both MS-based metabolomics for biodosimetry and complementary analytical platforms for increased metabolome coverage. [ABSTRACT FROM AUTHOR]

Heightened threats for nuclear terrorism using improvised nuclear devices (IND) necessitate the development of biodosimetry assays that could rapidly assess thousands of individuals. However, the radiation exposures from an IND may be complex due to mixed fields of neutrons and photons (γ-rays), shielding from buildings, and proximity to the epicenter among others. In this study we utilized lipidomics to analyze serum samples from mice exposed to various percentages of neutrons and X-rays to a total dose of 3 Gy. Triacylglycerides, phosphatidylserines, lysophosphatidylethanolamines, lysophosphatidylcholines (LPCs), sphingolipids, and cholesteryl esters all showed delayed increases at day 7 compared to day 1 after irradiation, while diacylglycerides decreased in mixed field exposures and phosphatidylcholines (PCs) remained largely unchanged. Individual lipid molecules with a high degree of unsaturation exhibited the highest fold changes in mixed fields compared to photons alone. More importantly, the increased ratio of LPCs to PCs of each irradiation group compared to control could be used as a radiation biomarker and highlights the existence of a pro-inflammatory phenotype. The results showed that even a small percentage of neutrons in a mixed field can lead to high biological responses with implications for accurate biodosimetry, triage and medical managements of exposed populations. [ABSTRACT FROM AUTHOR]