Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

Comparison of Novel Proteomic Expression Profiles for Radiation Exposure in Male and Female C57BL6 Mice

There is a need for point-of-care diagnostics for future mass casualty events involving radiation exposure. The development of radiation exposure and dose prediction algorithms for biodosimetry is needed for screening of large populations during these scenarios, and exploration of the potential effects which sex, age, genetic heterogeneity, and physiological comorbidities may have on the utility of biodosimetry diagnostics is needed. In the current study, proteomic profiling was used to examine sex-specific differences in age-matched C57BL6 mice on the blood proteome after radiation exposure, and the usefulness of development and application of biodosimetry algorithms using both male and female samples. Male and female mice between 9-11 weeks of age received a dose of total-body irradiation (TBI) of either 2, 4 or 8 Gy and plasma was collected at days 1, 3 and 7 postirradiation. Plasma was then screened using the SomaScan v4.1 assay for ∼7,000 protein analytes. A subset panel of protein biomarkers demonstrated significant (FDR < 0.05 and |logFC| > 0.2) changes in expression after radiation exposure. All proteins were used for feature selection to build predictive models of radiation exposure using different sample and sex-specific cohorts. Both binary (prediction of any radiation exposure) and multidose (prediction of specific radiation dose) model series were developed using either female and male samples combined or only female or only male samples. The binary series (models 1, 2 and 3) and multidose series (models 4, 5 and 6) included female/male combined, female only and male only respectively. Detectable values were obtained for all ∼7,000 proteins included in the SomaScan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies in the binary model series was ∼100% at the model training level, and when tested with fresh samples, 97.9% for model 1 (female and male) and 100% for model 2 (female only) and model 3 (male only). When sex-specific models 2 and 3 were tested with the opposite sex, the overall predictive accuracy rate dropped to 62.5% for model 2 and remained 100% for model 3. The overall predictive accuracy rate in the multidose model series was 100% for all models at the model training level and, when tested with fresh samples, 83.3%, 75% and 83.3% for Multidose models 4-6, respectively. When sex-specific model 5 (female only) and model 6 (male only) were tested with the opposite sex, the overall predictive accuracy rate dropped to 52.1% and 68.8%, respectively. These models represent novel predictive panels of radiation-responsive proteomic biomarkers and illustrate the utility and necessity of considering sex-specific differences in development of radiation biodosimetry prediction algorithms. As sex-specific differences were observed in this study, and as use of point-of-care radiation diagnostics in future mass casualty settings will necessarily include persons of both sexes, consideration of sex-specific variation is essential to ensure these diagnostic tools have practical utility in the field.

Paper-Based Vertical Flow Immunoassay for the Point-of-Care Multiplex Detection of Radiation Dosimetry Genes

In a nuclear or radiological incident, first responders must quickly and accurately measure radiation exposure among civilians as medical countermeasures are radiation dose-dependent and time-sensitive. Although several approaches have been explored to measure absorbed radiation dose, there is an important need to develop point-of-care (POC) bioassay devices that can be used immediately to triage thousands of individuals potentially exposed to radiation. Here we present a proof-of-concept study showing the use of a paper-based vertical flow immunoassay (VFI) to detect radiation dosimetry genes. Using labeled primers during amplification and a multiplex membrane, our results showed that the nucleic acid VFI can simultaneously detect two biodosimetry genes, CDKN1A and DDB2, as well as one housekeeping gene MRPS5. The assay demonstrated good linearity and precision with an inter- and intra-assay coefficient of variance <20% and <10%, respectively. Moreover, the assay showed its ability to discriminate non-irradiated controls (0 Gy) from irradiated samples (1 + 2 Gy) with an overall sensitivity of 62.5% and specificity of 100% (AUC = 0.8672, 95% CI: 0.723-1.000; p = 0.004). Interestingly, the gene combination also showed a dose-dependent response for 0, 1, and 2 Gy, similar to data obtained by real-time PCR benchmark. These preliminary results suggest that a VFI platform can be used to detect simultaneously multiple genes that can be then quantified, thus offering a new approach for a POC biodosimetry assay that could be rapidly deployed on-site to test a large population and help triage and medical management after radiological event.

Urinary Metabolomics for the Prediction of Radiation-Induced Cardiac Dysfunction

Survivors of acute radiation exposures are likely to experience delayed effects that manifest as injury in late-responding organs such as the heart. Noninvasive indicators of radiation-induced cardiac dysfunction are important in the prediction and diagnosis of this disease. In this study, we aimed to identify urinary metabolites indicative of radiation-induced cardiac damage by analyzing previously collected urine samples from a published study. The samples were collected from male and female wild-type (C57BL/6N) and transgenic mice constitutively expressing Activated Protein C (APCHi), a circulating protein with potential cardiac protective properties, that were exposed to 9.5 Gy of γ-rays. We utilized LC-MS-based metabolomics and lipidomics for the analysis of urine samples collected at 24 h, 1 week, 1 month, 3 months, and 6 months post-irradiation. Radiation caused perturbations in the TCA cycle, glycosphingolipid metabolism, fatty acid oxidation, purine catabolism, and amino acid metabolites, which were more prominent in wild-type (WT) mice compared to APCHi mice, suggesting a differential response between the two genotypes. After combining genotypes and sexes, we identified a multi-analyte urinary panel at early post-irradiation time points that predicted heart dysfunction using a logistic regression model with a discovery validation study design. These studies demonstrate the utility of a molecular phenotyping approach to develop a urinary biomarker panel predictive of delayed effects of ionizing radiation. It is important to note that no live mice were used or assessed in this study; instead, we focused solely on analyzing previously collected urine samples.

Application of radiation omics in the development of adverse outcome pathway networks: an example of radiation-induced cardiovascular disease

BACKGROUND

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 is 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.

RESULTS

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 of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix and vascular remodeling.

CONCLUSIONS

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.

Biofluid Metabolomics and Lipidomics of Mice Exposed to External Very High-Dose Rate Radiation

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.

Metabolomics as a valid analytical technique in environmental exposure research: application and progress

BACKGROUND

In recent years, studies have shown that exposure to environmental pollutants (e.g., radiation, heavy metal substances, air pollutants, organic pollutants) is a leading cause of human non-communicable diseases. The key to disease prevention is to clarify the harmful mechanisms and toxic effects of environmental pollutants on the body. Metabolomics is a high-sensitivity, high-throughput omics technology that can obtain detailed metabolite information of an organism. It is a crucial tool for gaining a comprehensive understanding of the pathway network regulation mechanism of the organism. Its application is widespread in many research fields such as environmental exposure assessment, medicine, systems biology, and biomarker discovery.

AIM OF REVIEW

Recent findings show that metabolomics can be used to obtain molecular snapshots of organisms after environmental exposure, to help understand the interaction between environmental exposure and organisms, and to identify potential biomarkers and biological mechanisms.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the application of metabolomics to understand the biological effects of radiation, heavy metals, air pollution, and persistent organic pollutants exposure, and examines some potential biomarkers and toxicity mechanisms.

Small Molecule Signatures of Mice Lacking T-cell p38 Alternate Activation, a Model for Immunosuppression Conditions, after Total-Body Irradiation

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, 4-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.

An integrative chemometric approach and correlative metabolite networking of LC-MS and 1H NMR based urine metabolomics for radiation signatures

The increasing threat of nuclear terrorism or radiological accident has made high throughput radiation biodosimetry a requisite for the immediate response for triage. Owing to detection of subtle alterations in biological pathways before the onset of clinical conditions, metabolomics has become an important tool for studying biomarkers and the related mechanisms for radiation induced damage. Here, we have attempted to combine two detection techniques, LC-MS and ¹H NMR spectroscopy, to obtain a comprehensive metabolite profile of urine at 24 h following lethal (7.5 Gy) and sub-lethal (5 Gy) irradiation in mice. Integrated data analytics using multiblock-OPLSDA (MB-OPLSDA), correlation networking and pathway analysis was used to identify metabolic disturbances associated with radiation exposure. MB-OPLSDA revealed better clustering and separation of irradiated groups compared with controls without overfitting (p-value of CV-ANOVA: 1.5 × 10^-3). Metabolites identified through MB-OPLSDA, namely, taurine, creatine, citrate and 2-oxoglutarate, were found to be dose independent markers and further support and validate our earlier findings as potential radiation injury biomarkers. Integrated analysis resulted in the enhanced coverage of metabolites and better correlation networking in energy, taurine, gut flora, L-carnitine and nucleotide metabolism observed post irradiation in urine. Our study thus emphasizes the major advantage of using the two detection techniques along with integrated analysis for better detection and comprehensive understanding of disturbed metabolites in biological pathways.

Clinical Applications of Biological Dosimetry in Patients Exposed to Low Dose Radiation Due to Radiological, Imaging or Nuclear Medicine Procedures

Radiation dosimetric biomarkers have found applications beyond radiation protection area and now are actively introduced into clinical practice. Cytogenetic assays appeared to be a valuable tool for individualized quantifying radiation effects in patients, with high capability for assessing genotoxicity of various medical exposure modalities and providing meaningful radiation dose estimates for prognoses of radiation-related cancer risk. This review summarized current data on the use of biological dosimetry methods in patients undergoing various medical irradiations to low doses. The highlighted topics include basic aspects of biological dosimetry and its limitations in the range of low radiation doses, and main patterns of in vivo induction of radiation biomarkers in clinical exposure scenarios, occurring in X-ray diagnostics, computed tomography, interventional radiology, low dose radiotherapy, and nuclear medicine (internally administered ¹³¹I and other radiopharmaceuticals). Additionally, several specific issues, examined by biodosimetry techniques, are analysed, such as contrast media effect, radiation response in pediatric patients, impact of magnetic resonance imaging, evaluation of radioprotectors, detection of patients' abnormal intrinsic radiosensitivity and dose estimation in persons involved in medical radiation incidents. A prognosis of possible directions for further improvements in this area includes the automation of cytogenetic analysis, introduction of molecular biodosimeters and development of multiparametric biodosimetry platforms. A potential approach to the advanced biodosimetry of internal exposure and/or low dose external irradiation is suggested; this can be a multiparametric platform based on the combination of the γ-H2AX foci, dicentric, and translocation assays, each applied in the optimum postexposure time range, with the amalgamation of the dose estimates. The study revealed the necessity of further research, which might clarify medical radiation safety concerns for patients via using stringent biodosimetry methodology.

Biofluid Metabolomics of Mice Exposed to External Low-Dose Rate Radiation in a Novel Irradiation System, the Variable Dose-Rate External 137Cs Irradiator

An important component of ionizing radiation (IR) exposure after a radiological incident may include low-dose rate (LDR) exposures either externally or internally, such as from ¹³⁷Cs deposition. In this study, a novel irradiation system, VAriable Dose-rate External ¹³⁷Cs irradiatoR (VADER), was used to expose male and female mice to a variable LDR irradiation over a 30 d time span to simulate fall-out-type exposures in addition to biofluid collection from a reference dose rate (0.8 Gy/min). Radiation markers were identified by untargeted metabolomics and random forests. Mice exposed to LDR exposures were successfully identified from control groups based on their urine and serum metabolite profiles. In addition to metabolites commonly perturbed after IR exposure, we identified and validated a novel metabolite (hexosamine-valine-isoleucine-OH) that increased up to 150-fold after LDR and 80-fold after conventional exposures in urine. A multiplex panel consisting of hexosamine-valine-isoleucine-OH with other urinary metabolites (N6,N6,N6-trimethyllysine, carnitine, 1-methylnicotinamide, and α-ketoglutaric acid) achieved robust classification performance using receiver operating characteristic curve analysis, irrespective of the dose rate or sex. These results show that in terms of biodosimetry, dysregulated energy metabolism is associated with IR exposure for both LDR and conventional IR exposures. These mass spectrometry data have been deposited to the NIH data repository via Metabolomics Workbench with study IDs ST001790, ST001791, ST001792, ST001793, and ST001806.

Radiobiological and social considerations following a radiological terrorist attack; mechanisms, detection and mitigation: review of new research developments

PURPOSE

This review focuses on recent research in understanding the different aspects of what society should expect from a radiological attack. Although some scenarios of a radiologic event can be impossible to be prepared for, the effort put toward educating and better preparing for these types of events can help minimize some of the issues. The different areas discussed in this review include radioisotopes of concern, detection of radiation dose, biological effects of ionizing radiation exposures, low dose effects, targeted and non-targeted effects (NTE), psychological effects, mitigations, with a brief mention of other considerations such as medical preparedness, communication, policy implications and ethical issues. This review also discusses solutions to rectify the issues faced at hand that may come up in the event of a radiologic terrorist attack.

CONCLUSIONS

A review of recent work in the area shows that a multi-layered and interdisciplinary approach is needed to prepare for a radiological terrorist attack. As well as medical preparedness, the approach needs to include sociological and psychological planning as well as an understanding of ethical issues. Since the likely 'dirty bomb' scenarios may involve low dose exposures to high numbers of people, a much better theoretical and practical understanding of low dose radiobiology and the development of robust low dose exposure biomarkers is needed as part of an integrated plan.

Metabolomics of Multiorgan Radiation Injury in Non-human Primate Model Reveals System-wide Metabolic Perturbations

ABSTRACT

Exposure to ionizing radiation following a nuclear or radiological incident results in potential acute radiation syndromes causing sequelae of multi-organ injury in a dose- and time-dependent manner. Currently, medical countermeasures against radiation injury are limited, and no biomarkers have been approved by regulatory authorities. Identification of circulating plasma biomarkers indicative of radiation injury can be useful for early triage and injury assessment and in the development of novel therapies (medical countermeasures). Aims of this study are to (1) identify metabolites and lipids with consensus signatures that can inform on mechanism of injury in radiation-induced multi-organ injury and (2) identify plasma biomarkers in non-human primate (NHP) that correlate with tissues (kidney, liver, lung, left and right heart, jejunum) indicative of radiation injury, assessing samples collected over 3 wk post-exposure to 12 Gy partial body irradiation with 2.5% bone marrow sparing. About 180 plasma and tissue metabolites and lipids were quantified through Biocrates AbsoluteIDQ p180 kit using liquid chromatography and mass spectrometry. System-wide perturbations of specific metabolites and lipid levels and pathway alterations were identified. Citrulline, Serotonin, PC ae 38:2, PC ae 36:2, and sum of branched chain amino acids were identified as potential biomarkers of radiation injury. Pathway analysis revealed consistent changes in fatty acid oxidation and metabolism and perturbations in multiple other pathways.

NMR-Based Metabolomics in Investigation of the Radiation Induced Changes in Blood Serum of Head and Neck Cancer Patients and Its Correlation with the Tissue Volumes Exposed to the Particulate Doses

In the present study, we analyze the nuclear magnetic resonance (NMR) blood serum metabolic profiles of 106 head and neck squamous cell carcinoma (HNSCC) patients during radio (RT) and concurrent radio-chemotherapy (CHRT). Four different fractionation schemes were compared. The blood samples were collected weekly, from the day before the treatment until the last week of CHRT/RT. The NMR spectra were acquired on A Bruker 400 MHz spectrometer at 310 K and analyzed using multivariate methods. Seven metabolites were found significantly to be altered solely by radiotherapy: N-acetyl-glycoprotein (NAG), N-acetylcysteine, glycerol, glycolate and the lipids at 0.9, 1.3 and 3.2 ppm. The NMR results were correlated with the tissue volumes receiving a particular dose of radiation. The influence of the irradiated volume on the metabolic profile is weak and mainly limited to sparse correlations with the inflammatory markers, creatinine and the lymphocyte count in RT and the branched-chain amino-acids in CHRT. This is probably due to the optimal planning and delivery of radiotherapy improving sparing of the surrounding normal tissues and minimizing the differences between the patients (caused by the tumor location and size).

Metabolomics-based predictive biomarkers of radiation injury and countermeasure efficacy: current status and future perspectives

INTRODUCTION

There is an urgent need for specific and sensitive bioassays to augment biodosimetric assessments of unwanted and excessive radiation exposures that originate from unexpected nuclear/radiological events, including nuclear accidents, acts of terrorism, or the use of a radiological dispersal device. If sufficiently intense, such ionizing radiation exposures are likely to impact normal metabolic processes within the cells and organs of the body, thus inducing multifaceted biological responses.

AREAS COVERED

This review covers the application of metabolomics, an emerging and promising technology based on quantitative and qualitative determinations of small molecules in biological samples for the rapid assessment of an individual's exposure to ionizing radiation. Recent advancements in the analytics of high-resolution chromatography, mass spectrometry, and bioinformatics have led to untargeted (global) and targeted (quantitative phase) approaches to identify biomarkers of radiation injury and countermeasure efficacy. Biomarkers are deemed essential for both assessing the radiation exposure levels and for extrapolative processes involved in determining scaling factors of a given radiation countering medicinal between experimental animals and humans.

EXPERT OPINION

The discipline of metabolomics appears to be highly informative in assessing radiation exposure levels and for identifying biomarkers of radiation injury and countermeasure efficacy.

Acute Radiation Syndrome and the Microbiome: Impact and Review

Study of the human microbiota has been a centuries-long endeavor, but since the inception of the National Institutes of Health (NIH) Human Microbiome Project in 2007, research has greatly expanded, including the space involving radiation injury. As acute radiation syndrome (ARS) is multisystemic, the microbiome niches across all areas of the body may be affected. This review highlights advances in radiation research examining the effect of irradiation on the microbiome and its potential use as a target for medical countermeasures or biodosimetry approaches, or as a medical countermeasure itself. The authors also address animal model considerations for designing studies, and the potential to use the microbiome as a biomarker to assess radiation exposure and predict outcome. Recent research has shown that the microbiome holds enormous potential for mitigation of radiation injury, in the context of both radiotherapy and radiological/nuclear public health emergencies. Gaps still exist, but the field is moving forward with much promise.