Development of Biomarkers for Radiation Biodosimetry and Medical Countermeasures Research: Current Status, Utility, and Regulatory Pathways

Biomarkers are important indicators of biological processes in health or disease. For this reason, they play a critical role in advanced development of radiation biodosimetry tools and medical countermeasures (MCMs). They can aid in the assessment of radiation exposure level, extent of radiation-induced injury, and/or efficacy of an MCM. This meeting report summarizes the presentations and discussions from the 2020 workshop titled, “Biomarkers in Radiation Biodosimetry and Medical Countermeasures,” sponsored by the Radiation and Nuclear Countermeasures Program (RNCP) at the National Institute of Allergy and Infectious Diseases (NIAID). The main goals of this meeting were to: 1. Provide an overview on biomarkers and to focus on the state of science with regards to biomarkers specific to radiation biodosimetry and MCMs; 2. Understand developmental challenges unique to the role of biomarkers in the fields of radiation biodosimetry and MCM development; and 3. Identify existing gaps and needs for translational application.

Breath biomarkers of total body irradiation in non-human primates

Background: Radiation exposure causes oxidative stress, eliciting production of metabolites that are exhaled in the breath as volatile organic compounds (VOCs). We evaluated breath VOCs as potential biomarkers for use in radiation biodosimetry. Methods: Five anesthetized non-human primates receive total body irradiation (TBI) of three daily fractions of 120 cGy per day for three days, resulting in a cumulative dose of 10.8 Gy. Breath samples were collected prior to irradiation and after each radiation fraction, and analyzed with gas chromatography mass spectrometry. Results: TBI elicited a prompt and statistically significant increase in the abundance of several hundred VOCs in the breath, including some that were increased more than five-fold, with100% sensitivity and 100% specificity for radiation exposure. The most significant breath VOC biomarkers of radiation mainly comprised straight-chain n-alkanes (e.g. hexane), as well as methylated alkanes (e.g. 3-methyl-pentane) and alkane derivatives (e.g. 2-butyl-1-octanol), consistent with metabolic products of oxidative stress. An unidentified breath VOC biomarker increased more than ten-fold following TBI, and rose linearly with the total cumulative dose of radiation (R2=0.92). Conclusions: TBI of non-human primates elicited increased production of breath VOCs consistent with increased oxidative stress. These findings provide a rational basis for further evaluation of breath VOC biomarkers in human radiation biodosimetry.

Impact of aging on gene expression response to x-ray irradiation using mouse blood

As a radiation biodosimetry tool, gene expression profiling is being developed using mouse and human peripheral blood models. The impact of dose, dose-rate, and radiation quality has been studied with the goal of predicting radiological tissue injury. In this study, we determined the impact of aging on the gene expression profile of blood from mice exposed to radiation. Young (2 mo) and old (21 mo) male mice were irradiated with 4 Gy x-rays, total RNA was isolated from whole blood 24 h later, and subjected to whole genome microarray analysis. Pathway analysis of differentially expressed genes revealed young mice responded to x-ray exposure by significantly upregulating pathways involved in apoptosis and phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. In contrast, the functional annotation of senescence was overrepresented among differentially expressed genes from irradiated old mice without enrichment of phagocytosis pathways. Pathways associated with hematologic malignancies were enriched in irradiated old mice compared with irradiated young mice. The fibroblast growth factor signaling pathway was underrepresented in older mice under basal conditions. Similarly, brain-related functions were underrepresented in unirradiated old mice. Thus, age-dependent gene expression differences should be considered when developing gene signatures for use in radiation biodosimetry.

The effect of data aggregation on dispersion estimates in count data models

For the modelling of count data, aggregation of the raw data over certain subgroups or predictor configurations is common practice. This is, for instance, the case for count data biomarkers of radiation exposure. Under the Poisson law, count data can be aggregated without loss of information on the Poisson parameter, which remains true if the Poisson assumption is relaxed towards quasi-Poisson. However, in biodosimetry in particular, but also beyond, the question of how the dispersion estimates for quasi-Poisson models behave under data aggregation have received little attention. Indeed, for real data sets featuring unexplained heterogeneities, dispersion estimates can increase strongly after aggregation, an effect which we will demonstrate and quantify explicitly for some scenarios. The increase in dispersion estimates implies an inflation of the parameter standard errors, which, however, by comparison with random effect models, can be shown to serve a corrective purpose. The phenomena are illustrated by γ-H2AX foci data as used for instance in radiation biodosimetry for the calibration of dose-response curves.

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

Triage and medical intervention strategies for unanticipated exposure during a radiation incident benefit from the early, rapid and accurate assessment of dose level. Radiation exposure results in complex and persistent molecular and cellular responses that ultimately alter the levels of many biological markers, including the metabolomic phenotype. Metabolomics is an emerging field that promises the determination of radiation exposure by the qualitative and quantitative measurements of small molecules in a biological sample. This review highlights the current role of metabolomics in assessing radiation injury, as well as considerations for the diverse range of bioanalytical and sampling technologies that are being used to detect these changes. The authors also address the influence of the physiological status of an individual, the animal models studied, the technology and analysis employed in interrogating response to the radiation insult, and variables that factor into discovery and development of robust biomarker signatures. Furthermore, available databases for these studies have been reviewed, and existing regulatory guidance for metabolomics are discussed, with the ultimate goal of providing both context for this area of radiation research and the consideration of pathways for continued development.