A multiple-parameter based approach using radiation-induced clinical signs and symptoms, hematology changes, cytogenetic chromosomal aberrations, and molecular biomarkers changes after radiation exposure is used for biodosimetry-based dose assessment. In the current article, relevant milestones from Radiation Research are documented that forms the basis of the current consensus approach for diagnostics after radiation exposure. For example, in 1962 the use of cytogenetic chromosomal aberration using the lymphocyte metaphase spread dicentric assay for biodosimetry applications was first published in Radiation Research. This assay is now complimented using other cytogenetic chromosomal aberration assays (i.e., chromosomal translocations, cytokinesis-blocked micronuclei, premature chromosome condensation, γ-H2AX foci, etc.). Changes in blood cell counts represent an early-phase biomarker for radiation exposures. Molecular biomarker changes have evolved to include panels of organ-specific plasma proteomic and blood-based gene expression biomarkers for radiation dose assessment. Maturation of these assays are shown by efforts for automated processing and scoring, development of point-of-care diagnostics devices, service laboratories inter-comparison exercises, and applications for dose and injury assessments in radiation accidents. An alternative and complementary approach has been advocated with the focus to de-emphasize dose and instead focus on predicting acute or delayed health effects. The same biomarkers used for dose estimation (e.g., lymphocyte counts) can be used to directly predict the later developing severity degree of acute health effects without performing dose estimation as an additional or intermediate step. This review illustrates contributing steps toward these developments published in Radiation Research. 

Radiation Research Society Journal-based Historical Review of the Use of Biomarkers for Radiation Dose and Injury Assessment: Acute Health Effects Predictions

Radiation injury, either from radiotherapy or a mass-casualty event requires a health care system that can efficiently allocate resources to patients. We conducted a comprehensive transcriptome analysis of whole blood from a nonhuman primate model that received upper thoracic radiation (9.8-10.7 Gy). Blood samples were collected at multiple time points, extending up to 270 days post-irradiation with a minimum n = 6 for initial time points (Day 3-Day 40) and a total number of n = 28 primates. No males receiving the higher dose survived to Day 270. Using the Elastic Net model in R we found that pooling biomarkers from Day 3-21 increased our accuracy in discerning survival time, pleural effusion or dose compared to using biomarkers specific to a single day. For survival data, in predicting short term (less than 90 day), medium term (Day 91-269) or long-term survival (Day 270), prediction accuracy using only Day 3 data was 0.14 (95% Confidence Interval (CI) 0.1, 0.19) while pooled data for Male and Female was 0.76 (CI 0.69, 0.82). When pooled data was divided by biological sex, accuracy was 0.7 (CI 0.58, 0.8) for pooled data from Males and 0.84 (CI 0.76, 0.91) for Females. The development of RNA biomarkers as a tool to aid in clinical decision-making could significantly improve patient care in cases of radiation injury, whether from radiotherapy or mass-casualty events. Further validation and clinical translation of these findings could lead to improved patient care and management strategies in cases of radiation exposure. 

Whole-blood RNA biomarkers for predicting survival in non-human primates following thoracic radiation

In this study, to investigate damage-associated biomarkers that can measure γ-irradiation exposure doses, human epidermal melanocytes (HEMs) and keratinocytes (HEKs) exposed to different γ-irradiation doses were analyzed using a caesium-137 biological γ-irradiator and Raman spectrometer. The results showed that as the dose increased, the expression of cell death proteins, such as those involved in apoptosis, autophagy, and necroptosis, increased in the HEKs. However, only apoptosis-related proteins increased in a dose-dependent manner in the HEMs. Intracellular reactive oxygen species (ROS) levels also increased in the HEMs and the HEKs in response to γ-irradiation. Raman spectral analysis was used to quantify protein composition changes in the HEKs and the HEMs exposed to γ-irradiation. These results suggest that the expression levels of various cell death proteins, the level of intracellular ROS, and the changes in cellular membrane components can potentially be used as damage-associated markers for estimating the degree of γ-irradiation exposure in human skin. 

Biomolecular signatures of γ-irradiation exposure: Differential cell death pathways and Raman spectral profiles in human epidermal keratinocytes and melanocytes

High-dose-radiation exposure in a short period of time leads to radiation syndromes characterized by severe acute and delayed organ-specific injury accompanied by elevated organismal morbidity and mortality. Radiation biodosimetry based on gene expression analysis of peripheral blood is a valuable tool to detect exposure to radiation after a radiological/nuclear incident and obtain useful biological information that could predict tissue and organismal injury. However, confounding factors, including chronic inflammation, can potentially obscure the predictive power of the method. GADD45A (Growth arrest and DNA damage-inducible gene a) plays important roles in cell growth control, differentiation, DNA repair, and apoptosis. GADD45A-deficient mice develop an autoimmune disease, similar to human systemic lupus erythematosus, characterized by severe hematological disorders, kidney disease, and premature death. The goal of this study was to elucidate how pre-existing inflammation in mice, induced by GADD45A ablation, can affect radiation biodosimetry. We exposed wild-type and GADD45A knockout male C57BL/6J mice to 7 Gy of X rays and 24 h later RNA was isolated from whole blood and subjected to whole genome microarray and gene ontology analyses. Dose reconstruction analysis using a gene signature trained on gene expression data from irradiated wild-type male mice showed accurate reconstruction of either a 0 Gy or 7 Gy dose with root mean square error of ± 1.05 Gy (R^2 = 1.00) in GADD45A knockout mice. Gene ontology analysis revealed that irradiation of both wild-type and GADD45A-null mice led to a significant overrepresentation of pathways associated with morbidity and mortality, as well as organismal cell death. However, based on their z-score, these pathways were predicted to be more significantly overrepresented in GADD45A-null mice, implying that GADD45A deletion may exacerbate the deleterious effects of radiation on blood cells. Numerous immune cell functions and quantities were predicted to be underrepresented in both genotypes; however, differentially expressed genes from irradiated GADD45A knockout mice predicted an increased deterioration in the numbers of T lymphocytes, as well as myeloid cells, compared with wild-type mice. Furthermore, an overrepresentation of genes associated with radiation-induced hematological malignancies was associated with GADD45A knockout mice, whereas hematopoietic and progenitor cell functions were predicted to be downregulated in irradiated GADD45A knockout mice. In conclusion, despite the significant differences in gene expression between wild-type and GADD45A knockout mice, it is still feasible to identify a panel of genes that could accurately distinguish between irradiated and control mice, irrespective of pre-existing inflammation status. 

Impact of GADD45A on Radiation Biodosimetry Using Mouse Peripheral Blood

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Impact of GADD45A on Radiation Biodosimetry Using Mouse Peripheral Blood