Project description:Background: The effects of dose-rate and its implications on radiation biodosimetry methods are not well studied in the context of large-scale radiological scenarios. There are significant health risks to individuals exposed to an acute dose in such an event, but the most realistic scenario would be a combination of exposure to both high and low dose-rates, from both external and internal radioactivity. It is important therefore, to understand the biological response to prolonged exposure; and further, discover biomarkers that can be used to estimate the extent of damage from low-dose rate exposure and propose appropriate clinical treatment. Methods: We irradiated human whole blood ex vivo to three doses, 0.56 Gy, 2.25 Gy and 4.45 Gy, using two dose rates: 1.1Gy/min and 3.1mGy/min. After 24 hours, we isolated RNA from blood cells and hybridized these to Agilent Whole Human genome microarrays. We validated the microarray results using qRT-PCR. Results: Microarray results showed that there were 454 significantly differentially expressed genes after prolonged exposure to all doses. After acute exposure, 598 genes were differentially expressed to all doses combined. Gene ontology terms enriched in both sets of genes were related to immune processes and B cell mediated immunity. Genes responding to acute exposure was also enriched in functions related to natural killer cell activation and cell-to-cell signaling. As expected, p53 pathway was found to be significantly enriched at all doses and by both dose-rates of radiation. Prediction algorithms were able to distinguish between low dose-rate and acute exposures, on the basis of a group of genes. These maybe candidates for preliminary testing as markers for differences in gene expression based on dose-rate. Radiation induced gene expression was measured in ex vivo irradiated human blood, at the 24hr time point after irradiation. Doses (0.56 Gy, 2.2 Gy and 4.45 Gy) were delivered by two dose rates, acute dose rate of 1Gy/min and low dose rate of 3.1 mGy/min.

Project description:In the event of a large-scale radiation exposure incident, accurate and quick assessment of radiation dose would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to limited availability of appropriate human samples, however, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate models to build and test a biodosimetry algorithm for use in humans, we ex vivo-irradiated peripheral blood samples from both humans and rhesus macaques to 0, 2, 5, 6, and 7 Gy, and compared the gene expression profiles 24 hours later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis, and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using non-human primate data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the non-human primate model. A ‘multi-gene’ approach utilizing all gene values for cross-species conversion and applying the converted values on the non-human primate biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primate. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the non-human primate model.

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Homo sapiens

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