Edwin S Iversen1, Janice M McCarthy2, Kirsten Bell Burdett3, Gary Lipton1, Gary Phillips4, Holly Dressman5, Joel Ross4, Nelson Chao4. 1. Department of Statistical Science, Duke University, Durham, NC, USA. 2. Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA. 3. Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA. 4. Department of Hematologic Malignancies & Cell Therapy, Duke University, Durham, NC, USA. 5. Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA.
Abstract
Purpose: Design and characterization of a radiation biodosimetry device are complicated by the fact that the requisite data are not available in the intended use population, namely humans exposed to a single, whole-body radiation dose. Instead, one must turn to model systems. We discuss our studies utilizing healthy, unexposed humans, human bone marrow transplant patients undergoing total body irradiation (TBI), non-human primates subjected to the same irradiation regimen received by the human TBI patients and NHPs given a single, whole-body dose of ionizing radiation.Materials and Methods: We use Bayesian linear mixed models to characterize the association between NHP and human expression patterns in radiation response genes when exposed to a common exposure regimen and across exposure regimens within the same species. Results: We show that population average differences in expression of our radiation response genes from one to another model system are comparable to typical differences between two randomly sampled members of a given model system and that these differences are smaller, on average, for linear combinations of the probe data and for the model-based combinations employed for dose prediction as part of a radiation biodosimetry device.Conclusions: Our analysis suggests that dose estimates based on our gene list will be accurate when applied to humans who have received a single, whole-body exposure to ionizing radiation.
Purpose: Design and characterization of a radiation biodosimetry device are complicated by the fact that the requisite data are not available in the intended use population, namely humans exposed to a single, whole-body radiation dose. Instead, one must turn to model systems. We discuss our studies utilizing healthy, unexposed humans, human bone marrow transplant patients undergoing total body irradiation (TBI), non-human primates subjected to the same irradiation regimen received by the human TBI patients and NHPs given a single, whole-body dose of ionizing radiation.Materials and Methods: We use Bayesian linear mixed models to characterize the association between NHP and human expression patterns in radiation response genes when exposed to a common exposure regimen and across exposure regimens within the same species. Results: We show that population average differences in expression of our radiation response genes from one to another model system are comparable to typical differences between two randomly sampled members of a given model system and that these differences are smaller, on average, for linear combinations of the probe data and for the model-based combinations employed for dose prediction as part of a radiation biodosimetry device.Conclusions: Our analysis suggests that dose estimates based on our gene list will be accurate when applied to humans who have received a single, whole-body exposure to ionizing radiation.
Entities:
Keywords:
Bayesian linear mixed models; Radiation biodosimetry; non-human primate model system; total-body irradiated human bone marrow transplant patient model system
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