Bridging the gaps: using an NHP model to predict single dose radiation absorption in humans.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Iversen, ES; McCarthy, JM; Bell Burdett, K; Lipton, G; Phillips, G; Dressman, H; Ross, J; Chao, N

Published Date

  • October 29, 2018

Published In

Start / End Page

  • 1 - 10

PubMed ID

  • 30371121

Pubmed Central ID

  • 30371121

Electronic International Standard Serial Number (EISSN)

  • 1362-3095

International Standard Serial Number (ISSN)

  • 0955-3002

Digital Object Identifier (DOI)

  • 10.1080/09553002.2018.1532614

Language

  • eng