Rapid Low-Cost Paper-based Biodosimetry that reveals individual organ injuries

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Abstract: Increasing threats of nuclear accidents and/or terrorism have triggered an urgent need for the ability to confirm and quantify absorbed radiation doses in a large population exposed to an unknown amount of unintended radiation. An effective triage method has the potential to save thousands of lives. To best utilize the available resources, stepwise triage recommends first using a point-of-care (POC) test that distinguishes between the non-exposed and the exposed population, followed by an assessment of those exposed using high throughput quantitative analysis methods to estimate their absorbed doses of radiation. The ideal POC test will predict acute and delayed radiation injuries to major organs, like bone marrow. To estimate the absorbed dose, biodosimetry measures host biological responses to ionizing radiation. The expression of specific genes alters based on the dose of radiation. Here we use the expression levels of these radiation-responsive genes as biomarkers of exposure to radiation. Previously, we used genomic approaches coupled with an in vivo NHP model to identify many radiation responsive genes and develop a high throughput laboratory test to detect and quantify absorbed dose of radiation within 7 days of post exposure. A new analysis of these data reveals a subset of biomarkers that distinguish exposed from non-exposed individuals. Moreover, one of the hallmarks of radiation exposure is a rapid decay in the total number of lymphocytes. This new panel of biomarkers can quantitatively predict a significant drop in the lymphocyte count at 7 days post exposure, only 24 hours post exposure. We also have technology for converting our gene expression assays into a low-cost paper-based POC test, compatible with screening a large population. By combining our capabilities and currently available biomarkers, we intend to develop a low-cost POC test that; 1) identifies individuals exposed to unintended radiation; 2) qualitatively classifies individuals based on their absorbed dose of radiation; 3) predicts the risk of serious bone marrow injury by calculating their future day 7 lymphocyte counts on day 1. We will execute our project study plan in three steps. First, we will select the best subset of biomarkers by analyzing gene expression data sets and curating literature. Second, we will adapt our paper-based, low-cost, POC test to the critical expression levels of these markers. Finally, we will validate our test and biomarkers using independent unknown samples.