A translatable predictor of human radiation exposure.
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Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.
Translational Medical Research
Published Version (Please cite this version)10.1371/journal.pone.0107897
Publication InfoAbedi, M; Chao, Nelson J; Chute, JP; Dressman, HK; Himburg, Heather; Lucas, J; ... Terbrueggen, R (2014). A translatable predictor of human radiation exposure. PLoS One, 9(9). pp. e107897. 10.1371/journal.pone.0107897. Retrieved from https://hdl.handle.net/10161/10977.
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Donald D. and Elizabeth G. Cooke Cancer Research Professor
My research interests are in two broad areas, clinical hematopoietic stem cell and cord blood transplantation and in the laboratory studies related to graft vs. host disease and immune reconstitution. On the clinical side we are currently conducting approximately 50 different clinical protocols ranging from preparatory regimens, supportive care studies and disease specific protocols. Most of these clinical studies are centered around studies of the sources of stem cells and the methods to
I work in Omic and biomarker research at the Center for Applied Genomics and Precision Medicine at Duke University. My current work focuses on infectious disease and cardiovascular disease. I have also worked on cardiovascular risk prediction, classification, and genome-wide association studies. Some of my work uses risk-prediction models and classification in Omic and other settings, and I give workshops on this topic and others. I am interested in any research that s
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