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Gene expression-based biodosimetry for radiological incidents : assessment of dose and time after radiation exposure

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Abstract
Purpose: In order to ensure efficient use of medical resources following a radiological incident, there is an urgent need or high-throughput time-efficient biodosimetry tools. In the present study, we tested the applicability of a gene expression signature for the prediction of exposure dose as well as the time elapsed since irradiation. Materials and methods: We used whole blood samples from seven healthy volunteers as reference samples (X-ray doses: 0, 25, 50, 100, 500, 1000, and 2000 mGy; time points: 8, 12, 24, 36 and 48 h) and samples from seven other individuals as ‘blind samples’ (20 samples in total). Results: Gene expression values normalized to the reference gene without normalization to the unexposed controls were sufficient to predict doses with a correlation coefficient between the true and the predicted doses of 0.86. Importantly, we could also classify the samples according to the time since exposure with a correlation coefficient between the true and the predicted time point of 0.96. Because of the dynamic nature of radiation-induced gene expression, this feature will be of critical importance for adequate gene expression-based dose prediction in a real emergency situation. In addition, in this study we also compared different methodologies for RNA extraction available on the market and suggested the one most suitable for emergency situation which does not require on-spot availability of any specific reagents or equipment. Conclusions: Our results represent an important advancement in the application of gene expression for biodosimetry purposes.
Keywords
Biodosimetry, gene expression, radiation, time point prediction, dose prediction, DICENTRIC CHROMOSOME ASSAY, MESSENGER-RNA REDUCTION, WHOLE-BLOOD SAMPLES, PERIPHERAL-BLOOD, IN-VITRO, EX-VIVO, BIOLOGICAL DOSIMETRY, STEM-CELLS, PROFILES, BIOMARKERS

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MLA
Macaeva, Ellina et al. “Gene Expression-based Biodosimetry for Radiological Incidents : Assessment of Dose and Time After Radiation Exposure.” INTERNATIONAL JOURNAL OF RADIATION BIOLOGY 95.1 (2019): 64–75. Print.
APA
Macaeva, E., Mysara, M., De Vos, W., Baatout, S., & Quintens, R. (2019). Gene expression-based biodosimetry for radiological incidents : assessment of dose and time after radiation exposure. INTERNATIONAL JOURNAL OF RADIATION BIOLOGY, 95(1), 64–75.
Chicago author-date
Macaeva, Ellina, Mohamed Mysara, Winnok De Vos, Sarah Baatout, and Roel Quintens. 2019. “Gene Expression-based Biodosimetry for Radiological Incidents : Assessment of Dose and Time After Radiation Exposure.” International Journal of Radiation Biology 95 (1): 64–75.
Chicago author-date (all authors)
Macaeva, Ellina, Mohamed Mysara, Winnok De Vos, Sarah Baatout, and Roel Quintens. 2019. “Gene Expression-based Biodosimetry for Radiological Incidents : Assessment of Dose and Time After Radiation Exposure.” International Journal of Radiation Biology 95 (1): 64–75.
Vancouver
1.
Macaeva E, Mysara M, De Vos W, Baatout S, Quintens R. Gene expression-based biodosimetry for radiological incidents : assessment of dose and time after radiation exposure. INTERNATIONAL JOURNAL OF RADIATION BIOLOGY. 2019;95(1):64–75.
IEEE
[1]
E. Macaeva, M. Mysara, W. De Vos, S. Baatout, and R. Quintens, “Gene expression-based biodosimetry for radiological incidents : assessment of dose and time after radiation exposure,” INTERNATIONAL JOURNAL OF RADIATION BIOLOGY, vol. 95, no. 1, pp. 64–75, 2019.
@article{8600308,
  abstract     = {Purpose: In order to ensure efficient use of medical resources following a radiological incident, there is an urgent need or high-throughput time-efficient biodosimetry tools. In the present study, we tested the applicability of a gene expression signature for the prediction of exposure dose as well as the time elapsed since irradiation.
Materials and methods: We used whole blood samples from seven healthy volunteers as reference samples (X-ray doses: 0, 25, 50, 100, 500, 1000, and 2000 mGy; time points: 8, 12, 24, 36 and 48 h) and samples from seven other individuals as ‘blind samples’ (20 samples in total). 
Results: Gene expression values normalized to the reference gene without normalization to the unexposed controls were sufficient to predict doses with a correlation coefficient between the true and the predicted doses of 0.86. Importantly, we could also classify the samples according to the time since exposure with a correlation coefficient between the true and the predicted time point of 0.96. Because of the dynamic nature of radiation-induced gene expression, this feature will be of critical importance for adequate gene expression-based dose prediction in a real emergency situation. In addition, in this study we also compared different methodologies for RNA extraction available on the market and suggested the one most suitable for emergency situation which does not require on-spot availability of any specific reagents or equipment.
Conclusions: Our results represent an important advancement in the application of gene expression for biodosimetry purposes.},
  author       = {Macaeva, Ellina and Mysara, Mohamed and De Vos, Winnok and Baatout, Sarah and Quintens, Roel},
  issn         = {0955-3002},
  journal      = {INTERNATIONAL JOURNAL OF RADIATION BIOLOGY},
  keywords     = {Biodosimetry,gene expression,radiation,time point prediction,dose prediction,DICENTRIC CHROMOSOME ASSAY,MESSENGER-RNA REDUCTION,WHOLE-BLOOD SAMPLES,PERIPHERAL-BLOOD,IN-VITRO,EX-VIVO,BIOLOGICAL DOSIMETRY,STEM-CELLS,PROFILES,BIOMARKERS},
  language     = {eng},
  number       = {1},
  pages        = {64--75},
  title        = {Gene expression-based biodosimetry for radiological incidents : assessment of dose and time after radiation exposure},
  url          = {http://dx.doi.org/10.1080/09553002.2018.1511926},
  volume       = {95},
  year         = {2019},
}

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