SBI – Department of Systems Biology and Bioinformatics
Faculty of Computer Science and Electrical Engineering
University of Rostock
Ulmenstrasse 69 | 18057 Rostock
+49 381 498-7571
System Biology approaches to radiation biodosimetry and the analysis of individual radiosensitivity
Protection of humans from the adverse effects of ionizing radiation is a major goal of the Radiation Protection field. In the case of accidental exposures to radiation the development of effective counter measures requires information on the actual exposure dose as well as knowledge on the individual radiosensitivity of the exposed group of individuals. The major scientific goal of this project is to identify suitable sub-sets of genes which correspond to the expression patterns and correlate this information with radiation dose and radiation quality. In addition, it will investigate the effects of single nucleotide polymorphisms on the individual radiation susceptibility and their influence on the proposed biodosimetry system.
A fast and highly accurate prediction of the exposed radiation dose after an accidental triage is essential for medical decision making. Based on microarray data of irradiated human peripheral blood lymphocytes, we developed an approach that identified a preferably small set of signature genes, which is particular suitable for dose level discrimination at a window of time that would be appropriate for life-saving medical triage.
We successfully generate a small molecular signature that distinguishes clinically relevant radiation doses independently of the time after exposure. Starting with a high number of radiation responsive genes, an information gain based methods helped us to extract a small number of biomarker genes which are highly suitable for radiation dose prediction. Based on these biomarker genes we tested the prediction performances of different machine learning classifiers like k-Nearest Neighbour.
Future work will focus on the analysis of low radiation doses and the dynamics and complexity of signalling pathways interactions in order to understand the molecular mechanisms determining cellular radiation response and individual radiosensitivity.
Ward linkage hierarchical clustering of human peripheral blood samples irradiated with 5 different radiation doses (0 Gy, 0.5 Gy, 1 Gy, 2 Gy and 4 Gy) and measured at three different timepoints after irradiation (6h, 24h, and 48h). Hierarchical clustering showed that gene expression of samples irradiated with 0.5 and 1 Gy resemble each other more closely than gene expression patterns of samples irradiated with 2 and 4 Gy (Fig. 2). Furthermore, the expression of samples irradiated with 0.5 Gy is very different from that of non-irradiated samples.