performed leave-one-out cross validation studies as we have previously described [27]. A leave one out cross validation involves removing one sample from the dataset, using the remaining samples to develop the model, and then predicting the status of the held out sample. This is then repeated for each sample in the dataset. We have utilized this approach as previously described [27]. A ROC curve analysis was used to define a cut-off for sensitivity and specificity in the predictive models of radiation. Genes found to be predictive of radiation dose were characterized utilizing an in-house program, GATHER (http://meddb01.duhs. duke.edu/gather/). GATHER quantifies the evidence supporting the association between a gene group and an annotation using a Bayes factor [29]. All microarray data files can be found at http:// data.cgt.duke.edu/ChuteRadiation.php and at gene expression omnibus website (GEO [http://www.ncbi.nlm.nih.gov/geo], ac- cession number GSE10640). Results PB gene expression signatures predict ionizing radiation exposure in a heterogeneous population In a previous study, we demonstrated that PB collected from a single strain and gender of mice, at a single time point, contained patterns of gene expression that predicted both prior radiation exposure and distinguished different levels of radiation exposure with a high degree of accuracy [27]. In this study, we sought to determine whether PB gene expression signatures could be identified that predict radiation exposure status within a population that was heterogeneous for genotype, gender and time of sampling. We found that a clear pattern of gene expression could be identified within this heterogeneous population of mice that distinguished non-irradiated animals from those irradiated with 50 cGy, 200 cGy, and 1000 cGy (Figure 1A). To verify that these patterns did indeed represent genes reflecting exposure to radiation, we utilized a leave-one-out cross- validation analysis to assess the ability of the pattern to predict the relevant samples (Figure 1B). The results demonstrate that the pattern selected for distinguishing control animals from those irradiated at various doses has the capacity to predict the status of the samples. The accuracies of prediction of the non-irradiated samples, the 50 cGy-, 200 cGy- and 1000 cGy-irradiated samples were 92%, 78%, 91% and 100%, respectively. Figure 1. Peripheral blood gene expression profiles distinguish irradiated mice within a heterogeneous population (A) The left panel represents a heat map of a 25 gene profile that can predict radiation status. The figure is sorted by dosage (0 cGy, 50cGy, 200cGy, and 1000cGy). High expression is depicted as red, and low expression is depicted as blue. (B) The right panel is a graph of the predicted capabilities of the irradiation signature across all mice (including C57Bl6 and BALB/c strains, males and females and 3 sampling time points) versus a control, non irradiated sample. All predicted probabilities for the controls are listed. doi:10.1371/journal.pone.0001912.g001 Radiation Signatures Sex differences impact the accuracy of gene expression signatures of radiation We next sought to determine the extent to which variables within a heterogeneous population can limit the accuracy of PB gene expression profiling. In order to address the impact of sex difference, healthy adult male and female C57Bl6 mice were irradiated with 50 cGy, 200 cGy, and 1000 cGy and PB was collected at 6 hours post-irradiation, along with PB from non- irradiated control mice (n = 7–10 per group). Patterns of gene expression could be identified in the PB of both male and female mice that appeared to distinguish radiation exposure status (Figure 2A). When the PB signatures from the male C57Bl6 mice were tested against the female PB samples, the heat map analysis suggested less distinction between the non-irradiated and irradi- ated profiles (Figure 2B). Comparable effects were observed when the female PB signatures were applied against male PB samples. A leave-one-out cross-validation analysis demonstrated that the male and female PB signatures of radiation were 100% accurate in predicting the radiation status of PB samples from mice of the same sex (Figure 2C). The male PB signatures also were 100% accurate in predicting the status of the female mice. However, the female PB signatures were less accurate in distinguishing the non- irradiated from 50 cGy irradiated male mice, with improved accuracy in predicting non-irradiated samples from male mice irradiated with higher doses of radiation (200 cGy and 1000 cGy; Figure 2C). The basis for the observed differences in predicting the radiation status of mice across gender differences may be a function of the distinct sets of genes which are represented in the predictors of radiation exposure in males and females (Table S1). Less than 15% of the genes overlapped between the PB metagenes of males and females at each dose of radiation (Table S2). Impact of genotype on prediction of radiation status Since the human population is genetically diverse, we next examined whether gene expression signatures of radiation exposure could accurately predict the status of mice across different genotypes. PB was collected from C57Bl6 and BALB/c mice at 6 hours following 50 cGy, 200 cGy or 1000 cGy and we were able to identify patterns of gene expression which appeared to distinguish the different levels of radiation from the non- irradiated controls within each strain (Figure 3A). However, when the PB gene expression signatures from C57Bl6 mice were tested against BALB/c mice, and vice versa, the gene expression profiles were less distinct (Figure 3B). We then performed a leave-one-out cross-validation analysis in which gene expression profiles from C57Bl6 mice were tested against PB from BALB/c mice and found that the metagene predictors of radiation from C57Bl6 mice displayed 100% accuracy in predicting the status of non-irradiated and irradiated BALB/c mice (Figure 3C). Similarly, application of the PB metagene profiles of radiation generated in BALB/c mice demonstrated 100% accuracy in distinguishing non-irradiated and irradiated C57Bl6 mice. Interestingly, less than 20% of the genes represented within the PB predictors from C57Bl6 mice and BALB/c mice overlapped (Table S3, Table S2), but both predictors were highly accurate in predicting the radiation status of the different strain of mice. Dda3, a p53-inducible gene, which participates in suppression of cell growth [30], was represented in both strains at all radiation doses. The impact of time on PB gene expression signatures of irradiation PB responses to environmental exposures may change over time as a function of changes in PB cellular composition and cellular PLoS ONE | www.plosone.org 3 April 2008 | Volume 3 | Issue 4 | e1912