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Comparison of novel proteomic expression profiles for radiation exposure in male and female C57BL6 mice

ABSTRACT: Purpose: There is a need for point-of-care diagnostics for future mass casualty events involving radiation exposure. The development of radiation exposure and dose prediction algorithms for biodosimetry is needed for screening of large populations during these scenarios, and exploration of the potential effects which sex, age, genetic heterogeneity, and physiological comorbidities may have on the utility of biodosimetry diagnostics is needed. In the current study, proteomic profiling was used to examine sex specific differences in age matched C57BL6 mice on the blood proteome following radiation exposure and the usefulness of development and application of biodosimetry algorithms using both male and female samples. Methods: C57BL6 male and female mice between 9-11 weeks of age received a single total body radiation exposure of either 2, 4 or 8 Gy with plasma collection at days 1, 3 and 7 post-irradiation. Plasma was then screened using the SomaScan v4.1 assay for ~7000 protein analytes. A subset panel of protein biomarkers demonstrated significant (FDR<0.05 and |logFC|>0.2) changes in expression following radiation exposure. All proteins were used for feature selection to build predictive models of radiation exposure using different sample and sex specific cohorts. Both binary (prediction of any radiation exposure) and multidose (prediction of specific radiation dose) model series were developed using either female and male samples combined or only female or only male samples. The binary series (Models 1, 2 and 3) and multidose series (Models 4, 5 and 6) series included female/male combined, female only and male only respectively. Results: Detectable values were obtained for all ~7000 proteins included in the SomaScan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies in the binary model series was ~100% at the model training level and when tested with fresh samples 97.9% for Model 1(Female and Male) and 100% for Model 2 (Female only) and Model 3 (Male only). When sex specific Models’ 2 and 3 were tested with the opposite sex, the overall predictive accuracy rate dropped to 62.5% for Model 2 and remained 100% for Model 3. The overall predictive accuracy rate in the multidose model series was 100% for all models at the model training level and when tested with fresh samples 83.3%, 75% and 83.3% for Multidose Models 4-6 respectively. When sex specific Models’ 5 (Female only) and Model 6 (Male only) were tested with the opposite sex the overall predictive accuracy rate dropped to 52.1% and 68.8% respectively. Conclusion: These models represent novel predictive panels of radiation responsive proteomic biomarkers and illustrate the utility and necessity of considering sex specific differences in development of radiation biodosimetry prediction algorithms. As sex specific differences were observed in this study, and as use of point-of-care radiation diagnostics in future mass casualty settings will necessarily include persons of both sexes, consideration of sex specific variation is essential to ensure these diagnostic tools have practical utility in the field.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE267131 | GEO | 2024/05/11

REPOSITORIES: GEO

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Project description:In the event of a large-scale radiation exposure incident, accurate and quick assessment of radiation dose would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to limited availability of appropriate human samples, however, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate models to build and test a biodosimetry algorithm for use in humans, we ex vivo-irradiated peripheral blood samples from both humans and rhesus macaques to 0, 2, 5, 6, and 7 Gy, and compared the gene expression profiles 24 hours later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis, and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using non-human primate data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the non-human primate model. A ‘multi-gene’ approach utilizing all gene values for cross-species conversion and applying the converted values on the non-human primate biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primate. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the non-human primate model.

Project description:A series of two color gene expression profiles obtained using Agilent 44K expression microarrays was used to examine sex-dependent and growth hormone-dependent differences in gene expression in rat liver. This series is comprised of pools of RNA prepared from untreated male and female rat liver, hypophysectomized (‘Hypox’) male and female rat liver, and from livers of Hypox male rats treated with either a single injection of growth hormone and then killed 30, 60, or 90 min later, or from livers of Hypox male rats treated with two growth hormone injections spaced 3 or 4 hr apart and killed 30 min after the second injection. The pools were paired to generate the following 6 direct microarray comparisons: 1) untreated male liver vs. untreated female liver; 2) Hypox male liver vs. untreated male liver; 3) Hypox female liver vs. untreated female liver; 4) Hypox male liver vs. Hypox female liver; 5) Hypox male liver + 1 growth hormone injection vs. Hypox male liver; and 6) Hypox male liver + 2 growth hormone injections vs. Hypox male liver. A comparison of untreated male liver and untreated female liver liver gene expression profiles showed that of the genes that showed significant expression differences in at least one of the 6 data sets, 25% were sex-specific. Moreover, sex specificity was lost for 88% of the male-specific genes and 94% of the female-specific genes following hypophysectomy. 25-31% of the sex-specific genes whose expression is altered by hypophysectomy responded to short-term growth hormone treatment in hypox male liver. 18-19% of the sex-specific genes whose expression decreased following hypophysectomy were up-regulated after either one or two growth hormone injections. Finally, growth hormone suppressed 24-36% of the sex-specific genes whose expression was up-regulated following hypophysectomy, indicating that growth hormone acts via both positive and negative regulatory mechanisms to establish and maintain the sex specificity of liver gene expression. For full details, see V. Wauthier and D.J. Waxman, Molecular Endocrinology (2008)

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Comparison of novel proteomic expression profiles for radiation exposure in male and female C57BL6 mice

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