在过去的几十年中,已经产生了关于辐射应激源对转录变化的影响的大量数据。这些数据显示出跨平台和实验设计的显着一致性,能够增加对辐射暴露的早期分子效应的理解。然而,转录组数据在风险评估中的价值尚不明确,存在一个差距,值得进一步考虑.最近,基准剂量(BMD)建模已显示出将转录出发点(POD)与使用与人类健康风险评估相关的表型结果得出的转录出发点(POD)相关联的希望。尽管经常应用于化学毒性评估,我们小组最近在辐射研究领域展示了应用。这种方法允许使用BMD值在各种数据集中定量比较辐射诱导的基因和途径改变的可能性,并得出有意义的生物学效应。然而,在可以自信地使用BMD建模之前,需要了解混杂变量对BMD输出的影响。
为此,BMD建模应用于公开可用的微阵列数据集(基因表达Omnibus#GSE23515),该数据集使用以0.82Gy/min离体γ辐射的外周血,剂量为0、0.1、0.5或2Gy,并在暴露后6小时进行评估。数据集包括六名女性吸烟者(F-S),六名女性不吸烟者(F-NS),六名男性吸烟者(M-S),和六名男性不吸烟者(M-NS)。
将总共412个基因的组合拟合到模型,并且注意到BMD分布在四组中是双峰的。共有74、41、62和62个基因是F-NS特有的,M-NS,F-S和M-S组。在所有四组中,共有62个BMD建模基因和9个途径。在强大的常见基因和途径中,BMD反应没有差异敏感性。
对于研究小组中常见的辐射响应基因和途径,转录活性的BMD分布不受性别和吸烟状况的影响。尽管需要进一步验证数据,这些初步研究结果表明,辐射相关基因和通路的BMD值是稳健的,可以在未来的研究中进一步探索.
A vast amount of data regarding the effects of radiation stressors on transcriptional changes has been produced over the past few decades. These data have shown remarkable consistency across platforms and experimental design, enabling increased understanding of early molecular effects of radiation exposure. However, the value of transcriptomic data in the context of risk assessment is not clear and represents a gap that is worthy of further consideration. Recently, benchmark dose (BMD) modeling has shown promise in correlating a transcriptional point of departure (POD) to that derived using phenotypic outcomes relevant to human health risk assessment. Although frequently applied in chemical toxicity evaluation, our group has recently demonstrated application within the field of radiation research. This approach allows the possibility to quantitatively compare radiation-induced gene and pathway alterations across various datasets using BMD values and derive meaningful biological effects. However, before BMD modeling can confidently be used, an understanding of the impact of confounding variables on BMD outputs is needed.
To this end, BMD modeling was applied to a publicly available microarray dataset (Gene Expression Omnibus #GSE23515) that used peripheral blood ex-vivo gamma-irradiated at 0.82 Gy/min, at doses of 0, 0.1, 0.5 or 2 Gy, and assessed 6 hours post-exposure. The dataset comprised six female smokers (F-S), six female nonsmokers (F-NS), six male smokers (M-S), and six male nonsmokers (M-NS).
A combined total of 412 genes were fit to models and the BMD distribution was noted to be bi-modal across the four groups. A total of 74, 41, 62 and 62 genes were unique to the F-NS, M-NS, F-S and M-S groups. Sixty-two BMD modeled genes and nine pathways were common across all four groups. There were no differential sensitivity of BMD responses in the robust common genes and pathways.
For radiation-responsive genes and pathways common across the study groups, the BMD distribution of transcriptional activity was unaltered by sex and smoking status. Although further validation of the data is needed, these initial findings suggest BMD values for radiation relevant genes and pathways are robust and could be explored further in future studies.