Genetics of individual variation in response to radiation exposure

描述(由申请人提供)： 人们通过各种来源暴露在辐射中。为诊断和治疗目的而使用辐射的情况正在增加。虽然这些程序带来了显著的好处，但辐射暴露也有风险。考虑到低剂量和高剂量辐射的不同生物效应以及辐射敏感性的个体差异，可以改进辐射暴露风险的预测。关于辐射影响的大部分数据都是从原子弹幸存者那里积累起来的，他们是唯一一大批受到仔细监测的受辐射个人。辐射敏感性的遗传研究很困难，因为亲属很少接触到相同类型和剂量的辐射。在这个项目中，我们将使用基因组和遗传学相结合的方法来确定细胞对不同剂量辐射的反应机制，并识别影响辐射敏感性的遗传变异。我们将以照射细胞中基因的表达水平作为表型。这使我们能够将细胞暴露在不同剂量的辐射下，并从相关个人那里获得辐射诱导的表型，以便进行基因分析。其具体目的是：1)确定和比较0.5GyIR和3GyIR诱导的基因表达表型；2)通过连锁分析定位影响IR反应基因遗传变异的染色体区域；3)通过关联分析确认连锁结果，缩小候选基因区域，并从功能上表征对0.5GyIR和3GyIR反应的候选调控因子。这些结果将提供有关个体对辐射暴露反应的分子和遗传基础的信息，并为个性化风险预测方法奠定基础。

DESCRIPTION (provided by applicant): People are exposed to radiation through various sources. The use of radiation for diagnostic and therapeutic purposes is increasing. While these procedures bring significant benefits, radiation exposure carries risks. Prediction of risk from radiation exposure can be improved by taking into account the different biological effects of low and high dose radiation and individual variation in radiosensitivity. Most of the data on the effect of radiation have been accumulated from atomic bomb survivors, the only large cohort of exposed individuals that has been carefully monitored. Genetic study of radiosensitivity is difficult because relatives rarely get exposed to the same type and doses of radiation. In this project, we will use a combined genomic and genetic approach to determine the mechanisms of cellular response to different doses of radiation and to identify genetic variants that influence radiosensitivity. We will use expression level of genes in irradiated cells as phenotypes. This allows us to expose cells to different doses of radiation and to obtain radiation-induced phenotypes from related individuals for genetic analysis. The specific aims are 1) determine and compare the gene expression phenotypes induced by 0.5 Gy and 3 Gy IR, 2) map the chromosomal regions that influence inherited variation in IR responsive genes in large families by linkage analysis, and 3) confirm the linkage results and narrow the candidate gene regions by association analysis, and functionally characterize candidate regulators of response to 0.5 Gy and 3 Gy IR exposures. The results will provide information on the molecular and genetic basis of individual response to radiation exposure and form a foundation for a personalized approach to risk prediction.