GENETICS OF GLUCOCORTICOID INDUCED OSTEOPOROSIS IN MICE

骨质疏松症是老年人发病和死亡的主要原因 但对骨质疏松症的易感性差异很大。几个 一系列证据表明，遗传易感性对 这种变异的一半。尽管长期使用糖皮质激素会导致 包括骨质疏松症在内的一系列副作用，这些药物是 广泛用于包括关节炎在内的许多医疗条件。按原样 在退化性骨质疏松症的病例中，个体在 对糖皮质激素引起的骨质疏松症的易感性。此项目测试 遗传易感性与糖皮质激素有关的假说 致小鼠骨质疏松。其目标是识别、绘制地图并最终 糖皮质激素易感性相关基因的克隆 利用已有重组同源基因分析小鼠骨质疏松 应变组。在这项工作的第一阶段， 糖皮质激素重组基因的祖细胞诱导 骨质疏松，以及其他糖皮质激素毒性，将是 下定决心。在第二阶段的工作中，重组同源基因 其祖先最分散的菌株集将被分析以 识别含有影响糖皮质激素基因的染色体区域 诱发骨质疏松症。在第三阶段的工作中进一步繁育 将执行以完善候选基因的图谱并提供 为它们的位置克隆提供必要的信息。识别鼠标 导致骨质疏松症的染色体区域将允许预测 通过句法论元对相应的人类区域进行分析，并促进 设计人类基因研究这个问题。

Osteoporosis is a leading cause of morbidity and mortality of older individuals, but susceptibility to osteoporosis varies widely. Several lines of evidence suggest that genetic predisposition contributes about half of this variation. Although chronic glucocorticoid use can lead to a broad range of adverse effects including osteoporosis, these drugs are widely used for many medical conditions including the arthritides. As is the case with involutional osteoporosis, individuals vary widely in their susceptibility to glucocorticoid induced osteoporosis. This project tests the hypothesis that genetic predisposition contributes to glucocorticoid induced osteoporosis in mice. Its goal is to identify, map and ultimately clone genes mediating susceptibility to glucocorticoid induced osteoporosis in mice through the analysis of existing recombinant congenic strain sets. In the first stage of the work, the susceptibilities of the progenitors of the recombinant congenics to glucocorticoid induced osteoporosis, and secondarily other glucocorticoid toxicities, will be determined. In the second stage of the work, the recombinant congenic strain set whose progenitors are most divergent will be analyzed to identify chromosomal regions that harbor genes affecting glucocorticoid induced osteoporosis. In the third stage of the work further breeding will be performed to refine the mapping of the candidate genes and provide the necessary information for their positional cloning. Identifying mouse chromosome regions that contribute to osteoporosis will allow prediction of the corresponding human regions by synteny arguments and facilitate the design of human genetic studies of this problem.