Examination of Co-inheritance of Bone Mineral Density, IGF-1 and Lifespan

描述(申请人提供)：在美国女性中，骨质疏松性骨折的年发病率比心脏病发作、中风和乳腺癌的总和还要高。骨矿密度(BMD)是骨折风险的最强预测因子之一，研究表明，高达80%的差异可以由遗传因素解释。许多骨密度的数量性状基因座(QTL)已经在小鼠和人类中定位，但缺乏实际的基因识别。这个应用程序的目标是更好地识别和定位这些与小鼠骨骼相关的QTL，并识别一些潜在的候选基因。老鼠是定位复杂性状背后的基因的极好模型，但寻找这些基因的努力受到了用于QTL分析的遗传图谱中的一些错误的阻碍。一份新的、经过修正的小鼠基因图谱现已问世。我们收集了18个小鼠定位杂交的原始数据，并将使用这个新的图谱重新计算骨密度、几何形状和强度等骨相关性状的QTL。然后，系统地将一套生物信息学分析技术应用于骨遗传学，包括荟萃分析、QTL-QTL交互作用、联合交叉分析、比较基因组学和区块单倍型。在生物信息学分析的基础上，我们将重点确定最有希望的QTL的基因。通过聚焦于控制多种表型的一条分子途径，并利用这些表型的QTL共定位来缩小QTL间隔，可以帮助寻找BMD QTL基因。年轻时的骨密度与血清胰岛素样生长因子-1(IGF-1)呈正相关，与中位寿命呈负相关。我们将重点关注另外两个QTL，其中这三个表型的QTL已经使用精细定位杂交和生物信息学进行了共同定位，以确定这两个QTL背后的基因。总而言之，我们将使用先进的遗传分析和综合表型方法来更好地识别BMD的候选基因。与公共健康相关：这项研究将帮助我们更好地理解控制骨密度和骨质疏松症的基因是什么。了解骨质疏松症的遗传学将导致新的更好的治疗方法，并提高我们筛查和预防这种常见的、使人衰弱的疾病的能力。

DESCRIPTION (provided by applicant): In women in the US, the annual incidence of osteoporotic fracture is greater than for heart attack, stroke and breast cancer combined. Bone mineral density (BMD) is one of the strongest predictors of fracture risk and studies have demonstrated that up to 80% of the variance can be explained by heritable factors. Many quantitative trait loci (QTL) for BMD have been mapped in mice and humans, but actual gene identification is lacking. The goal of this application is to better identify and map these bone related QTL in mice and to identify some of the underlying candidate genes. The mouse is an excellent model for mapping genes that underlie complex traits, but the effort to find these genes has been hampered by a number of errors in the genetic map used for QTL analysis. A new and corrected mouse genetic map is now available. We have collected the raw data from 18 mouse mapping crosses and will use this new map to recalculate QTL for the bone related traits of BMD, geometry and strength. Then a set of bioinformatic analysis techniques will be systematically applied to bone genetics including meta-analysis, QTL-QTL interaction, combined-cross analysis, comparative genomics and block haplotyping. Based on this bioinformatics analysis, we will then focus on identifying the genes for the most promising QTL. Finding BMD QTL genes could be aided by focusing on one molecular pathway that controls a variety of phenotypes and to use co-mapping of QTL for these phenotypes to narrow the QTL interval. BMD at a young age positively correlated with serum insulin-like growth factor-1 (IGF-1) and negatively correlated with the median lifespan. We will focus on two additional QTL where QTL for these three phenotypes have been co-mapped using both fine mapping crosses and bioinformatics to identify the genes underlying these two QTL. In summary, we will use both advanced genetic analyses and a combined phenotypes approach to better identify candidate genes for BMD. PUBLIC HEALTH RELEVANCE: This research will help us better comprehend what the genes are that control bone mineral density and osteoporosis. Understanding the genetics of osteoporosis will lead to new and better treatments and improve our ability to screen for and prevent this common and debilitating disease.