Genomic Convergence for Female Osteoporosis Risk Genes

描述（由申请人提供）：骨质疏松症是最常见的代谢性骨病，是一个主要的公共卫生问题。骨质疏松症的主要特征是低骨矿物质密度（BMD）。一般来说，女性的BMD较低，患骨质疏松症的风险高于男性。大多数骨密度变异是由遗传因素决定的，遗传率大于60%。然而，涉及的特定基因在很大程度上是未知的。我们的研究和其他人的研究表明，一些骨质疏松症风险基因/基因组区域具有性别特异性。该SCOR的目标主要是识别女性骨质疏松症风险基因及其功能方面，其次是评估男性样本中这些已识别基因/功能的女性特异性。此外，我们还将通过研究我们最近发现的两个新基因，对确定的风险基因的具体机制和确认进行深入的分子和细胞功能研究。 该SCOR将通过同时在基因组、转录组和蛋白质组水平上研究骨质疏松症，在骨遗传学方面开创一种全面而新颖的方法。我们将使用大量招募或存档的样本进行定向招募，并采用在我们最近的试点研究中证明成功的最先进技术。这种基因组融合方法将精确定位和巩固在每个项目中鉴定的最重要的基因。我们和我们的合作者将对确定的基因进行种群内和种群间的复制研究。在基因组聚合方法中鉴定的所有基因将进行深入的功能研究，以确认和功能机制，如本SCOR项目2的第2阶段所示。该SCOR由三个项目组成，所有项目都旨在识别骨质疏松症风险基因，但来自不同的基因组方法。项目1是使用密集SNP进行全基因组关联扫描，以识别与骨质疏松症风险相关的基因/区域。项目2是进行DMA微阵列研究，扫描超过40，000个已知的人类基因和EST，以识别与骨质疏松症相关的mRNA和相应的基因。项目3是进行蛋白质组学研究，以确定与骨质疏松症相关的蛋白质（和相应的基因）。SCOR有三个核心：A）行政核心; B）临床核心;和C）生物统计学和生物信息学核心。每个核心服务于所有三个项目。例如，临床核心招募项目2和3共享的样本;为临床相关问题（如选择重要的医学和环境因素进行协变量分析）和项目1中的人类受试者研究问题提供支持。确定人类BMD变异的基因及其功能，特别是对于女性，对于1）深入了解骨质疏松症风险的基本分子机制，2）发现新的治疗途径和靶点，3）识别遗传易感个体，以便未来的预防和干预可以针对并基于个体的特定基因型。

DESCRIPTION (provided by applicant): Osteoporosis is the most prevalent metabolic bone disease responsible for a major public health problem. Osteoporosis is mainly characterized by low bone mineral density (BMD). In general, women have lower BMD and higher risk of osteoporosis than men. Most BMD variation is determined by genetic factors with heritability greater than 60%. However, the specific genes involved are largely unknown. Our studies and the studies of others have demonstrated that some osteoporosis risk genes/genomic regions are gender specific. The GOAL of this SCOR is primarily to identify osteoporosis risk genes and their functional aspects in females and, secondarily, to assess the female specificity of these identified genes/functions in male samples. In addition, we will also perform in-depth molecular and cellular functional studies for specific mechanisms and confirmation of the risk genes identified, by studying two novel genes we discovered recently. This SCOR will pioneer a comprehensive and novel approach in bone genetics by investigating osteoporosis at the genome-, transcriptome-, and proteome-wide levels simultaneously. We will use the samples largely recruited or archived for targeted recruitment and adopt state-of-the-art technologies proved successful in our recent pilot studies. This qenomic convergence approach will pinpoint and consolidate the most significant genes identified in each of the individual projects. The genes identified will be subject to replication studies within and across populations by ourselves and our collaborators. All the genes identified in the genomic convergence approach will be subject to in-depth functional studies for confirmation and functional mechanisms as exemplified in Stage 2 of Project 2 of this SCOR. This SCOR is composed of three projects, all aimed at identifying osteoporosis risk genes but from different genomic approaches. Project 1 is to perform a whole genome association scan using dense SNPs to identify those genes/regions that are associated with risk of osteoporosis. Project 2 is to perform a DMA microarray study to scan >40,000 known human genes and ESTs to identify those mRNAs and corresponding genes associated with osteoporosis. Project 3 is to perform proteomics studies to identify those proteins (and corresponding genes) associated with osteoporosis. The SCOR has three cores: A) Administrative Core; B) Clinical Core; and C) Biostatistics and Bioinformatics Core. Each core serves all the three projects. For example, the Clinical Core recruits samples that are shared by Projects 2 and 3; provides support for clinical related issues (such as choice of important medical and environmental factors for co-variate analyses) and for human subject research issues in Project 1. Identifying genes and their functions for human BMD variation, especially for women, is important for 1) gaining insights into the fundamental molecular mechanisms underlying risk of osteoporosis, 2) discovering new pathways and targets for therapeutic cures; 3) identifying genetically susceptible individuals, so that future preventions and interventions can be targeted to and based on individuals' specific genotypes.