Bone Microarchitecture: The Framingham Osteoporosis Study

这是对我们目前资助的基金的补充(“修订”)，题为“骨骼微结构：Framingham 骨质疏松症研究“扩大了父母基金的遗传学工作的范围。它将扩大基因组- 对潜在功能更多、不太常见的领域的父母赠款的广泛关联研究(GWAS) 将提供关于这些变体对骨微结构的贡献的重要数据的变体 采用高分辨率外周定量计算机断层扫描(HR-pQCT)测量。理想情况下，最好的方式 要确定与骨骼微结构相关的潜在功能遗传变异，需要进行测序 从尽可能多的基因组中获取数据。尽管深度测序代表了一种强大的方法 发现导致疾病的变异的全谱，获得和分析的成本 大量人类样本的全基因组甚至外显子序列仍然令人望而却步。因此，这项研究 将利用外显子芯片数据和密集的全基因组基因分型数据在几个HR- PQCT表型，以归因于整个基因组中不太常见的和潜在的功能变异。这个 归罪将利用一个不断增长的全基因组测序参考小组，该小组已经从 几项国际努力。为了实现我们的目标，我们召集了来自世界各地的所有队伍 他们目前有HR-pQCT表型和DNA可用。这一项目将采取的方法将 涉及以下步骤：1)使用现有的Gwas基因分型和外显子芯片基因分型- 基于Framingham的研究，将微小等位基因频率低至0.5%的变异归因于；2)获得相同的结果 另外三个具有相同HR-pQCT衍生骨的队列中的Gwas和Exome芯片基因分型 微体系结构表型；3)在基于群体的队列中执行全基因组推算 使用由10,000个可公开获得的全基因组序列组成的综合参考小组；4) 使用推定的基因类型对队列特定关联分析的结果进行Meta分析；5)优先 Meta分析中最重要的发现，使用统计显著性水平和生物信息学工具 预测功能潜力(例如ENCODE、eQTL分析)；6)验证推测的变体的准确性 通过在骨微结构中进行从头基因分型，具有最显著的相关性 弗雷明翰研究；7)复制变异的最重要的关联，并证实其准确性 另5个HR-pQCT队列的基因分型采用从头基因分型方法。我们的策略是找出两个共同的 以及蛋白质编码区和非编码调控区中不太常见的潜在因果变异 为研究骨微结构退化提供了一个可靠的概念范例 这种疾病的特征是骨质疏松症。

This supplement ("Revision") to our currently funded grant entitled, "Bone Microarchitecture: The Framingham Osteoporosis Study," expands the scope of the genetics work of the parent grant. It will extend the genome- wide association study (GWAS) of the parent grant to the realm of potentially more functional, less common variants that will provide important data on the contribution of these variants to bone microarchitecture measured by high resolution peripheral quantitative computed tomography (HR-pQCT). Ideally, the best way to identify potentially functional genetic variants associated with bone microarchitecture is to have sequencing data from as much of the genome as possible. Although deep sequencing represents a powerful approach for the discovery of the complete spectrum of variants that cause diseases, the cost of obtaining and analyzing whole genome or even exome-sequences on a large human sample remains prohibitive. Therefore, this study will make use of exome chip data along with dense genome wide genotyping data in several cohorts with HR- pQCT phenotypes to impute less common and potentially functional variants across the whole genome. The imputation will make use of a growing reference panel of whole genome sequencing that has emerged from several international efforts. To accomplish our aim, we have assembled all the cohorts from around the world who currently have HR-pQCT phenotypes and DNA available. The approach to be taken in this project will involve the following steps: 1) Use existing GWAS genotyping and exome chip genotyping from the family- based Framingham Study to impute variants with minor allele frequency as low as 0.5%; 2) Obtain the same GWAS and exome chip genotyping in three other cohorts with the identical HR-pQCT-derived bone microarchitecture phenotypes; 3) Perform the whole genome imputation in those population-based cohorts using an integrated reference panel consisting of 10,000 publicly available whole genome sequences; 4) Meta-analyze results from cohort specific association analyses using the imputed genotypes; 5) Prioritize the most significant findings in the meta-analyses, using statistical significance levels as well as bioinformatic tools to predict functional potential (e.g. ENCODE, eQTL analysis); 6) Validate the accuracy of the imputed variants having the most significant association with bone microarchitecture by performing de-novo genotyping in the Framingham Study; 7) Replicate the most significant associations for variants with confirmed accurate genotype in five other HR-pQCT cohorts using de-novo genotyping. Our strategy of identifying both common and less common, potentially causal variants in protein-coding regions and non-coding regulatory regions represents a robust conceptual paradigm for the study of bone microarchitectural deterioration that characterizes the disease, osteoporosis.