Bone Microarchitecture: The Framingham Osteoporosis Study

这一补充（“修订”），我们目前资助的赠款，题为“骨微结构： 骨质疏松症研究”，扩大了父母赠款的遗传学工作的范围。它将扩展基因组- 广泛的关联研究（GWAS）的父母授予的领域，潜在的功能，不太常见， 这些变体将提供关于这些变体对骨微结构的贡献的重要数据 通过高分辨率外周定量计算机断层扫描（HR-pQCT）测量。理想情况下，最好的方法 鉴定与骨微结构相关的潜在功能性遗传变异的方法是进行测序， 尽可能多的基因组数据。虽然深度测序是一种强大的方法， 发现导致疾病的变异的完整谱，获得和分析的成本 大的人类样品上的全基因组或甚至外显子组序列仍然是令人望而却步的。因此本研究 将利用外显子组芯片数据沿着密集的全基因组基因分型数据在几个队列与HR- pQCT表型，以填补整个基因组中不太常见的和潜在的功能性变体。的 插补将利用一个不断增长的全基因组测序参考小组， 多项国际努力。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 目前有HR-pQCT表型和DNA可用的人。本项目采取的方法将 涉及以下步骤：1）使用来自家族的现有GWAS基因分型和外显子组芯片基因分型- 基于Fragrance的研究来插补具有低至0.5%的次要等位基因频率的变体; 2）获得相同的 在其他三个具有相同HR-pQCT衍生骨的队列中进行GWAS和外显子组芯片基因分型 微结构表型; 3）在那些基于群体的群组中进行全基因组插补 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组; 4） 使用插补的基因型对来自队列特异性关联分析的荟萃分析结果进行分析; 5）优先考虑 荟萃分析中最重要的发现，使用统计学显著性水平以及生物信息学工具 预测功能潜力（例如ENCODE，eQTL分析）; 6）验证插补变异的准确性 通过在骨微结构中进行从头基因分型， 7）复制变体的最显著关联， 使用从头基因分型在其他5个HR-pQCT队列中进行基因型分析。我们的战略是， 以及蛋白质编码区和非编码调控区中不太常见的潜在致病变异 代表了骨微结构退化研究的一个强大的概念范式， 是骨质疏松症的特征

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.