Skeletal Microstructure - Racial Differences and Genetic Contributors

骨质疏松症的特征是低骨矿物质密度（BMD）和微结构恶化。而 骨密度具有高遗传性，与骨质疏松症或骨折相关的变异基因检测在骨密度方面没有作用。 骨骼健康的临床评估。BMD的大部分遗传变异尚未得到解释。 解决这个问题的尝试受到了遗传方法和骨骼肌的阻碍。 评估结果。全基因组关联研究（GWAS）无法识别罕见变异。这种罕见 可以通过全外显子组测序（WES）鉴定的变体通常具有大的功能重要性， 方面的影响.此外，罕见的变异与常见的多基因条件有关。一些“失踪”的 骨质疏松症的“遗传性”可能是由于未识别的罕见变异。此外，大多数GWAS还评估了 与“骨矿物质密度”（BMD）或“骨折”的遗传相关性，两种结果均为异质性 致病过程为了克服这些局限性，我们将使用WES来评估特定的骨骼特征，如 作为微结构或基质性质，其易于断裂或防止断裂。这样的特质比较少 遗传异质性和更适合遗传分析。因此，除了DXA之外的工具，例如高 分辨率外周定量计算机断层扫描（HRpQCT）和冲击显微压痕（IMI）， 测量导致骨折的特定骨骼元素有助于识别骨质疏松症基因。与 HRpQCT，我们通过在少数民族中识别新的基于成像的骨表型， 赋予更大的骨强度，尽管DXA的BMD较低或相似。利用WES，我们已经开始研究 这些种族差异的遗传学。我们的数据表明，这是一种强有力的方法来识别遗传 微观结构的贡献者。这个项目的目标是表型一个大的，人口为基础的，多种族的， 使用HRpQCT和IMI的现有WES数据队列，以确定调节骨微结构的基因 和基质性质。这样做，我们可以评估因果变异等位基因频率的种族差异， 决定了这些特征的种族差异。最后，我们将评估确定的变异是否与 骨折这项研究的一个主要优势是WES数据的可用性，与GWAS相比， 鉴定常见和罕见的编码变体。我们基于基因的统计方法是一种强大的 方法，使这种方法与我们的样本量可行。这些方法已被用于识别新的 调节血脂、身高、感染易感性、癫痫的致病基因（在GWAS中未发现） 和其他条件。它在骨质疏松症中才刚刚开始探索，但提供了一种识别新基因的方法。 具有GWAS未检测到的重要生物学效应。最重要的假设是， 微观结构和基质性质受到遗传调节，并且可以识别它们背后的基因 使用WES。最终，这些基因的鉴定可能会增强对骨骼调节因子的理解， 可能导致基因检测的发展和骨质疏松症新药靶点的鉴定。

Osteoporosis is characterized by low bone mineral density (BMD) and microstructural deterioration. While BMD has high heritability, genetic testing for variants associated with osteoporosis or fracture plays no role in the clinical assessment of bone health. Most of the genetic variance of BMD has yet to be accounted for. Attempts to address this issue have been impeded by the genetic approaches utilized and the skeletal outcomes assessed. Genome-wide association studies (GWASs) cannot identify rare variants. Such rare variants, which can be identified by whole exome sequencing (WES), often have large functionally important effects. Moreover, rare variants are relevant to common, polygenic conditions. Some of the “missing heritability” of osteoporosis is likely due to unidentified rare variants. Further most GWASs have assessed genetic associations with “bone mineral density” (BMD) or “fracture”, both outcomes of heterogeneous pathogenic processes. To overcome these limitations, we will use WES to assess specific skeletal traits, such as microstructure or matrix properties, that predispose to or protect from fracture. Such traits are less genetically heterogeneous and more amenable to genetic analysis. Thus, tools other than DXA, such as high resolution peripheral quantitative computed tomography (HRpQCT) and impact microindentation (IMI) that can measure specific skeletal elements contributing to fracture are useful to identify osteoporosis genes. With HRpQCT, we have made progress by identifying in minorities, novel imaging-based bone phenotypes conferring greater bone strength despite lower or similar BMD by DXA. Using WES, we have begun to study the genetics of these racial differences. Our data indicate this is a powerful approach to identify genetic contributors to microstructure. The goal of this project is to phenotype a large, population-based, multi-ethnic cohort with existing WES data using HRpQCT and IMI in order identify genes regulating bone microstructure and matrix properties. In doing so, we can assess how racial differences in causal variant allele frequencies dictate racial differences in these traits. Lastly, we will assess if identified variants are associated with fractures. A major strength of this study is the availability of WES data, which in contrast to GWAS, allows for the identification of both common and rare coding variants. Our gene-based statistical approach is a powerful method, making this approach feasible with our sample size. These methods have been used to identify new disease-causing genes (not found with GWAS) that regulate lipids, height, infectious susceptibility, epilepsy and other conditions. It has only begun to be explored in osteoporosis, but offers a way to identify novel genes with important biological effects not detected by GWAS. The overarching hypothesis is that skeletal microstructure and matrix properties are under genetic regulation and genes underlying them can be identified using WES. Ultimately, identification of such genes may enhance understanding of skeletal regulators, which may lead to the development of genetic tests and identification of new drug targets for osteoporosis.