Skeletal Microstructure - Racial Differences and Genetic Contributors

骨骼微观结构 - 种族差异和遗传因素

基本信息

批准号：
9469037
负责人：
MARCELLA Donovan WALKER
金额：
$ 59.2万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9469037
关键词：
Address African American Aging Asians Bioinformatics Biological Biomedical Engineering Bone Density Bone Matrix Bone structure Caucasians Clinical Clinical assessments Code Cohort Studies Communities Complex Data Deterioration Development Diagnosis Diagnostic Diagnostic tests Disease Elements Endocrine Epilepsy Ethnic Origin Fracture Gene Frequency Genes Genetic Genetic Determinism Genetic screening method Genetic study Goals Grant Health Height Heritability Hispanics Image Imaging Techniques Individual Lead Lipids Measures Methods Minority Modality Osteoporosis Outcome Pathogenicity Patients Peripheral Phenotype Play Predisposition Process Property Public Health Publishing Race Regulation Resolution Roentgen Rays Role Sample Size Testing Thick Thinness Variant Washington Woman Work X-Ray Computed Tomography base bone bone health bone strength cohort design endophenotype exome exome sequencing experience fracture risk fragility fracture genetic analysis genetic approach genetic association genetic variant genome wide association study insight new therapeutic target next generation sequencing novel personalized medicine population based racial difference rare variant retinal rods skeletal skeletal disorder tool trait

项目摘要

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.

骨质疏松症的特点是骨矿物质密度（BMD）低和微结构恶化。 BMD 具有高遗传性，对与骨质疏松或骨折相关的变异进行基因检测并无作用。骨健康的临床评估大部分 BMD 的遗传变异尚未得到解释。解决这个问题的尝试受到了所使用的遗传方法和骨骼的阻碍。全基因组关联研究（GWAS）无法识别这种罕见的变异。可以通过全外显子组测序（WES）识别的变体通常具有重要的功能此外，罕见变异与常见的多基因状况有关。骨质疏松症的“遗传性”可能是由于未识别的罕见变异引起的，大多数 GWAS 已进一步评估。与“骨矿物质密度”（BMD）或“骨折”的遗传关联，这两种结果都是异质性的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，例如例如微观结构或基体特性，这些特性较少导致断裂或防止断裂。遗传异质性并且更适合遗传分析，因此，DXA 以外的工具，例如高。分辨率外围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。 HRpQCT，我们通过识别少数群体、基于成像的新型骨表型取得了进展尽管 DXA 的 BMD 较低或相似，但我们已开始使用 WES 进行研究。我们的数据表明，这是识别遗传的有效方法。该项目的目标是对一个大型的、基于人群的多种族进行表型分析。使用 HRpQCT 和 IMI 与现有 WES 数据进行队列，以确定调节骨微结构的基因和矩阵属性，我们可以评估因果变异等位基因频率的种族差异。最后，我们将评估已识别的变异是否与这些特征相关。这项研究的一个主要优势是 WES 数据的可用性，与 GWAS 相比，它允许我们基于基因的统计方法是一种强大的识别常见和罕见编码变异的方法。方法，使得这种方法在我们的样本量下可行，这些方法已被用来识别新的。调节血脂、身高、传染性、癫痫的致病基因（GWAS 未发现）它在骨质疏松症和其他疾病中的研究才刚刚开始，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总体假设是骨骼。微观结构和基质特性受到遗传调控，并且可以识别它们背后的基因最终，对此类基因的鉴定可能会增强对骨骼调节因子的了解，从而增强对骨骼调节因子的了解。可能会导致基因测试的发展和骨质疏松症新药物靶点的鉴定。