GWAS in MrOS and SOF

描述（由申请人提供）：年龄相关疾病的遗传成分引起了人们的强烈兴趣，基因组全关联研究（GWAS）是识别与疾病相关的染色体位点的重要工具。GWAS成功的两个主要和相互关联的挑战是聚集足够规模的队列和开发准确和详细的表型数据。在这里，我们建议通过提供来自两项最重要的年龄相关肌肉骨骼疾病研究（骨质疏松性骨折研究（SOF）和男性骨质疏松性骨折研究（mro））的高密度基因分型和详细表型数据，来显著增强解决重要健康问题的遗传决定因素的能力。这些是基于社区的老年女性和男性的大型纵向观察研究（可用于基因分型的联合队列- 10,307），具有骨密度，骨结构，骨折，身体成分和骨关节炎的详细表型信息。这些队列使用非常相似的方法进行表型分析，因此可以对基因型表型关联进行综合分析，并提供了检查性别对遗传学影响的机会。此外，关于协变量和环境影响的大量数据可供使用，这将使基因-环境分析成为可能。最后，除了肌肉骨骼表型外，SOF和mro还具有与许多其他与年龄相关的条件（例如睡眠、视觉障碍、肌肉减少症、身体表现、认知）相关的可用测量，这将有助于与其他队列合作研究中进行荟萃分析的能力。具体而言，我们建议：1。对10,307名SOF和mro参与者进行高密度（1M SNP）全基因组基因分型，从而有机会了解SNP-表型关联，以及结构变异（如拷贝数）与表型之间的关联。2. 组装链接的基因型和表型信息在数据集中转移到dbGaP。这些数据将显著增加主要肌肉骨骼疾病遗传学的研究机会，并为其他突出的年龄相关疾病的合作研究提供重要的队列。

DESCRIPTION (provided by applicant): The genetic components of age-related disorders are of intense interest, and genome wide association studies (GWAS) are an important tool in identifying chromosomal loci that are associated with disease. Two of the major and interlinked challenges for successful GWAS has been assembling cohorts of sufficient size and developing accurate and detailed phenotype data. Here we propose to significantly enhance the power to address the genetic determinates of important health issues by making available high density genotyping and detailed phenotyping data from two of the most important studies of age-related musculoskeletal disorders: The Study of Osteoporotic Fractures (SOF) and the Osteoporotic Fractures in Men Study (MrOS). These are large, community based longitudinal observational studies of older women and men (combined cohorts available for genotyping - 10,307) that have detailed phenotypic information for bone density, bone structure, fracture, body composition, and osteoarthritis. The cohorts use very similar methods for phenotyping and thus allow combined analyses of genotype phenotype associations, and provide an opportunity to examine the influence of sex on genetics. Moreover, extensive data is available on a host of covariates and environmental influences that will enable gene-environment analyses. Finally, in addition to the musculoskeletal phenotypes SOF and MrOS have available measures relevant to a host of additional age-related conditions (e.g. sleep, visual disturbance, sarcopenia, physical performance, cognition) that will contribute to the power of meta-analyses performed in collaborative studies with other cohorts. Specifically, we propose to: 1. Perform high density (1M SNP) genome wide genotyping in 10,307 SOF and MrOS participants, yielding opportunities to understand SNP-phenotype associations, as well as the associations between structural variation (e.g. copy number) and phenotype. 2. Assemble linked genotype and phenotype information in a data set for transfer to dbGaP. These data will significantly increase research opportunities in the genetics of major musculoskeletal disorders as well as contribute important cohorts to the collaborative study of other prominent age-related conditions.