Department of Orthopedic Surgery, University of California, San Francisco, CA, USA.
Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
Curr Osteoporos Rep. 2023 Dec;21(6):637-649. doi: 10.1007/s11914-023-00821-7. Epub 2023 Oct 13.
The integration of data from multiple genomic assays from humans and non-human model organisms is an effective approach to identify genes involved in skeletal fragility and fracture risk due to osteoporosis and other conditions. This review summarizes genome-wide genetic variation and gene expression data resources relevant to the discovery of genes contributing to skeletal fragility and fracture risk.
Genome-wide association studies (GWAS) of osteoporosis-related traits are summarized, in addition to gene expression in bone tissues in humans and non-human organisms, with a focus on rodent models related to skeletal fragility and fracture risk. Gene discovery approaches using these genomic data resources are described. We also describe the Musculoskeletal Knowledge Portal (MSKKP) that integrates much of the available genomic data relevant to fracture risk. The available genomic resources provide a wealth of knowledge and can be analyzed to identify genes related to fracture risk. Genomic resources that would fill particular scientific gaps are discussed.
整合来自人类和非人类模式生物的多个基因组分析的数据是一种有效的方法,可以识别与骨质疏松症和其他疾病导致的骨骼脆弱和骨折风险相关的基因。本综述总结了与发现导致骨骼脆弱和骨折风险的基因相关的全基因组遗传变异和基因表达数据资源。
总结了与骨质疏松症相关特征的全基因组关联研究(GWAS),以及人类和非人类生物组织中的骨基因表达,重点介绍了与骨骼脆弱和骨折风险相关的啮齿动物模型。描述了使用这些基因组数据资源进行基因发现的方法。我们还描述了骨骼肌肉知识门户(MSKKP),它整合了与骨折风险相关的大部分可用基因组数据。现有的基因组资源提供了丰富的知识,可以进行分析以识别与骨折风险相关的基因。讨论了可以填补特定科学空白的基因组资源。