The need for mouse models in osteoporosis genetics research.

The need for mouse models in osteoporosis genetics research.
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DOI:
10.1038/bonekey.2012.98
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发表时间:
2012-06
期刊:
BoneKEy reports
影响因子:
--
通讯作者:
C. Ackert-Bicknell;Matthew A. Hibbs
C. Ackert-Bicknell;Matthew A. Hibbs
中科院分区:
其他
文献类型:
--
作者:
C. Ackert-Bicknell;Matthew A. Hibbs

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骨质疏松症是骨质的逐渐流失导致的脆性骨折,影响着美国,欧洲和日本的1.75亿人。骨矿物质密度(BMD)与骨折风险相关,并广泛用于临床环境中预测骨折。大量研究表明峰值骨量具有高度遗传性,因此进行了大量全基因组关联研究(GWAS)以确定调节BMD的基因。传统的小鼠杂交作图在骨骼生物学领域取得了有限的成功。随着人类GWAS的出现,在遗传学研究中继续需要小鼠模型的问题已经出现。然而,在小鼠遗传学领域已经取得了重大进展,包括新的遗传资源群体和基因座作图技术,这使得基因水平的作图分辨率成为可能。在这篇综述中,我们讨论了小鼠模型的需要,以帮助了解新的人类GWAS研究结果的骨骼生物学基础,如何在小鼠中发现的基因座可以用来补充GWAS分析,并强调了骨骼生物学领域的最新进展,从使用这些新的和发展中的资源。最后,我们讨论了在骨骼生物学领域的系统级方法的必要性,重点是对通路和网络分析的必要性。
Osteoporosis, the progressive loss of bone mass resulting in fragility fractures, affects ∼75 million people in the United States, Europe and Japan. Bone mineral density (BMD) correlates with fracture risk and is widely used in clinical settings to predict fracture. Numerous studies have demonstrated that peak bone mass is highly heritable and consequently a number of genome-wide association studies (GWASs) have been conducted to identify the genes that regulate BMD. Traditional intercross mapping in the mouse has met with limited successes in the field of skeletal biology. With the advent of human GWAS, questions have arisen about the continued need for mouse models in genetics research. However, significant advances have been made in the field of mouse genetics, including new genetics resource populations and loci mapping techniques, which enable gene-level mapping resolution. In this review, we discuss the need for mouse models to help understand the skeletal biology underlying novel human GWAS findings, how loci discovered in the mouse can be used to complement GWAS analysis and highlight the recent advances made in the field of skeletal biology from the use of these new and developing resources. We conclude this paper with a discussion of the need for systems-level approaches in the skeletal biology field, with an emphasis on the need for pathway and network analyses.