Chen Yuan-Cheng, Guo Yan-Fang, He Hao, Lin Xu, Wang Xia-Fang, Zhou Rou, Li Wen-Ting, Pan Dao-Yan, Shen Jie, Deng Hong-Wen
Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, PR China.
Institute of Bioinformatics, School of Basic Medical Science, Southern Medical University, Guangzhou, PR China.
J Bone Miner Res. 2016 May;31(5):1041-9. doi: 10.1002/jbmr.2781. Epub 2016 Feb 6.
Osteoporosis is known to be highly heritable. However, to date, the findings from more than 20 genome-wide association studies (GWASs) have explained less than 6% of genetic risks. Studies suggest that the missing heritability data may be because of joint effects among genes. To identify novel heritability for osteoporosis, we performed a system-level study on bone mineral density (BMD) by weighted gene coexpression network analysis (WGCNA), using the largest GWAS data set for BMD in the field, Genetic Factors for Osteoporosis Consortium (GEFOS-2), and a transcriptomic gene expression data set generated from transiliac bone biopsies in women. A weighted gene coexpression network was generated for 1574 genes with GWAS nominal evidence of association (p ≤ 0.05) based on dissimilarity measurement on the expression data. Twelve distinct gene modules were identified, and four modules showed nominally significant associations with BMD (p ≤ 0.05), but only one module, the yellow module, demonstrated a good correlation between module membership (MM) and gene significance (GS), suggesting that the yellow module serves an important biological role in bone regulation. Interestingly, through characterization of module content and topology, the yellow module was found to be significantly enriched with contractile fiber part (GO:044449), which is widely recognized as having a close relationship between muscle and bone. Furthermore, detailed submodule analyses of important candidate genes (HOMER1, SPTBN1) by all edges within the yellow module implied significant enrichment of functional connections between bone and cytoskeletal protein binding. Our study yielded novel information from system genetics analyses of GWAS data jointly with transcriptomic data. The findings highlighted a module and several genes in the model as playing important roles in the regulation of bone mass in females, which may yield novel insights into the genetic basis of osteoporosis. © 2016 American Society for Bone and Mineral Research.
已知骨质疏松症具有高度遗传性。然而，迄今为止，20多项全基因组关联研究（GWAS）的结果所解释的遗传风险不到6%。研究表明，缺失的遗传力数据可能是由于基因间的联合效应。为了确定骨质疏松症的新遗传力，我们使用该领域最大的骨密度GWAS数据集——骨质疏松症遗传因素联盟（GEFOS - 2）以及从女性髂骨活检产生的转录组基因表达数据集，通过加权基因共表达网络分析（WGCNA）对骨密度（BMD）进行了系统水平研究。基于对表达数据的差异测量，为1574个具有GWAS名义关联证据（p≤0.05）的基因生成了加权基因共表达网络。识别出了12个不同的基因模块，其中4个模块与骨密度表现出名义上的显著关联（p≤0.05），但只有一个模块，即黄色模块，在模块成员度（MM）和基因显著性（GS）之间显示出良好的相关性，这表明黄色模块在骨骼调节中发挥着重要的生物学作用。有趣的是，通过对模块内容和拓扑结构的表征，发现黄色模块显著富集收缩纤维部分（GO:044449），而收缩纤维部分被广泛认为在肌肉和骨骼之间存在密切关系。此外，通过对黄色模块内所有边的重要候选基因（HOMER1、SPTBN1）进行详细的子模块分析，暗示了骨与细胞骨架蛋白结合之间功能连接的显著富集。我们的研究从GWAS数据与转录组数据的系统遗传学分析中获得了新信息。研究结果突出了模型中的一个模块和几个基因在女性骨量调节中发挥重要作用，这可能为骨质疏松症的遗传基础提供新的见解。© 2016美国骨与矿物质研究学会
