Multistage genome-wide association meta-analyses identified two new loci for bone mineral density

Zhang, Lei; Choi, Hyo Geun; Estrada, Karol; Leo, Paul; Li, Jian; Zhang, Yinping; Lin, Yong; Shen, Hui; Liu, Yao Zhong; Liu, Yongjun; Zhao, Yingchun; Zhang, Ji Gang; Tian, Qing; Wang, Yu Ping; Han, Yingying; Ran, Shu; Hai, Rong; Zhu, Xue Zhen; Wu, Shuyan; Yan, Han; Liu, Xiaogang; Yang, Tie Lin; Zhang, Feng; Guo, Yan; Chen, Yuan; Chen, Xiang-Ding; Tan, Lijun; Zhang, Lishu; Dèng, Fēi; Deng, Hong‐Wen; Rivadeneira, Fernando; Duncan, Emma L.; Lee, Jong‐Young; Han, Bok Ghee; Cho, Nam H.; Nicholson, Geoffrey C.; McCloskey, Eugène; Eastell, Richard; Prince, Richard; Eisman, John A.; Jones, Graeme; Reid, Ian R.; Sambrook, Philip N.; Dennison, Elaine; Danoy, Patrick; Yerges‐Armstrong, Laura M.; Streeten, Elizabeth A.; Hu, Tian; Xiang, Sheng; Papasian, Christopher J.; Brown, Matthew A.; Shin, Chan Soo; Uitterlinden, André G.; Deng, Hong Wen

doi:10.1093/hmg/ddt575

Cited by 139 publications

(148 citation statements)

References 38 publications

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“…Across all these studies, B60 loci involved in key pathways that contribute to the pathophysiology of osteoporosis, including bone mass and fracture susceptibility, have been identified and have confirmed the strong regulation exerted by the RANKL and WNT signaling pathways (reviewed in references 22-24). [25][26][27] Although the role of some of the loci/genes identified by BMD GWAS lack experimental confirmation of their involvement in skeletal homeostasis, several have been shown to contribute to skeletal phenotypes and to be involved in signaling pathways regulating bone mass. Thus, known key master genes of skeletal development (such as SOX9 and RUNX2), mesenchymal cell differentiation (including RUNX2 and SP7) and regulation of osteoclast differentiation (RANK-RANKL-OPG (osteoprotegerin)) have been associated with BMD in humans.…”

Section: Genome-wide Association Studies Of Skeletal Phenotypes Reveamentioning

confidence: 99%

A new WNT on the bone: WNT16, cortical bone thickness, porosity and fractures

Gori¹,

Lerner²,

Ohlsson³

et al. 2015

BoneKEy Reports

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The last decade has provided abundant data implicating the WNT pathway in bone development and in the regulation of skeletal homeostasis. Rare human mutations together with gain-and loss-of-function approaches in mice have clearly demonstrated that disrupted regulation of this pathway leads to altered bone mass. In addition to these rare human and mice mutations, large population-based genome-wide association studies (GWASs) have identified single-nucleotide polymorphisms in B60 loci strongly associated with variations in bone mineral density (BMD) at different skeletal sites. Among the loci/genes identified by BMD GWAS, components of the WNT signaling pathway are numerous and have been shown to contribute to skeletal development and homeostasis. Within the components of WNTsignaling, the gene coding for WNT16, one of the 19 WNT ligands of the human genome, has been found strongly associated with specific bone traits such as cortical bone thickness, cortical porosity and fracture risk. Recently, the first functional characterization of Wnt16 has confirmed the critical role of Wnt16 in the regulation of cortical bone mass and bone strength in mice. These reports have extended our understanding of Wnt16 function in bone homeostasis and have not only confirmed the unique association of Wnt16 with cortical bone and fracture susceptibility, as suggested by GWAS in human populations, but have also provided novel insights into the biology of this WNT ligand and the mechanism(s) by which it regulates cortical but not trabecular bone homeostasis. Most interestingly, Wnt16 appears to be a strong anti-resorptive soluble factor acting on both osteoblasts and osteoclast precursors. WNT Signaling and Skeletal HomeostasisSkeletal homeostasis is maintained throughout life by the balance between bone formation by osteoblasts (which derive from mesenchymal cells) and bone resorption by osteoclasts (which have hematopoietic origin), regulated in part by the third bone cell type, the osteocyte, itself derived from osteoblasts. The adult skeleton continuously undergoes remodeling, and failure to balance these two processes can lead to skeletal diseases, such as osteoporosis, characterized by decreased bone mass, altered bone micro-structure and increased risk of fragility fractures.1 Most studies have, however, focused on trabecular bone remodeling despite the fact that 80% of the skeleton is constituted by cortical bone. [2][3][4] The findings that with aging 80% of fractures are associated with cortical bone (non-vertebral fractures) indicate that cortical bone mass is a key determinant of bone strength. [2][3][4] Although the risk of vertebral fractures, which arise mainly at trabecular sites, is significantly decreased by the currently available anti-resorptive or anabolic treatments, the risk of non-vertebral fractures is reduced only by B20%, confirming a dichotomy between the homeostatic regulation of the trabecular and cortical bone compartments 1,[5][6][7][8]

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Section: Genome-wide Association Studies Of Skeletal Phenotypes Reveamentioning

confidence: 99%

A new WNT on the bone: WNT16, cortical bone thickness, porosity and fractures

Gori¹,

Lerner²,

Ohlsson³

et al. 2015

BoneKEy Reports

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“…Moreover, genome-wide studies identified genetic variants associated with bone mineral density and fracture risk, that could identify new additive biological pathways underlying bone metabolism, and provide new possibility of OP intervention and treatment [52][53][54][55][56][57].…”

Section: Resultsmentioning

confidence: 99%

Biomarkers of Bone Turnover: Potential, Challenges and Pitfalls from the Laboratory Point of view

Vassalle¹

2016

Rheumatology

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“…Details of this dataset are provided in Ref. 18. Briefly, each GWAS sample was genotyped by high-throughput SNP genotyping array.…”

Section: Gwas Datasetmentioning

confidence: 99%

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

Zhang

et al. 2014

The Journal of Clinical Endocrinology & Metabolism

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Context:To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods:First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results:In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value Ͻ.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion:We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis.

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Multistage genome-wide association meta-analyses identified two new loci for bone mineral density

Cited by 139 publications

References 38 publications

A new WNT on the bone: WNT16, cortical bone thickness, porosity and fractures

A new WNT on the bone: WNT16, cortical bone thickness, porosity and fractures

Biomarkers of Bone Turnover: Potential, Challenges and Pitfalls from the Laboratory Point of view

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

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