Guo Yan, Dong Shan-Shan, Chen Xiao-Feng, Jing Ying-Aisha, Yang Man, Yan Han, Shen Hui, Chen Xiang-Ding, Tan Li-Jun, Tian Qing, Deng Hong-Wen, Yang Tie-Lin
Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P. R. China.
School of Public Health and Tropical Medicine, Tulane University New Orleans, LA 70112, USA.
Sci Rep. 2016 Jul 28;6:30558. doi: 10.1038/srep30558.
To identify susceptibility genes for osteoporosis, we conducted an integrative analysis that combined epigenomic elements and previous genome-wide association studies (GWASs) data, followed by validation at population and functional levels, which could identify common regulatory elements and predict new susceptibility genes that are biologically meaningful to osteoporosis. By this approach, we found a set of distinct epigenomic elements significantly enriched or depleted in the promoters of osteoporosis-associated genes, including 4 transcription factor binding sites, 27 histone marks, and 21 chromatin states segmentation types. Using these epigenomic marks, we performed reverse prediction analysis to prioritize the discovery of new candidate genes. Functional enrichment analysis of all the prioritized genes revealed several key osteoporosis related pathways, including Wnt signaling. Genes with high priority were further subjected to validation using available GWASs datasets. Three genes were significantly associated with spine bone mineral density, including BDNF, PDE4D, and SATB2, which all closely related to bone metabolism. The most significant gene BDNF was also associated with osteoporotic fractures. RNA interference revealed that BDNF knockdown can suppress osteoblast differentiation. Our results demonstrated that epigenomic data could be used to indicate common epigenomic marks to discover additional loci with biological functions for osteoporosis.
为了鉴定骨质疏松症的易感基因,我们进行了一项综合分析,该分析整合了表观基因组元件和之前全基因组关联研究(GWAS)的数据,随后在人群和功能水平上进行验证,这能够识别常见的调控元件并预测对骨质疏松症具有生物学意义的新的易感基因。通过这种方法,我们发现了一组在骨质疏松症相关基因启动子中显著富集或缺失的独特表观基因组元件,包括4个转录因子结合位点、27个组蛋白标记和21种染色质状态分割类型。利用这些表观基因组标记,我们进行了反向预测分析以优先发现新的候选基因。对所有优先排序基因的功能富集分析揭示了几条与骨质疏松症相关的关键途径,包括Wnt信号通路。具有高优先级的基因进一步使用可用的GWAS数据集进行验证。三个基因与脊柱骨密度显著相关,包括BDNF、PDE4D和SATB2,它们都与骨代谢密切相关。最显著的基因BDNF也与骨质疏松性骨折相关。RNA干扰显示,BDNF敲低可抑制成骨细胞分化。我们的结果表明,表观基因组数据可用于指示常见的表观基因组标记,以发现具有生物学功能的骨质疏松症额外位点。