Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.
Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.
复制标题
GWAS、eQTL 和 meQTL 数据的综合分析表明，多个基因集与骨矿物质密度相关。
DOI：
10.1302/2046-3758.610.bjr-2017-0113.r1
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发表时间：
2017-10
影响因子：
4.6
通讯作者：
Zhang F
中科院分区：
文献类型：
--
作者：
Wang W;Huang S;Hou W;Liu Y;Fan Q;He A;Wen Y;Hao J;Guo X;Zhang F
几个全基因组关联研究（GWAS）的骨密度（BMD）已成功地确定了多个易感基因，但孤立的易感基因往往难以生物学解释。本研究的目的是通过整合BMD GWAS数据、全基因组表达数量性状基因座（eQTL）和甲基化数量性状基因座（meQTL）数据，在通路水平上揭示BMD的遗传背景。研究的区域包括32735个股骨颈，28498个腰椎和8143个前臂。从最近发表的研究中收集了全基因组eQTL（包含923 021个eQTL）和meQTL（包含683 152个独特甲基化位点和局部meQTL）数据集。首先通过基于汇总数据的孟德尔随机化（SMR）软件和meQTL对齐的GWAS结果计算基因评分。然后应用基因集富集分析（GSEA）以0.05的预定义显著性水平鉴定BMD相关基因集。我们在一个或多个区域鉴定了与BMD相关的多个基因组，包括相关的已知生物基因组，例如Reactome昼夜节律钟（在基于eQTL的GSEA中，LS和股骨颈BMD的GSEA p值分别为1.0 × 10-4和2.7 × 10-2）和胰岛素样生长因子受体结合（在基于meQTL的GSEA中，股骨颈和腰椎BMD的GSEA p值分别为5.0 × 10-4和2.6 × 10-2）。我们的研究结果为后续的骨代谢功能分析提供了新的线索，并说明了将eQTL和meQTL数据整合到复杂人类疾病遗传研究的途径关联分析中的好处。引用这篇文章：W. Wang，S.黄，W. Hou，Y.刘，智-地Fan，黄毛菊A.他，Y. Wen，J. Hao，X. Guo，F.张某GWAS、eQTL和meQTL数据的综合分析表明，多个基因集与骨密度相关。骨关节研究2017;6：572-576。
Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients’ BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05. We identified multiple gene sets associated with BMD in one or more regions, including relevant known biological gene sets such as the Reactome Circadian Clock (GSEA p-value = 1.0 × 10-4 for LS and 2.7 × 10-2 for femoral necks BMD in eQTLs-based GSEA) and insulin-like growth factor receptor binding (GSEA p-value = 5.0 × 10-4 for femoral necks and 2.6 × 10-2 for lumbar spines BMD in meQTLs-based GSEA). Our results provided novel clues for subsequent functional analysis of bone metabolism, and illustrated the benefit of integrating eQTLs and meQTLs data into pathway association analysis for genetic studies of complex human diseases. Cite this article: W. Wang, S. Huang, W. Hou, Y. Liu, Q. Fan, A. He, Y. Wen, J. Hao, X. Guo, F. Zhang. Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density. Bone Joint Res 2017;6:572–576.