Background Osteoporosis is a complex disease with a strong genetic contribution. A recently published genome-wide association study (GWAS) for estimated bone mineral density (eBMD) identified 1103 independent genome-wide significant association signals. Most of these variants are non-coding, suggesting that regulatory effects may drive many of the associations. To identify genes with a role in osteoporosis, we integrate the eBMD GWAS association results with those from our previous osteoclast expression quantitative trait locus (eQTL) dataset. Results We identify sixty-nine significant cis -eQTL effects for eBMD GWAS variants after correction for multiple testing. We detect co-localisation of eBMD GWAS and osteoclast eQTL association signals for 21 of the 69 loci, implicating a number of genes including CCR5 , ZBTB38 , CPE , GNA12 , RIPK3 , IQGAP1 and FLCN . Summary-data-based Mendelian Randomisation analysis of the eBMD GWAS and osteoclast eQTL datasets identifies significant associations for 53 genes, with TULP4 presenting as a strong candidate for pleiotropic effects on eBMD and gene expression in osteoclasts. By performing analysis using the GARFIELD software, we demonstrate significant enrichment of osteoporosis risk variants among high-confidence osteoclast eQTL across multiple GWAS P value thresholds. Mice lacking one of the genes of interest, the apoptosis/necroptosis gene RIPK3 , show disturbed bone micro-architecture and increased osteoclast number, highlighting a new biological pathway relevant to osteoporosis. Conclusion We utilise a unique osteoclast eQTL dataset to identify a number of potential effector genes for osteoporosis risk variants, which will help focus functional studies in this area.

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人类破骨细胞骨质疏松症风险变异的遗传调控作用表征

背景 骨质疏松症是一种复杂的疾病，具有很强的遗传作用。最近发表的用于估计骨矿物质密度 (eBMD) 的全基因组关联研究 (GWAS) 确定了 1103 个独立的全基因组显着关联信号。大多数这些变体是非编码的，这表明调节效应可能会驱动许多关联。为了识别在骨质疏松症中起作用的基因，我们将 eBMD GWAS 关联结果与我们之前的破骨细胞表达数量性状基因座 (eQTL) 数据集的结果相结合。结果我们在多重测试校正后确定了 eBMD GWAS 变体的 69 个显着的 cis -eQTL 效应。我们检测了 69 个基因座中 21 个的 eBMD GWAS 和破骨细胞 eQTL 关联信号的共定位，涉及许多基因，包括 CCR5、ZBTB38、CPE、GNA12、RIPK3、IQGAP1 和 FLCN。eBMD GWAS 和破骨细胞 eQTL 数据集的基于汇总数据的孟德尔随机化分析确定了 53 个基因的显着关联，其中 TULP4 是对 eBMD 和破骨细胞基因表达的多效性影响的有力候选者。通过使用 GARFIELD 软件进行分析，我们证明了在多个 GWAS P 值阈值的高置信度破骨细胞 eQTL 中骨质疏松症风险变异的显着富集。缺乏感兴趣的基因之一，即凋亡/坏死性凋亡基因 RIPK3 的小鼠显示出骨微结构紊乱和破骨细胞数量增加，突出了与骨质疏松症相关的新生物学途径。结论我们利用一个独特的破骨细胞 eQTL 数据集来鉴定一些骨质疏松症风险变异的潜在效应基因，