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Osteoporosis is a complex disease with a strong genetic component. Genome-wide association studies (GWAS) have been very successful at identifying common genetic variants associated with bone parameters. A recently published study documented the results of the largest GWAS for bone mineral density (BMD) performed to date (n = 142,487), identifying 307 conditionally independent single-nucleotide polymorphisms (SNPs) as associated with estimated BMD (eBMD) at the genome-wide significance level. The vast majority of these variants are non-coding SNPs. Expression quantitative trait locus (eQTL) studies using disease-specific cell types have increasingly been integrated with the results from GWAS to identify genes through which the observed GWAS associations are likely mediated. We generated a unique human osteoclast-specific eQTL dataset using cells differentiated in vitro from 158 participants. We then used this resource to characterise the 307 recently identified BMD GWAS SNPs for association with nearby genes (+/- 500 kb). After correction for multiple testing, 24 variants were found to be significantly associated with the expression of 32 genes in the osteoclast-like cells. Bioinformatics analysis suggested that these variants and those in strong linkage disequilibrium with them are enriched in regulatory regions. Several of the eQTL associations identified are relevant to genes that present strongly as having a role in bone, particularly IQGAP1, CYP19A1, CTNNB1 and COL6A3. Supporting evidence for many of the associations was obtained from publicly available eQTL datasets. We have also generated strong evidence for the presence of a regulatory region on chromosome 15q21.2 relevant to both the GLDN and CYP19A1 genes. In conclusion, we have generated a unique osteoclast-specific eQTL resource and have used this to identify 32 eQTL associations for recently identified BMD GWAS loci, which should inform functional studies of osteoclast biology. This article is protected by copyright. All rights reserved.