Characterisation of genetic regulatory effects for osteoporosis risk variants in human osteoclasts

Benjamin Mullin, Jennifer Tickner, Kun Zhu, Jacob Kenny, Shelby Mullin, Suzanne J. Brown, Frank Dudbridge, Nathan Pavlos, Edward S. Mocarski, John P Walsh, Jiake Xu, Scott Wilson

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


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 1,103 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 eQTL dataset.
Results: We identify sixty-nine significant cis-eQTL effects for eBMD GWAS variants after correction for multiple testing. We detect co-localization 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 Randomization 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 utilize 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.
Original languageEnglish
Article number80
JournalGenome Biology
Issue number1
Publication statusPublished - 26 Mar 2020


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