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

The University of Western Australia
Mullin, Benjamin H. ; Tickner, Jennifer ; Zhu, Kun ; Kenny, Jacob ; Mullin, Shelby ; Brown, Suzanne J. ; Dudbridge, Frank ; Pavlos, Nathan J. ; Mocarski, Edward S. ; Walsh, John ; Xu, Jiake ; Wilson, Scott G.
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.6084/m9.figshare.c.4909641.v1&rft.title=Characterisation of genetic regulatory effects for osteoporosis risk variants in human osteoclasts&rft.identifier=10.6084/m9.figshare.c.4909641.v1&rft.publisher=Figshare&rft.description=Abstract 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.&rft.creator=Mullin, Benjamin H. &rft.creator=Tickner, Jennifer &rft.creator=Zhu, Kun &rft.creator=Kenny, Jacob &rft.creator=Mullin, Shelby &rft.creator=Brown, Suzanne J. &rft.creator=Dudbridge, Frank &rft.creator=Pavlos, Nathan J. &rft.creator=Mocarski, Edward S. &rft.creator=Walsh, John &rft.creator=Xu, Jiake &rft.creator=Wilson, Scott G. &rft.date=2020&rft.relation=http://research-repository.uwa.edu.au/en/publications/72a9a54c-44a6-4052-b075-20a7c0cb08f5&rft_subject=FOS: Biological sciences&rft_subject=Genetics&rft.type=dataset&rft.language=English Access the data

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Abstract 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.

Notes

External Organisations
Sir Charles Gairdner Hospital; University of Leicester; Emory University; King's College London
Associated Persons
Shelby Mullin (Creator); Suzanne J. Brown (Creator)Frank Dudbridge (Creator); Edward S. Mocarski (Creator)

Issued: 2020

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