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Endocrine Abstracts (2018) 59 S2.1 | DOI: 10.1530/endoabs.59.S2.1

SFEBES2018 Symposia Big data and bone disease (3 abstracts)

Osteoporosis Mega GWAS: Paths to causal proteins

Brent Richards


McGill University, Montreal, Canada.


Recent genome-wide association studies of estimated BMD (eBMD) have now included 426,000 individuals, identifying 518 genome-wide significant loci (301 novel), which explain 20% of the total variance in eBMD. Some of these loci are also strongly associated with risk of fracture in a GWAS meta-analysis of 1.2 million individuals. In this talk, I will discuss functional genomics methods that can use this information to identify proteins strongly enriched for known causal proteins. These same proteins have also been shown to have strong effects on the murine skeleton through a large-scale osteoporosis murine knock-out programs. They also are strongly enriched for expression in murine osteocytes. In-depth analysis of one such target gene, DAAM2, in an animal knock-out model and CRISPR studies on human cells, showed clear perturbation of osteoporosis-related metrics. These findings now enable a more clear identification of the causal proteins underlying GWAS associations and explain 66% more variance than the most recent GWAS for eBMD. This comprehensive human and murine genetic atlas also provides new insights into osteoporosis pathophysiology and provides opportunities for drug development.

Volume 59

Society for Endocrinology BES 2018

Glasgow, UK
19 Nov 2018 - 21 Nov 2018

Society for Endocrinology 

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