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Using epigenomic data to inform genome-wide association studies of bone mineral density

   
@article{ATM13047,
	author = {John A. Morris},
	title = {Using epigenomic data to inform genome-wide association studies of bone mineral density},
	journal = {Annals of Translational Medicine},
	volume = {4},
	number = {24},
	year = {2016},
	keywords = {},
	abstract = {Osteoporosis is primarily an aging-related disease, characterized by decreased bone strength and increased fracture risk. The incidence of osteoporosis is increasing worldwide due to aging populations and is a major healthcare burden. For instance, osteoporosis-related healthcare costed China \$9.45 billion USD in 2010, will likely double by 2035, and increase to \$25 billion USD by 2050 (1). Bone mineral density (BMD) is used to predict fracture risk and is the primary clinical measurement used to diagnose osteoporosis. Genome-wide association studies (GWAS) of BMD have successfully identified many genetic loci that influence osteoporosis (2-12), but like most GWAS, these studies used stringent statistical significance thresholds to limit false positive results at the expense of false negatives.},
	issn = {2305-5847},	url = {https://atm.amegroups.org/article/view/13047}
}