Searchable abstracts of presentations at key conferences on calcified tissues
Bone Abstracts (2016) 5 OC2.3 | DOI: 10.1530/boneabs.5.OC2.3

1ErasmusMC, Rotterdam, The Netherlands; 2University of Queensland Diamantina Institute, Brisbane, Queensland, Australia; 3Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA; 4COPSAC; University of Copenhagen, Copenhaguen, Denmark; 5Leiden University Medical Centre, Leiden, The Netherlands; 6Federal University of Pelotas, Pelotas, Brazil; 7University of Eastern Finland, Kuopio, Finland; 8California Pacific Medical Center Research Institute, San Francisco, USA; 9University of Western Australia, Perth, Western Australia, Australia; 10University of Gothenburg, Gothenburg, Sweden; 11deCODE Genetics/Amgen, Helsinki, Iceland; 12Boston University, Boston, Massachusetts, USA; 13Lund University, Malmo, Sweden; 14University of Washington, Seattle, USA; 15King’s College, London, UK; 16Laboratory for Epidemiology, Demography, and Biometry, National Institutes of Aging, Bethesda, Maryland, USA; 17University of Bristol, Bristol, UK; 18Harvard, University, Cambridge, Massachusetts, USA.

Introduction: Bone mineral density (BMD) is a highly heritable trait used to assess skeletal health in children and risk of osteoporosis later in life. To date >60 loci associated with bone-related traits measured at different skeletal sites have been identified. We conducted a genome-wide association study (GWAS) meta-analysis of total body (TB-)BMD in children and adults to identify genetic determinants and age-specific effects of loci on this trait.

Methods: We included 26 different study populations comprising ~52 000 individuals with DXA measurements at different age ranges (0–15 years, n=11 800; 15–45 years, n=10 600; and >45 years, n=30 500) and genetic data imputed to the 1000 Genomes reference panel. Inverse variance meta-analysis was performed on TB-BMD adjusted for sex, age, weight, height and population stratification, for all the data and within each age strata. Genome-wide significance (GWS) was set at P<5×10−8. We compared effect sizes of leading variants between the two extreme groups.

Results: We identified GWS variants in 45 loci of which 16 are novel. Of these, 7 novel signals map in close vicinity of genes with a proven role in bone metabolism, EN1, AQP1, RIC8A, CSF1, SLC8A1-AS1, MAFB and SMAD3. Additionally, we identified loci with known skeletal specificity (SOX6, LIN7C, RIN3, ABCF2), age heterogeneity (CPED1, C17orf53) and bone compartment specificity (trabecular volumetric BMD, FMN2; or heel ultrasound, TMEM135). The strongest age-specific effects were found for variants in ESR1 with GWS effect (β=0.07 S.D., P=9.3×10−13) only in adults (Phet=3×10−12) and RIN3 with GWS effect (β=0.1 S.D., P=1×10−8) only in children (Phet=7×10−10).

Conclusion: TB-BMD is a relevant trait for genetic studies of osteoporosis, capable of identifying (novel) variants influencing different bone compartments at different skeletal sites. Applying an age-stratified GWAS approach allowed us to identify loci exerting effects at different stages of the lifespan, helping to unveil further the complex genetic architecture of osteoporosis.

Volume 5

43rd Annual European Calcified Tissue Society Congress

Rome, Italy
14 May 2016 - 17 May 2016

European Calcified Tissue Society 

Browse other volumes

Article tools

My recent searches

No recent searches.