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Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course.

Original publication

DOI

10.1016/j.ajhg.2017.12.005

Type

Journal article

Journal

Am J Hum Genet

Publication Date

04/01/2018

Volume

102

Pages

88 - 102

Keywords

BMD, CREB3L1, ESR1, GWASs, RANKL, age-dependent effects, bone mineral density, fracture, genetic correlation, genome-wide association studies, meta-regression, total-body DXA, Adolescent, Age Factors, Animals, Bone Density, Child, Child, Preschool, Genetic Loci, Genome-Wide Association Study, Humans, Infant, Infant, Newborn, Mice, Knockout, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Regression Analysis