| Literature DB >> 29304378 |
Carolina Medina-Gomez1, John P Kemp2, Katerina Trajanoska3, Jian'an Luan4, Alessandra Chesi5, Tarunveer S Ahluwalia6, Dennis O Mook-Kanamori7, Annelies Ham8, Fernando P Hartwig9, Daniel S Evans10, Raimo Joro11, Ivana Nedeljkovic12, Hou-Feng Zheng13, Kun Zhu14, Mustafa Atalay11, Ching-Ti Liu15, Maria Nethander16, Linda Broer8, Gudmar Porleifsson17, Benjamin H Mullin14, Samuel K Handelman18, Mike A Nalls19, Leon E Jessen20, Denise H M Heppe21, J Brent Richards22, Carol Wang23, Bo Chawes20, Katharina E Schraut24, Najaf Amin12, Nick Wareham4, David Karasik25, Nathalie Van der Velde26, M Arfan Ikram12, Babette S Zemel27, Yanhua Zhou15, Christian J Carlsson20, Yongmei Liu28, Fiona E McGuigan29, Cindy G Boer8, Klaus Bønnelykke20, Stuart H Ralston30, John A Robbins31, John P Walsh14, M Carola Zillikens8, Claudia Langenberg4, Ruifang Li-Gao32, Frances M K Williams33, Tamara B Harris34, Kristina Akesson35, Rebecca D Jackson36, Gunnar Sigurdsson37, Martin den Heijer38, Bram C J van der Eerden8, Jeroen van de Peppel8, Timothy D Spector33, Craig Pennell23, Bernardo L Horta9, Janine F Felix39, Jing Hua Zhao4, Scott G Wilson40, Renée de Mutsert32, Hans Bisgaard20, Unnur Styrkársdóttir17, Vincent W Jaddoe39, Eric Orwoll41, Timo A Lakka42, Robert Scott4, Struan F A Grant43, Mattias Lorentzon44, Cornelia M van Duijn12, James F Wilson45, Kari Stefansson46, Bruce M Psaty47, Douglas P Kiel48, Claes Ohlsson49, Evangelia Ntzani50, Andre J van Wijnen51, Vincenzo Forgetta22, Mohsen Ghanbari52, John G Logan53, Graham R Williams53, J H Duncan Bassett53, Peter I Croucher54, Evangelos Evangelou55, Andre G Uitterlinden1, Cheryl L Ackert-Bicknell56, Jonathan H Tobias57, David M Evans2, Fernando Rivadeneira58.
Abstract
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.Entities:
Keywords: BMD; CREB3L1; ESR1; GWASs; RANKL; age-dependent effects; bone mineral density; fracture; genetic correlation; genome-wide association studies; meta-regression; total-body DXA
Mesh：
Year: 2018 PMID： 29304378 PMCID： PMC5777980 DOI： 10.1016/j.ajhg.2017.12.005
Source DB: PubMed Journal: Am J Hum Genet ISSN： 0002-9297 Impact factor: 11.025