Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR) = 58, P = 1 × 10−75) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P < 0.0001). In-depth analysis of one gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This genetic atlas provides evidence linking associated SNPs to causal genes, offers new insight into osteoporosis pathophysiology, and highlights opportunities for drug development.
Access optionsAccess options
Subscribe to Journal
Get full journal access for 1 year
only $18.75 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Human genotype and phenotype data on which the results of this study were based are available upon application from the UK Biobank (http://www.ukbiobank.ac.uk). GWAS summary statistics for eBMD and fracture can be downloaded from the GEFOS website (http://www.gefos.org/). RNA-seq and ATAC-seq data generated for human osteoblast cell lines, including re-called DHS peaks from human primary osteoblasts, can be downloaded from the Gene Expression Omnibus (accession number GSE120755). Mouse phenotype data are available online from the IMPC (http://www.mousephenotype.org) and OBCD (http://www.boneandcartilage.com).
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This research has been conducted using the UK Biobank Resource (accession IDs: 24268, 12703 and 4580). J.B.R. was supported by the Canadian Institutes of Health Research, the Canadian Foundation for Innovation and the Fonds de Recherche Santé Québec (FRSQ), and a FRQS Clinical Research Scholarship. TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’s NHS Foundation Trust in partnership with King’s College London. J.A.M. was funded by the Canadian Institutes of Health Research. D.M.E. was funded by a National Health and Medical Research Council Senior Research Fellowship (APP1137714) and funded by a Medical Research Council Programme Grant (MC_UU_12013/4). J.P.K. was funded by a University of Queensland Development Fellowship (UQFEL1718945). C.L.G. was funded by Arthritis Research UK (ref; 20000). G.R.W., J.H.D.B., and P.I.C. were funded by the Wellcome Trust (Strategic Award grant number 101123; project grant 094134), and P.I.C. was also funded by the Mrs. Janice Gibson and the Ernest Heine Family Foundation. D.K. was supported by Israel Science Foundation grant #1283/14. Y-H.H. was funded by US NIH NIAMS 1R01AR072199. F.R., C.M-G., and K.T. were funded by the Netherlands Organization for Health Research and Development (ZonMw VIDI 016.136.361 grant). C.L.A-B. was funded by NIH/NIAMS AR063702 AR060981. D.P.K. was funded by grants from the National Institute of Arthritis Musculoskeletal and Skin Diseases R01 AR041398, R01 AR072199. S.Y. was funded by the Australian Government Research Training Program Scholarship. J.R. and S.K. were funded by the Genetic Factors of Osteoporosis-GEFOS EU FP7 Integrated Project Grant Reference: 201865 2008-12 and 2007-12 UK NIHR Biomedical Research Centre Grant (Musculoskeletal theme) to Cambridge Clinical School. C.O. was supported by the Swedish Research Council, Swedish Foundation for Strategic Research, ALF/LUA research grant from the Sahlgrenska University Hospital, Lundberg Foundation, European Calcified Tissue Society, Torsten and Ragnar Söderberg’s Foundation, Novo Nordisk Foundation, and Knut and Alice Wallenberg Foundation. M.T.M. was supported by NIH grant R35 GM119703. We thank M. Schull for assistance with high-performance computing at the University of Queensland Diamantina Institute and T. Winkler for invaluable technical support for the EasyStrata Software used in this study. We thank the Sanger Institute’s Research Support Facility, Mouse Pipelines and Mouse Informatics Group who generated the mice and collected materials for this manuscript. We would like to thank the research participants and employees of 23andMe, Inc. for making this work possible.
About this article
Nature Reviews Endocrinology (2019)