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Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.

ABSTRACT: Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10(-4), Bonferroni corrected), of which six reached P < 5 × 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.

SUBMITTER: Estrada K

PROVIDER: S-EPMC3338864 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.

Estrada Karol K Styrkarsdottir Unnur U Evangelou Evangelos E Hsu Yi-Hsiang YH Duncan Emma L EL Ntzani Evangelia E EE Oei Ling L Albagha Omar M E OM Amin Najaf N Kemp John P JP Koller Daniel L DL Li Guo G Liu Ching-Ti CT Minster Ryan L RL Moayyeri Alireza A Vandenput Liesbeth L Willner Dana D Xiao Su-Mei SM Yerges-Armstrong Laura M LM Zheng Hou-Feng HF Alonso Nerea N Eriksson Joel J Kammerer Candace M CM Kaptoge Stephen K SK Leo Paul J PJ Thorleifsson Gudmar G Wilson Scott G SG Wilson James F JF Aalto Ville V Alen Markku M Aragaki Aaron K AK Aspelund Thor T Center Jacqueline R JR Dailiana Zoe Z Duggan David J DJ Garcia Melissa M Garcia-Giralt Natàlia N Giroux Sylvie S Hallmans Göran G Hocking Lynne J LJ Husted Lise Bjerre LB Jameson Karen A KA Khusainova Rita R Kim Ghi Su GS Kooperberg Charles C Koromila Theodora T Kruk Marcin M Laaksonen Marika M Lacroix Andrea Z AZ Lee Seung Hun SH Leung Ping C PC Lewis Joshua R JR Masi Laura L Mencej-Bedrac Simona S Nguyen Tuan V TV Nogues Xavier X Nogues Xavier X Patel Millan S MS Prezelj Janez J Rose Lynda M LM Scollen Serena S Siggeirsdottir Kristin K Smith Albert V AV Svensson Olle O Trompet Stella S Trummer Olivia O van Schoor Natasja M NM Woo Jean J Zhu Kun K Balcells Susana S Brandi Maria Luisa ML Buckley Brendan M BM Cheng Sulin S Christiansen Claus C Cooper Cyrus C Dedoussis George G Ford Ian I Frost Morten M Goltzman David D González-Macías Jesús J Kähönen Mika M Karlsson Magnus M Khusnutdinova Elza E Koh Jung-Min JM Kollia Panagoula P Langdahl Bente Lomholt BL Leslie William D WD Lips Paul P Ljunggren Östen Ö Lorenc Roman S RS Marc Janja J Mellström Dan D Obermayer-Pietsch Barbara B Olmos José M JM Pettersson-Kymmer Ulrika U Reid David M DM Riancho José A JA Ridker Paul M PM Rousseau François F Slagboom P Eline PE Tang Nelson L S NL Urreizti Roser R Van Hul Wim W Viikari Jorma J Zarrabeitia María T MT Aulchenko Yurii S YS Castano-Betancourt Martha M Grundberg Elin E Herrera Lizbeth L Ingvarsson Thorvaldur T Johannsdottir Hrefna H Kwan Tony T Li Rui R Luben Robert R Medina-Gómez Carolina C Palsson Stefan Th ST Reppe Sjur S Rotter Jerome I JI Sigurdsson Gunnar G van Meurs Joyce B J JB Verlaan Dominique D Williams Frances M K FM Wood Andrew R AR Zhou Yanhua Y Gautvik Kaare M KM Pastinen Tomi T Raychaudhuri Soumya S Cauley Jane A JA Chasman Daniel I DI Clark Graeme R GR Cummings Steven R SR Danoy Patrick P Dennison Elaine M EM Eastell Richard R Eisman John A JA Gudnason Vilmundur V Hofman Albert A Jackson Rebecca D RD Jones Graeme G Jukema J Wouter JW Khaw Kay-Tee KT Lehtimäki Terho T Liu Yongmei Y Lorentzon Mattias M McCloskey Eugene E Mitchell Braxton D BD Nandakumar Kannabiran K Nicholson Geoffrey C GC Oostra Ben A BA Peacock Munro M Pols Huibert A P HA Prince Richard L RL Raitakari Olli O Reid Ian R IR Robbins John J Sambrook Philip N PN Sham Pak Chung PC Shuldiner Alan R AR Tylavsky Frances A FA van Duijn Cornelia M CM Wareham Nick J NJ Cupples L Adrienne LA Econs Michael J MJ Evans David M DM Harris Tamara B TB Kung Annie Wai Chee AW Psaty Bruce M BM Reeve Jonathan J Spector Timothy D TD Streeten Elizabeth A EA Zillikens M Carola MC Thorsteinsdottir Unnur U Ohlsson Claes C Karasik David D Richards J Brent JB Brown Matthew A MA Stefansson Kari K Uitterlinden André G AG Ralston Stuart H SH Ioannidis John P A JP Kiel Douglas P DP Rivadeneira Fernando F

Nature genetics 20120415 5

Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identifi ...[more]

PMID: 22504420

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Project description:BackgroundOsteoporosis is characterised by a reduction of bone mineral density (BMD) and predisposition to fracture. Bone microarchitecture, measured by high resolution peripheral quantitative computed tomography (HR-pQCT), has been related to fragility fractures and BMD and has been the subject of large-scale genome-wide analysis. We investigated whether fracture was related to baseline values and longitudinal changes in bone microarchitecture and whether bone microarchitecture was associated with established BMD loci.Methods115 males and 99 females (aged 72-81 at baseline) from the Hertfordshire Cohort Study (HCS) were analysed. Fracture history was determined in 2011-2012 by self-report and vertebral fracture assessment. Participants underwent HR-pQCT scans of the distal radius and tibia in 2011-2012 and 2017. Previous fracture in relation to baseline values and changes in tibial HR-pQCT parameters was examined using sex-adjusted logistic regression with and without adjustment for age, sociodemographic, lifestyle and clinical characteristics; baseline values and changes in parameters associated with previous fracture were then examined in relation to four established BMD loci after adjustment for sex and age.ResultsPrevious fracture was related to: higher trabecular area (fully-adjusted odds ratio [95% CI] per SD greater baseline value: 2.18 [1.27,3.73], p = 0.005); lower total volumetric BMD (0.53 [0.34,0.84], p = 0.007), cortical area (0.53 [0.30,0.95], p = 0.032), cortical BMD (0.56 [0.36,0.88], p = 0.011) and cortical thickness (0.45 [0.27,0.77], p = 0.004); and greater declines in trabecular BMD (p = 0.001). Associations were robust in sex- and fully-adjusted analysis. Relationships between BMD loci and these HR-pQCT parameters were weak: rs3801387 (WNT16) was related to decline in trabecular BMD (p = 0.011) but no other associations were significant (p > 0.05).ConclusionBaseline values of HR-pQCT parameters and greater decline in trabecular BMD were associated with fracture. Change in trabecular BMD was associated with WNT16 which has been demonstrated to influence bone health in murine models and human genome-wide association studies (GWAS).

Project description:Osteoporosis is a common and debilitating bone disease that is characterised by a low bone mineral density (BMD), a highly heritable trait. Genome-wide association studies (GWAS) have proven to be very successful in identifying common genetic variants associated with BMD adjusted for age, gender and weight, however a large portion of the genetic variance for this trait remains unexplained. There is evidence to suggest significant genetic correlation between body size traits and BMD. It has also recently been suggested that unintended bias can be introduced as a result of adjusting a phenotype for a correlated trait. We performed a GWAS meta-analysis in two populations (total n = 6,696) using BMD data adjusted for only age and gender, in an attempt to identify genetic variants associated with BMD including those that may have potential pleiotropic effects on BMD and body size traits.We observed a single variant, rs2566752, associated with spine BMD at the genome-wide significance level in the meta-analysis (P = 3.36 × 10(-09)). Logistic regression analysis also revealed an association between rs2566752 and fracture rate in one of our study cohorts (P = 0.017, n = 5,654). This is an intronic variant located in the wntless Wnt ligand secretion mediator (WLS) gene (1p31.3), a known BMD locus which encodes an integral component of the Wnt ligand secretion pathway. Bioinformatics analyses of variants in moderate LD with rs2566752 produced strong evidence for a regulatory role for the variants rs72670452, rs17130567 and rs1430738. Expression quantitative trait locus (eQTL) analysis suggested that the variants rs12568456 and rs17130567 are associated with expression of the WLS gene in whole blood, cerebellum and temporal cortex brain tissue (P = 0.034-1.19 × 10(-23)). Gene-wide association testing using the VErsatile Gene-based Association Study 2 (VEGAS2) software revealed associations between the coiled-coil domain containing 170 (CCDC170) gene, located adjacent to the oestrogen receptor 1 (ESR1) gene, and BMD at the spine, femoral neck and total hip sites (P = 1.0 × 10(-06), 2.0 × 10(-06) and 2.0 × 10(-06) respectively).Genetic variation at the WLS and CCDC170/ESR1 loci were found to be significantly associated with BMD adjusted for only age and gender at the genome-wide level in this meta-analysis.

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Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.

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Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.

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