Identification of 153 New Loci Associated with Heel Bone

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. or or J.B.R. ( 25 of University Orthopaedics, of Rochester, Rochester, New York, USA. and Biotechnology Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia. USA. Montréal, Québec, Canada. Department of Oncology, McGill University, Montréal, Québec, Canada. Hospital Southampton NHS Foundation Trust, Southampton, UK. Epidemiology Unit, University of Southampton, Southampton, UK. Campus, Hinxton, UK. Cambridgeshire, 11 South Wales, Sydney, New South Wales, Australia. Perth, Western Australia, Australia. 6 of Human Genetics, McGill University, Montréal, Québec, Canada. of Bristol, Bristol, UK. also has 1 sequencing whole-genome on based imputation deep risk fracture with associated significantly are that many including trait, the with associated loci 73 at variants common fied treatment and strong a as well as is for a factor risk for osteoporosis, key indicator its diagnosis BMD Low risk. fracture and fragility skeletal increased to leading microarchitecture, bone in deterioration and mass bone by low characterized disorder is a age-related common Osteoporosis of analysis prediction; we 1 that by wide Osteoporosis Graham R Williams Jonathan H Tobias Celia M T Greenwood Fiona Kussy Natalie C Butterfield Andrea S Pollard Scott E Youlten John P Kemp osteoporosis mineral density and involvementfunctional of GPC6 in Identification of 153 new loci associated with heel bone Nature Ge Nature Received 31 December 2016; accepted 11 August 2017; published online 4 September 2017; Department Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands. University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia. 53 These These authors contributed equally to this work. Molecular Laboratory,Endocrinology Department of Medicine, Imperial College London, London, UK.

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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. significance ( significance ( testing multiple for at body. the SNPs of sites other at and heel the at sizes effect estimated ( fracture for significance Bonferroni-corrected reached that SNPs association). of evidence poor indicates white and fracture, with association of evidence robust indicates (black points data the of shading the × 10 < 6.6 ( the at ( 1 Figure allele minor with SNPs 17,166,351 of effect additive the tested We ( women) (53% individuals 142,487 from Methods, (Online genotypes genome-wide and measurements eBMD both of control fracture predicts that BMD of estimate of Quantitative ultrasound the heel was used to obtain a non-invasive Genome-wide RESULTS for ( validation genes functional prioritize to approaches complementary and systematic three used We subsequently genome- individuals. 142,487 and in genotypes eBMD wide genetic measured has novel which Study, Biobank identify UK the To in association fracture. genome-wide investigated we BMD, of fragility determinants of treatment and for prevention the targets drug identify may scientists help implicate they pathways biological the and loci genetic new of identification therapies osteoporosis relevant clinically of targets the for BMD spine/hip lumbar with associated previously been had that seven including loci, nine at variants fied ( parameters ultrasound heel used that GWAS ( spine and hip the at BMD DXA-derived risk fracture 80%) with to 50% associated of order the are (on values heritable eBMD highly Ultrasound-derived (eBMD)). BMD estimated as here to (referred calcaneus heel the at typically ultrasound, from derived is individuals, of samples large very in used and be can therefore inexpensive, relatively and safe quick, is that BMD estimating s e l c i t r A SNP). reported the of 1 Mb within region any detect not did DEPICT (i.e., locus a – Because genetic loci associated with BMD are strongly enriched enriched strongly are BMD with associated loci genetic Because c ) Effect size for heel eBMD ( eBMD heel for size ) Effect a

) femoral neck, ( neck, ) femoral eBMD effect size compared with the effect size from a previous GEFOS meta-analysis of DXA-derived BMD for eBMD-associated SNPs. SNPs. eBMD-associated for BMD DXA-derived of meta-analysis GEFOS a previous from size effect the with compared size effect eBMD −9 a

) for eBMD in the UK Biobank study are plotted. The −log The plotted. are study Biobank UK the in eBMD ) for Conditional and joint eBMD (s.d.) P β −0.4 −0.2 < 0.05) in the previous GEFOS-seq analysis.*Multiple conditionally independent variants present at the locus. locus. the at present variants independent conditionally analysis.*Multiple GEFOS-seq previous the in < 0.05) 0.0 0.2 0.4

association −0.4 P < 1.6 × 10 < 1.6 upeetr Fg 2 Fig. Supplementary Supplementary Fig. 1 Fig. Supplementary b Femoral neckBMD SOS ) lumbar spine and ( and spine ) lumbar −0.2 SOS ESR1 T WNT16 * T ESR1

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) are labeled. The blue dashed lines show the strong correlation between between correlation strong the show lines dashed blue The labeled. ) are * Of the 203 loci identified, 153 (75%) regions had not been impli been not GWASsBMD of previous had in cated regions (75%) 153 identified, loci 203 the Of rather = intercept 1.05). regression (LD score polygenicity stratification population than to due was inflation of majority the that cated had been reported as genome-wide significant in previous GWASs previous in significant genome-wide as reported been had ( BMD DXA-derived GWASof GEFOS-seq previous a in trait) any with ( eBMD heel association of evidence strong extremely was there which for SNPs at (e.g., variants multiple included associations 3 Fig. Supplementary null the to relative statistics test ( the of inflation substantial was ( BOLT-REML by herit SNP estimated eBMD the ability of one-third about explained SNPs 307 the in variance ( the eBMD of ~12% explained jointly and Methods)) Biobank UK (Online the in imputed deeply SNPs independent of number ( threshold genome-wide significance revised our surpassed loci 203 at SNPs independent controlling for age, sex and genotyping array. In total, 307 conditionally frequency (MAF) > 0.1% and imputation quality score > 0.4 on eBMD, is deliberately broad and comprehensive with respect to previous previous to GWASs.respect This comprehensive inclusion policy, with however, for called the comprehensive and broad deliberately is ( eBMD significance heel ultrasound-derived GWAS genome-wide of previous a with in identified loci all replicated we and effect), ( sites body other at BMD of MBL Supplementary Table 3 Supplementary Supplementary Table 4 Supplementary λ WNT16 * .0 GC Our study also replicated SNPs in replicated 55 out study also Our that of (>75%) 73 regions and and –log 2 * RSPO ~ RSPO = 1.37), linkage disequilibrium (LD) score regression score (LD) disequilibrium linkage 1.37), = * AQP1 10 ESR1 β ( P AQP1 0. 2. 5. 7. 10.0 3 (s.d.) 0. Supplementary Fig. 3 Fig. Supplementary ) 3 * Any fracture 0 5 0 5 * 0 2 * P were significantly related with fracture after correction correction after fracture with related significantly were < 10 a .4 DVANCE ONLINE PUBLICATION ONLINE DVANCE −30 c Conditional and joint eBMD β (s.d.) ) but little evidence of association ( of association evidence ) but little −0. –0. ). We found it interesting that the list of novel novel of list the that We). interesting it found 0. 0. 0. P 0 2 4 4 2 ). ). Our list of known BMD-associated SNPs BMD-associated known of list Our ).

≤ −0.4 6.6 × 10 × 6.6 P , , RSPO < 0.05 and consistent direction of of direction consistent and 0.05 < Supplementary Table 2 Table Supplementary SOST −0. Forearm BMD 3 WNT16 3 , 4 0 2 * −9 * FGFRL1 , h 16– AQP1 2 , which accounts for the large large the for accounts which , SNP * 2 MBL2 2 * RSPO ( .0 = 0.36). Although there there Although 0.36). = SOST –log Supplementary Table2 Supplementary ESR1 * ~ ~ β The closest gene to the the to gene closest The 3 10 (s.d.) * SLC8A1~ * ( ESR1 P

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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. rs2536195 rs10276670 rs2941741 rs4869744 rs7741021 rs9491689 rs112069922 rs10490046 RSID T in but below), (discussed data Biobank UK the in fracture with tion in at SNPs The studies. those BMD previous with compared study eBMD current the in effect of tions KCNMA1 study. smaller previous, and studies, 1 type between error population ences in in ancestral the differ BMD), DXA-derived versus (ultrasound-derived phenotype in differences specificity, site include loci nonreplicated for reasons represent type 1 errors), we Estrada replicated by 54 of the 64 (84%) meta-analysis SNPs. Possible (GEFOS) SNPs 64 Consortium Osteoporosis the for Factors to Genetic large attention the in our reported restricted we When positives. false GWASs of from smaller some results that may incorporation include SNP). reported the of 1 Mb within region locus. the at present variants independent conditionally *Multiple significant. wide N ( significance genome-wide at frequency allele minor a given at association detect to power 80% for required size effect ( significance genome-wide at frequency allele minor a given at association detect to power 80% for required size effect the shows curve dashed black The loci. novel at SNPs represent circles Blue loci. BMD reported previously at SNPs represent circles Red SNPs. independent conditionally ( size effect analysis 2 Figure Nature Ge Nature (OR) and95%confidenceintervals(CI β rs188810925 rs7209826 rs7099953 rs10668066 ( ed fracturewithinthe past5years( effect allelefrequency; chromosome; BP, base pairpositionofthevariantaccordingtohumanreferencesequenceHg19/GRCh37; C.GENE,closestgene;EA,effectallele;NEA,non-effectEAF, N α ands.e.valuesfromBOLT-LMM weretransformedviathefollowingformula:( able able 1 = 483,230 individuals in the full UK Biobank study. GWS, genome- study. GWS, Biobank UK full the in individuals = 483,230 =8,540cases/131,333 controls). = 6.6 × 10 = 6.6

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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. and and in as defined are plots the of Elements (toughness). fracture before dissipated energy and stiffness, load, fracture load, maximum load, yield show graphs The (stiffness). phase and wild-type from femurs of testing bend three-point in as defined are plots the of Elements BMD. cortical and cortical diameter internal (Ct.Th), thickness cortical (Tb.Sp), spacing trabecular (Tb.Th), thickness trabecular (Tb.N), number trabecular (BV/TV), volume tissue and wild-type from (right) bone cortical mid-diaphysis and (left) bone trabecular femur individual from parameters lines), center (solid mean the represent plots The (C57BL/6). background genetic and sex age, identical of mice wild-type >250 from derived ranges reference show bottom the at graphs The content. mineral bone high indicates pink and and (WT) wild-type 4 Figure variants. common versus rare to attributed effects in difference 6.5-fold a found we variants, significant genome-wide of BMP5 genes the near variants rare including loci, unreported previously in ( estimates correlation genetic The regression. LD score via estimated ( correlation Genetic LDHub. in implemented regression 3 Figure s e l c i t r A ( bars Scale Methods. Online the in described as analysis Gpc6 c a

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1.0 s.d. (dotted lines) and and lines) (dotted s.d. 1.0 Anorexia nervosa d Load (N) 10 12 c 20 40 60 80 ) Representative load-displacement curves from destructive destructive from curves load-displacement ) Representative − 0 0 0 Displacement (mm) Major depressiveNeuroticism disorder / − 0 0 Tb.Th (mm) 0.02 0.04 0.06 0.08 Yield mice. The graphs below show trabecular bone volume/ bone trabecular show below graphs The mice. load a Autism spectrumBipolar disorder FAM9B DVANCE ONLINE PUBLICATION ONLINE DVANCE 0 .2 Gpc6 Gpc WT

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a Coronary artery disease . .

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- - , © 2017 Nature America, Inc., part of Springer Nature. All rights reserved. pancy sites (DHSs) SNP lead ( independent conditionally each around SNPs causal ble Table8 ous These coding variation at genome-wide significant loci ( variants. and genes software Predictor Variant candidate the Effect included likely prioritize to tools ics humans. in genomics functional and statistical bioinformatic, one: Strategy Gene randomization Mendelian through and diabetes 2 type and traits common several of diseases with eBMD, etiology as has been shown previously genetic for findings BMD, adiposity These shared a diabetes. 2 support type and disease heart coronary ratio, waist-to-hip circumference, waist BMI, with correlated genetically ( arthritis matoid rheu and menarche at age height, level, cholesterol LDL level, terol Fig. ( diseases and traits complex other of range ( loci significant genome-wide the at observed directions concordant the with ment ( eBMD with correlation genetic positive moderate −0.59, −0.35). Further, measures of BMD at other skeletal sites ( showed fracture with correlated negatively and strongly was eBMD increased which Genetically (BMI), genetic). partially index itself is mass body as such variable underlying an by mediated is variable other the and eBMD between relationship the one (i.e., arises whether causes variable the other,etiology or whether it or eases although says about traits, nothing how shared this genetic dis two between shared are factors risk genetic which to degree the 247 score with LD used we regression etiology traits, relevant genetic biomedically shared and a diseases other has eBMD whether test To Shared ( fracture of odds the and eBMD on variants eBMD significant wide of genome- effects the between relationship an inverse We observed values from the study GEFOS-seq ( association nominal showed SNPs both (although previously fracture of risk or BMD with ated at variants loci, 12 these ( findings these with consistent were height) standing from (i.e., fall simple a from resulting fracture a reported had who women) (69% individuals 8,540 only including analyses sensitivity fracture, with ( testing associated multiple for were controlling after SNPs eBMD 12 that observed we future of etiology a shared predictive suggesting thus are fracture, and low-trauma BMD low by high-trauma as predicted are giving mechanism, fractures without trauma the to fracture, consideration previous a UK special in reported women) had (58% who individuals Biobank 14,492 and SNPs identified We eBMD-associated fracture. between relationship the tested We Effects Estrada from results previous replicating 6 Table Supplementary Nature Ge Nature of evidence Supplementary Table 9 Supplementary Fig. 5 Fig. Supplementary e lo se wehr BD s eeial creae wt a with correlated genetically is eBMD whether asked also We 3 ). ). We weak and observed negative correlation with HDL choles

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sets, sets, and more identified (FDR: than enriched 5%) 1,000 significantly also were entries). significant system 5/7 entries; cells, tissue connective entries; significant musculoskeletal significant 6/7 tissue, membrane 7/12 system, the (cardiovascular than overrepresented other systems mapping to eBMD loci came from chondrocytes and cartilage, although 6 Fig. ( annotations cell tissue MeSH and the from defined entries the among 5%) (FDR: and tions tissue (MeSH) Heading Subject annotations cell-type Medical 209 of any in sion COL21A1 as such metabolism, 0.05). < role in bone an (FDR) with established were several genes 273 Among these rate discovery (false signals association eBMD the tool computational DEPICT integration. the used we approach, gene-prioritization second expression-prioritized the For data-driven two: Strategy in described osteoblasts skeletal phenotyping was undertaken as part of the Origins of Bone Bone of Origins the of part as undertaken was phenotyping skeletal mice had been generated for IMPC 120 of the prioritized genes, the and bespoke for Institute Sanger Trust Wellcome the at generated mice knockout from genes with Wegenes these compared identified all genes within 1 Mb of lead SNPs at associated eBMD loci. SNPs. lead of genes Mb 1 within selected of knockout of phenotyping deep three: Strategy ( abnormalities skeletal data phenotype available, and 62 (33%) of included phenotypes those 189 of (78%) the 241 genes had DEPICT-prioritized mouse knockout We genes. that found of any prioritized of the deletion with out mice “URLs”) or Mouse Genome Informatics (“URLs”) databases in knock reported in the International Mouse Phenotyping Consortium (IMPC; osteoclasts). and osteocytes osteoblasts, of each ( osteoclasts and osteocytes osteoblasts, in expressed of This represents the a enrichment cell three types. genes substantial Table 14 osteoblasts, 66% in osteoclasts and 83% in osteocytes ( known homolog were RNAs), long in noncoding with 92% expressed prioritized, 241 had mouse homologs (the majority that did not have a genes 273 the Among osteocytes. and osteoclasts osteoblasts, mouse ( etc.) pathways other pathways, worthy melanogenesis, (oncogenic investigation of and further pathways, signaling Hedgehog and WNT the gene sets involved in bone mineralization and development, cadherin, results implicating similar produced of software variant associations) ( development) cell complex, eling remod chromatin and regulation, binding factor highlighted transcription (e.g., also were processes biological global More signaling). WNT or BMP differentiation, cell stem mesenchymal (e.g., biology pathways or involved in development) signaling bone ment, cartilage develop craniofacial abnormal fusion, vertebral development, tissue mineralized of regulation (e.g., growth skeletal to related were ters clus most that showed gene-sets’ ‘meta 35 in Clustering sets. gene We also tested the DEPICT-prioritized genes for enriched gene gene enriched for genes DEPICT-prioritized the tested also We expres Wefor genes enriched DEPICT-prioritized the tested next We then investigated whether a skeletal phenotype had been been had phenotype skeletal a whether investigated then We in expression for DEPICT by prioritized genes all tested We enrichment with the gene-set MAGENTAAnalysis (meta-analysis Supplementary Table 13 Supplementary ). The strongest evidence of enriched expression of the genes genes the of expression enriched of evidence strongest The ). ). ). In all, 95.4% of these genes were expressed in at least one of and and 3 3 Supplementary Note 1 Supplementary ( SOST upeetr Tbe 10 Table Supplementary 3 4 ( . We identified 273 genes as most likely to drive to drive likely as most genes . 273 We identified 3 Supplementary Table 11 Supplementary 4 . We identified 62 tissue or cell-type annota cell-type or tissue 62 We . identified BMP2 Supplementary Table 14 Supplementary upeetr Tbe 12 Table Supplementary The third gene-prioritization approach approach gene-prioritization third The , , ). LRP5 Supplementary Fig. 7 Fig. Supplementary . , , EN1 ). These results are fully fully are results These ). , , RUNX2 ). ). s e l c i t r A , , Supplementary Supplementary Supplementary , , P 3 JAG1 < 0.0001 for for 0.0001 < 5 . Knockout Knockout . ). , , ESR1 ------,

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. underlying the role of GPC6 in the pathogenesis of osteoporosis. of pathogenesis the in GPC6 of role the underlying mechanisms molecular and cellular the characterize in to required are studies further Thus, condition. the of festations mani adult regarding available is information no 1, omodysplasia of phenotype the Although permuted s.d., (+2.1 load P yield in increase an was abnormalities structural these of consequence biomechanical The mice. wild-type permuted s.d., (+2.3 thickness cortical bone mineral content (+2.4 s.d., permuted respectively). 0.016, permuted and s.d., −2.17 and (−1.95 mice wild-type of those 1, omodysplasia of phenotype Gpc6 C57BL/6 the identical with of Consistent mice control background. wild-type >250 for data with transcription factor in osteoblast differentiation. canonical through mass Wnt and signaling, bone influences that receptor important ( fold-enrichment) log (1.95 genes known to have involvement key skeleton, the with such as Gpc6 ( mice in osteocytes and locus. this at association the for ( with association of evidence some cell several in DHSs within ( types present was it that and 2.4), = factor ( low- eBMD a with was associated significantly was rs1933784 that 0.05) = (MAF that SNP frequency observed We variant. functional and ( locus this at rs147720516 SNP lead independent conditionally the with disequilibrium linkage high in the at association osteoporosis. in implicated been previously not has This indicates a role for dysmorphism. craniofacial with dwarfism by short-limbed acterized 1 (OMIM in mutations Loss-of-function family. protein proteoglycan sulfate heparan membrane-bound anchored, ( study further for gene-prioritization strategies identified ( mice mutant in phenotype skeletal abnormal an with when associated were that, genes disrupted, 100 identified we strategies, parallel these Using GPC6 knockout unselected mice 100 of analysis previous a of results the with abnormal bone structure, representing twofold enrichment compared (36%) of these 120 prioritized genes were associated with significantly mice with an identical C57BL/6 genetic background. We found that 43 control >250 from data reference normal with results our compared We testing. biomechanical and micro-CT microradiography, X-ray digital using samples, skeletal of analysis functional and structural Program Disease Cartilage and s e l c i t r A available statistics summary genome-wide full with PhenoScanner, P

= 8 × 10 × 8 = = 4.7 × 10 × 4.7 = Finally, we queried 87 separate GWASs using the web utility utility web the using GWASs separate 87 queried we Finally, female adult Weanalyzed identified DEPICT functional a for evidence provided pipeline bioinformatics Our GPC6 3 had a similar level of enrichment (1.76 log fold-enrichment) as fold-enrichment) log (1.76 enrichment of level similar a had − 6 /

Supplementary Table Supplementary 16 ( − findings mice had femurs and vertebrae that were shorter than than shorter were that vertebrae and femurs had mice χ P noe a ebr f h glycosylphosphatidylinositol- the of member a encodes 2 = 2.3 × 10 × 2.3 = 25831 = 8.359, 8.359, = −3 −3 ) that reflected increased material elasticity ( elasticity material increased reflected that ) Supplementary Tables 14 Supplementary ) ( ) 5 Supplementary Table 16 Supplementary ), ), a char rare dysplasia skeletal autosomal recessive Supplementary Table 16 Supplementary GPC6 Runx2 P = 0.0038) ( 0.0038) = −10 GPC6 GPC6 ), with high causal probability (log probability causal high with ), locus. A single SNP in in SNP single A locus. (1.73 log (1.73 fold-enrichment), a encoding key upeetr Tbe 14 Table Supplementary Gpc6 as the gene most likely to be responsible be to likely most gene the as Gpc6 Gpc6 in biology skeletal upeetr Fg 8 Fig. Supplementary − ). The rs1933784 ). variant The showed also rs1933784 3 / Supplementary Table 15 Supplementary − 6 − . Specifically, we carried out both both out carried we Specifically, . mice also had increased femoral femoral increased had also mice − / Gpc6 / − − GPC6 mice is consistent with human human with consistent is mice mice and compared the results results the compared and mice r 2 GPC6 > 0.9), was a plausible causal causal plausible a was 0.9), > GPC6 P is expressed in osteoblasts osteoblasts in expressed is = 5 × 10 × 5 = and P expression in osteoblasts osteoblasts in expression ). = 3 × 10 ). , so we selected this gene result in omodysplasia omodysplasia in result 15 3 ). However, all three three However, ). all 7 , although , the although gene −3 GPC6 −4 ) compared with with compared ) ). In osteocytes, osteocytes, In ). , noig an encoding ), ) ) and increased Gpc6 , rs1933784, rs1933784, , ). P − 10 Fig. Fig. / = 0.06 0.06 = − Bayes Bayes mice mice Lrp5 4 ). ). - -

relationship relationship with MAF the within limits of power the of statistical the lying BMD is highly polygenic. The observed effect sizes follow a close osteoporosis. of physiology that evidence functional provided and study future for genes prioritized We have fracture. of risk the influence also variants BMD-associated several of variance explained for this trait. Further, we have demonstrated that the amount and doubled ated threefold BMD in with humans almost associ loci With of study,number this the genetic we have increased DISCUSSION (all study present the SNPs in independent conditionally lead the with LD appreciable in not were scans these in reported SNPs lead the although height, facial lower and neuroticism disease, Alzheimer’s bronchodilation, after FEV1 disorder, hyperactivity deficit attention with association of evidence of region the in SNPs 2017). March 22 catalog NHGRI–EBI the for with rs72635657 femoral neck BMD ( a with tions at rs147720516) eBMD the (rs72635657, SNPs for significant genome-wide independent for conditionally the as suitable candidates for pharmacological manipulation. pharmacological for candidates suitable as confirmed be can molecules these before considered be to need will etc.) effects, side of unintended likelihood (the therapy, factors other pharmaco for targets promising be to seem proteins associated and GPC6 However, directly. although that we caution possibilities these and global of tissue-specific availability The activity. and binding factor growth regulate specifically that HS6ST1–3) and HS2ST GLCE, (NDST1–4, enzymes modification and (EXT1–2) synthetic sulfate heparan the also but GPC6, protein core the only not include that targets logical pharmaco new of possible a number suggest findings these Overall, humans. in BMD with associated is and formation bone osteoblastic of Wntin modulation the signaling GPC6 of role direct identified recently the with consistent is studies in identified thickness bone cortical increased pathways BMP and Hedgehog VEGF, FGF, the by mediated those including mineralization, and formation bone in involved pathways skeletal signaling regulate protein core GPC6 the to attached proteoglycans (OMIM adults affected skeletal abnormalities, but limited or no information is available from Mutations tiation. of core proteins that are involved in cellular growth control and differen dylinositol-anchored, membrane-bound heparan sulfate proteoglycan glycosylphosphati of (GPC1–6) family glypican the of member a is due to increased cortical bone and resultant increased elasticity. GPC6 loss whose of leads to bone content, function mineral increased likely signaling in involved protein cell-surface a is it as care, osteoporosis population. the in fracture of burden the decrease to manipulation pharmacologic to amenable proteins and tions in general, and this has been demonstrated for musculoskeletal condi therapies useful clinically in to result likely are most genetics human from by evidence supported targets Drug involved. mechanisms ular likely to improve of the overall understanding the and cellular molec is which studies, future in identified be will effect large to moderate of variants rare and low-frequency further that suggests This study. Our findings provide evidence that provide the under architecture Our evidence genetic findings GPC6 13 , 1 4 encodes a glypican that may serve as a novel drug target for target drug a novel as may serve that a glypican encodes . Thus, our findings will be helpful for identifying pathways pathways for identifying be helpful will . our Thus, findings 4 0 . In addition, the adult high-bone-mass phenotype and and phenotype high-bone-mass adult the addition, In . P value of <0.05 (ref. (ref. <0.05 of value GPC6 Gpc6 a DVANCE ONLINE PUBLICATION ONLINE DVANCE − has a role in determining BMD and the patho the and BMD determining in role a has GPC3 / − mice 31287 3 9 of published GWASs for published of , , GPC4 3 5 0 r now provides the opportunity to test test to opportunity the provides now , , OMIM 2 < 0.1). < 3 and 8 41 ). We identified one association, association, one We). identified , 4 2 GPC6 , which is the key regulator of , is key the regulator which 25831 GPC6 GPC6 P = 0.015). We also searched result in developmental result in developmental 5 had previously shown shown previously had locus, for locus, any associa Gpc6 ). The heparan ). sulfate The heparan

Nature Ge Nature − GPC6 / − mice in these in these mice (accessed (accessed n etics ------

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. https://www.cog ctsu.ox.ac.uk/crysta document #155580 on genotyping and quality control, ox.ac.uk eBMD, of measurement for protocol Biobank (GEFOS), Consortium Osteoporosis for (UKBB), Biobank Disease Study (OBCD), (OBCD), Study Disease ht http://www.m URLs. priority. care health major osteoporosis—a of treatment and identify studies these by pathways signaling that represent new drug targets prioritized for the prevention and identified proteins The mechanisms that underlie changes in BMD and fracture risk in humans. in the regulation of BMD, as has been the case for other conditions populations of different ancestry will of revealstudies that novellikely is Itloci individuals. Europeanthat in areonly osteoporosis important Finally,s.d.). 0.05 of< studyinvestigatedour sizeetiology genetic the (i.e., MAF < 0.1%) or rare variants of small effect (MAF < 1% and effect mediated in the future.not-too-distant osteocytes and osteoclasts will reveal how these eBMD associations are osteoblasts, in association genetic of pattern the investigating studies genomic large-scale that expect we mediated, be can association an of effects functional the which through mechanism only the not are those than processes Also, the expression of genes in culture may reflect different biological estimates. may have experiment to eQTL uncertain led osteoblast the osteoclasts. Further, the relativelyand smallosteocytes sample as such size of osteoblasts, 95 than individuals other in types cell on act may probably because at least some of the identified eBMD-associated SNPs SNP through osteoblast effects expression at a majority of loci. This is eBMD.were noteQTL analyses Our consistent of mediation the with through which variants at genome-wide significant loci causally affect predict risk of osteoporotic fracture over and above hip BMD thatpreviouswith measurementsultrasound observations of heel the structure beyond those obtained by central DXA, and this is consistent bone of aspects capture heel the of measurements ultrasound that is tion. Although the reason for these differences is unclear,risk of thefracture in implicationthe direction consistent with the heel eBMD associa sites, other at notably BMD atalthough DXA-derived and heel the at eBMD between identified variants at six loci where the direction of effect was ground opposite to heel the of reaction responses forces) that genetic are not example, present at (for other body heel sites. Interestingly, the to we studies. For other loci, it may reflect genetic influencesprevious that in are well specific tagged nor genotyped neither been having variants loci, such as at other sites body in samples. considerably smaller For some of these not found in previous studies that DXA-derived used BMD measures included some that were strongly relatedvariants to eBMD at significant the heel but weregenome-wide of list our in Also, identified studies. previous loci BMD known 18 at associations replicate not did study Our differences. notable some used were there BMD, DXA-derived that studies previous from those and BMD of ultrasound-derived measurements from identified loci the between concordance Nature Ge Nature tp://www.informatics In summary, our findings shed light on the pathophysiological pathophysiological the on light shed findings our summary, In variants rare very detect to ability limited a had study our Third, Second, our study does not provide a definitive biological mechanism high the despite First, study. our to limitations several are There International Mouse Phenotyping Consortium (IMPC), (IMPC), Consortium Phenotyping Mouse International /crystal/docs/Ultras n TBX1 etics ousephenotype.or -genomics.org/plink2 , , this may simply be a consequence of the associated

http://www.ukbioban CPED1 l/docs/genotyping_qc ADVANCE ONLINE PUBLICATION ONLINE ADVANCE in vivo .jax.or the variants also showed association with showed association variants also the http://www. . Although differences in gene expression differences . Although oundbonedensitometry g g ; the Origins of Bone and Cartilage Cartilage and Bone of Origins the ; ; Mouse Genome Informatics (MGI), / . boneandcartilage.co http://www. k.ac.uk .pd f ; Hg19 gene range list, list, range gene Hg19 ; https://b / ; Genetic Factors Factors Genetic ; .pd

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8. 7. J.A.M. and J.B.R.), the Natural andSciences Engineering Research Council of Appliquée (RMGA; J.A.M.), the Fonds de Recherche du Québec–Santé (FRQS; Swedish Research Council (funding to E.G.), the Réseau de Médecine Génétique Medical Research Council (Early Career Fellowship APP1104818 to N.M.W.), the NIAMS, NIH (AR060981 and AR060234 to C.L.A.-B.), the National Health and Union Erasmus Mundus Action 2: ERAWEB (programme funding to K.T.), (funding to F.R., C.M.-G. and K.T.), the mobility stimuli plan of the European Organization for Health Research and Development ZonMw VIDI 016.136.367 101123; project grant 094134; to G.R.W., J.H.D.B. and P.I.C.), the Netherlands MC_UU_12013/4 to D.M.E.), the Wellcome Trust (Strategic Award grant number technical support for the EasyStrata Software used in this study. Canadian Institutes of Health Research (CIHR). We thank T. Winkler for invaluable This part of the work was supported by Genome Quebec, Genome Canada and the Sweden, for large-scale collection of bone samples and culture of primary osteoblasts. Departments of Surgical and Medical Sciences, Uppsala University, Uppsala, high-performance computing. We thank research nurses and assistants at the We thank P. Sham for helpful discussions and M. Schull for assistance with online ver Note: Any Supplementary Information and Source Data files are available in the pape the the in available are references, and codes accession statements of including Methods, and data availability any associated M 6. 5. 4. 3. 2. 1. claims jurisdictional in published maps and affiliations. institutional reprints/index.htm at online available is information permissions and Reprints The authors declare no competing interests.financial and reviewed the paper. eBMD data. J.P.K., J.A.M. and C.M.-G. were the lead analysts. All authors revised mouse models and/or experiments. N.C.H. functional and C.C. generated heel A.-T.A., K.F.C., J.K.W., F.K., D.J.A., P.I.C., C.L.A.-B., J.H.D.B. and G.R.W. generated wrote the paper. S.E.Y., E.J.G., J.G.L., A.S.P., P.C.S., V.D.L.,R.A., N.C.B., D.K.-E., M.T.M., S.K., F.R., J.H.T., P.I.C., C.L.A.-B., J.H.D.B., G.R.W., J.B.R. and D.M.E. analysis. J.P.K., J.A.M., C.M.-G., V.F., N.M.W., S.E.Y., C.L.G., K.T., C.M.T.G., E.G., K.M.G., C.X., C.M.T.G., C.L.A.-B., J.H.D.B. and G.R.W. performed statistical and experiments. designed J.P.K., J.A.M., C.M.-G., V.F., N.M.W., S.E.Y., J.Z., K.T., S.K., F.R., J.H.T., P.I.C., C.L.A.-B., J.H.D.B., G.R.W., J.B.R. and D.M.E. conceived of Queensland (Early Career Researcher Grant to2014002959 N.M.W.). number 12703). Access to the UK Biobank study data was funded by the University Council (Future Fellowship to FT130101709 D.M.E.). Research (J.B.R.), the Jewish HospitalGeneral (J.B.R.), and the Australian Research Research Arthritis UK (ref. 20000; to C.L.G.), the Canadian Institutes of Health Canada (C.M.T.G.), the J. Gibson and the Ernest Heine Family Foundation (P.I.C.), A C AUTH ckn O

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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. be mediated through a causal effect of weight on eBMD on weight of effect causal a through mediated be may eBMD on effect their and weight, with associated primarily be may ants weight mediated the relationship between genotype and eBMD (i.e., some vari or whether increased was association to detect power the whether investigate in Weall models. weight also included as a covariate in a to analysis sensitivity ture and relatedness. Genotyping array, age and sex were included as covariates model implemented in BOLT-LMM in a non-infinitesimal mixed effect, eBMD, linear an allelic assuming additive with association for variants genetic We tested analyses. present the for able avail were measures ultrasound quantitative valid and genotype with males) 66,420 and females (76,067 individuals of 142,487 A maximum components. principal determined genetically four first the on based approach clustering a using by samples ancestry European’ ‘white of subset a defined we “URLs”), see #155580; document Biobank (UK Biobank UK by centrally performed metrics control quality the to addition In panel. erence (ref. IMPUTE2 with for a subset of 152,729 participants. Data were imputed centrally by UK Biobank Genotype data from the interim May 2015 release of UK Biobank samples. were Biobank UK in available analysis genetic and control quality Preparation, analyzer. composition was body Weight Tanitaa with BC418MA measured fracture. a report not did individuals 131,333 and fall from simple a fracture a had male) 2,687 and female (5,853 individuals 8,540 where fall simple a question, this from using We variable height). a second standing created from (i.e., resulted fracture the whether asked also were fracture a rates negative false and positive ( controls as coded were they otherwise follow-up; first and baseline at both answer” to not “Prefer or first or baseline either at follow-up. years?” Individuals were coded 5 as missing if they responded last “Do you not know” “Have the in question, bones the any to answers fractured/broken affirmative of basis the on fracture, a control. quality after cohort the of statistics and pipeline control see Please right calcaneus) for SOS, BUA and BMD (265,057 females and 218,173 males). were removed; this left a total of 483,230 valid measures (476,618 left and 6,612 others the with that not did cluster and any measurements inspected, visually ≤ males, excluded: were eBMD for thresholds males, males, SOS, thresholds: exclusion following the with rately sepa subjects female and to male applied was control quality measurements, × (BUA= (eBMD 0.002592 To+ − SOS) 3.687). of the impact outlying reduce combination of of speed sound (SOS) and bone attenuationultrasound (BUA) (g/cm eBMD assessment. follow-up and/or baseline quality control, ultrasound data were available for 488,683 individuals at either procedure is the provided ascertainment in N ( points time further two at up followed were subjects these ( calcaneus ( baseline at measured initially were Participants (“URLs”). website Biobank UK the on UK available in publicly are protocol calcanei complete the of of Details participants. assessment Biobank ultrasound quantitative for Massachusetts, used was Bedford, USA) Corporation, (Hologic Sonometer Bone Clinical Committee, and informed consent was obtained from all participants. A Sahara UK Biobank has analysis. ethical approval future from the for Northwest Multi-centresamples Research Ethics saliva and urine blood, provided also They consented to physical measurements, and agreed questionnaires, to have their health screen followed. touch via lifestyle and health their regarding mation infor provided participants All country. the across from years) 40–69 aged were (99.5% years 37–76 aged individuals 502,647 recruited Biobank UK the of and in Measurement eBMD, weight UK fracture Biobank. ONLINE doi: analyzed. were >0.4 of threshold info-score an with and 0.1% of MAF an to 0.12 or or 0.12 = 7,988), during which both heels were measured. A detailed description of description A were heels detailed both measured. which during = 7,988), We defined 14,492 individuals (8,439 female and 6,053 male) as having having as male) 6,053 and female (8,439 individuals 14,492 defined We 10.1038/ng.3949 ≤ ≤ 22 or 22 1,455 or or 1,455 ≥

1.025 g/cm 1.025 Supplementary Figure 2 Figure Supplementary N MET N = 4,102) or both calcanei ( calcanei both or 4,102) = ≥ = 487,428) and had their left calcaneus ( calcaneus left their had and 487,428) = 138 dB/MHz for females. Individuals exceeding the following following the exceeding Individuals for females. dB/MHz 138 H ≥ 1,700 m/s for females; and BUA, and females; for m/s 1,700 ODS 4 Supplementary Table 1 Table Supplementary 2 6 . Bivariate scatter plots of eBMD, BUA and SOS were were SOS BUAand eBMD, of plots scatter Bivariate . ) to a 1000 Genomes (October 2014) and UK10K ref UK10K and 2014) (October Genomes 1000 a to ) N = 130,563). Self-reported fractures have low false false low have fractures Self-reported 130,563). = 4 5 . Individuals who stated that they had had had had they that stated who Individuals . 4 for a detailed description of the quality quality the of description detailed a for 7 to account for population struc cryptic N = 165,511) measured. A subset of of subset A measured. 165,511) = Supplementary Figure 2 Supplementary for an overview of descriptive descriptive of overview an for ≤ 0.18 or or 0.18 ≤ 2 ≤ ) was derived as a linear linear a as derived was ) 27 or or 27 1,450 or 1,450 ≥ 2 1.06 g/cm 1.06 9 N ). Only SNPs down down SNPs Only ). = 317,815), right right 317,815), = ≥ K 138 dB/MHz for for dB/MHz 138 -means ( -means N In 2006–2010, In 2006–2010, ≥ = 20,104 and and 20,104 = 1,700 m/s for m/s 1,700 2 ; females females ; . . Prior to K = 4) 4) = ------

we defined a new and more conservative threshold to declare genome-wide genome-wide declare to threshold conservative more and new a defined we Thus, SNPs. million 17.17 in resulted which >0.4, of threshold info-score an applied and individuals 142,487 in 0.1% of we MAF an to Biobank, down SNPs UK of assessed case the in However, threshold. MAF this above SNPs of European populations (i.e., for > (MAF common variants threshold 5%) in significance the genome-wide threshold. significance of Estimation genome-wide effects fixed as fracture the reporting of time the and tested for association with fracture using BOLT-LMM, including age, sex, BMI additionally were levels significance genome-wide at eBMD with associated GWASs. of published catalog SNPs of that were NHGRI–EBI the release 2016 estimated from our reference UK Biobank sample, (v1.3) together with the December LocusZoom with generated were plots tion scans association were generated by version EasyStrata 15.3. associa Regional was tested with EasyStrata some SNPs for analysis. Heterogeneity sexes in between size effect coefficients chromo X 15,552 yielded which 5%, > rate missing overall and 0.1% < MAF total expected variance in BOLT-LMM. The difference between this estimate estimate this between BOLT-LMM. in difference The variance expected total the combined effect of the SNPs on the individual’s eBMD and recalculated the removed we sizes, effect corrected the calculating After estimated). precisely SNPs that on are moreeffect robustly significant negligible (and a consequently morehaving accurately while and significance reach just that SNPs of sizes effect ‘winner’sthe from curse’.suffer by works shrinking method the Briefly, Bigdeli of method the used SNPs, we significant first by genome-wide all explained the variance calculate BOLT-REML with heritability) SNP the (i.e., array genotyping the on herit SNP ability. and variants significant by explained variance of Estimation “URLs”). (see online available list range Gene Hg19 the and bedtools with gene closest physically the to annotated were cance 10 × (1 quality additional an with control step but to exclude SNPsGWAS, that from deviated Hardy–Weinberg our equilibrium in assessed variants same the million of 17 consisted set data genotyping reference The variants. between from UK was to used of Biobank patterns model selected randomly LD origin of British white < individuals 0.025) relatedness (pairwise of unrelated 15,000 away were to assumed be in A complete equilibrium. reference linkage sample regression tiple analysis using the software package GCTA association genome-wide joint and loci, conditional eBMD approximate out significant carried we genome-wide the of each at signals association ent Approximate analysis. association conditional MAF with SNPs all for accounting then, threshold significance genome-wide estimated Our thresholds. by significance of the number and divided tests the empirical 9 Fig. 740,018 all assessing 9 ( chromosome across when criteria that met our filtering variants Specifically, genome. whole the to thereby and extrapolate correlations, for corrects that threshold significance empirical the and threshold significance Bonferroni the between relationship the size, varying of genome the of subsets in estimate, to able were correlation we Thus the patterns. of assessment allows variants tested all of proportion a small from derived data permuted of Analysis empirically. statistics test nearby consortium sequencing UK10K the in previously used we method the applied we To this, data. do our in formed per tests statistical independent of number the for accounting significance, SNPs with evidence of deviation from Hardy–Weinberg equilibrium (1 × 10 our on genotypes, quality controlobserved was slightly different. We excluded software ( 2016) June (7 3.38 beta v1.09 Plink using components, principal ancestry four first the and sex age, array, genotyping for adjusting chromosome, X the on SNPs typed geno directly and eBMD between association the analyzed Weadditionally N α = 135,729). Because the analyses for the X chromosome data were based based were data chromosome X the for analyses the Because 135,729). = = 0.05/10 = ), we saw a good linear fit between family-wise error rate ( rate error family-wise between fit linear good a saw we ), We estimated the proportion of phenotypic variance tagged by all SNPs −6 ). Conditionally independent variants that reached GWASsignifi reached that variants independent Conditionally ). ≥ 0.1% and info-score > 0.4, was was 0.4, > info-score and 0.1% 6 , as there are an estimated 1 million statistically independent independent statistically million 1 estimated an are there as , R 2 > 0.9) were ignored, and those situated more than 20 Mb Mb 20 than more situated those and ignored, were 0.9) > 4 4 8 9 α and a nested sample of unrelated subjects subjects unrelated of sample nested a and . . Manhattan and Miami plots of our genome-wide et al. et = 5 × 10 5 4 to shrink the effect sizes of SNPs likely to to likely SNPs of sizes effect the shrink to 4 , which assesses the correlation between between correlation the assesses which , −8 ) ) are on based a correction Bonferroni 5 1 . . SNPs with high collinearity (mul α = 6.6 × 10 × 6.6 = To multiple detect independ 5 0 Traditional of estimates 4 , using LD information information LD using , 7 . −9 Nature Ge Nature . Supplementary Supplementary α 5 2 = 0.05), 0.05), = n v2.26.0 v2.26.0 etics 5 3 . To . −6 ), ------

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. given pathway, with a ranked score above a specified threshold (i.e., 95th and 95th (i.e., threshold a specified above score pathway, given a ranked with a in scores gene of number observed The score. gene adjusted its by is ranked gene each and model, regression linear a in etc.) size, gene density, (SNP to owing region HLA complex patternsthe of LD). in This genes (excluding window downstream 40-kb lowest the with SNP index single a to the MAGENTA software Cytoscape in performed was gene-sets meta these described previously sets’ as clustering, gene similarity ‘meta through into grouped further were sets gene enriched significantly hence overlapped; they repositories, different from came tested sets gene the ( threshold significance genome-wide the with panel) reference Genomes 1000 populations, European at FDR = 5%. was defined FDR to adjust for significance multiple testing; Initiative (phenotype–genotype relationships). In all three analyses we used the Genetics Mouse the and interaction), protein–protein (high-confidence base InWebdata the REACTOME, KEGG, Ontology, Gene diverse including from databases, generated were tested sets gene 10,968 The sets. gene stituted in recon were loci eBMD enriched the genes in to the associated test whether analysis enrichment a gene set we Third, performed arrays. expression 37,427 expression in had high anyloci of the 209 MeSH annotations, using data from particular tissues or cell types by testing whether genes in the associated eBMD lower prioritization obtained regions across similarity functional high with genes where regions associated different from genes among similarities functional tested we loci, First, to genes roles with prioritize relevant in biological the eBMD-associated tool v1 DEPICT the in implemented analyses different three conducted we Gene prioritization and pathway analysis. slope the markers). nearby on stratifica effect minimal population a have Likewise, will (i.e., intuitively, but as population overlap. stratification intercept does not correlate the with LD between sample affect by will tion biased be not will term the (i.e., regression the from intercept the only affect will it samples), between relatedness (or cryptic overlap is sample if Thus, there ping samples. and studies, both lap SNP for score LD the is 50%, and 5% between MAFs with panel reference the in SNPs of number where traits: between covariance genetic the of function a is regression the of slope The score. LD on the SNP, cross-product the each regresses then and at of statistics test cross-product the calculates of interest, traits and other the from the GWAS statistics of eBMD summary uses sion method meta-analysis chance of GWASs. overlap between with genuine signals The LD score regres a greater provide thus and signals more true to contain are more likely scores LD high with Variants score). LD (its tags SNP each variation much how of summary test statistics from two GWASs and regresses them against a in measure LDHub implemented utility as web online regression the score LD on based method new relatively a used we osteoporosis, to related those including diseases, and traits complex other and eBMD between correlation genetic the Toestimate Biobank. UK the from individuals unrelated 15,000 of consisting MAF set and data a 0.9 from > 0.1%) > score INFO (i.e., SNPs high-quality all for calculated were ness and other latent sources of bias, we used LD score regression related cryptic stratification, population to due residual data the in inflation score disequilibrium Linkage regression. SNPs. by all explained variance the of estimate an was correction and the total expected variance calculated on the original data without the SNP Nature Ge Nature statistic observed This calculated. then is scores), gene all of percentiles 75th r N N We also compared the DEPICT gene set enrichment results to analyses with ( SNPs lead independent on based were analyses DEPICT The s / N i is the sample size for study study for size sample the is 2 1 N n ) and not the slope, and hence estimates of the genetic covariance etics P values. Second, we analyzed expression enrichment across z E ρ ) ( is the phenotypic correlation among the the among correlation phenotypic the is j 2 1 5 , , 6 j j . . Briefly, MAGENTA maps each gene in the genome N z s quantifies the number of individuals that over that individuals of number the quantifies P 26 = value is then corrected for confounding factors , 2 7 N N . This method uses the cross-products of of cross-products the uses method This . 2 1 M i P , , ρ value within a 110-kb upstream and and upstream 110-kb a within value r g g To establish functional connections, is the genetic covariance, covariance, genetic the is To estimate the amount of genomic P < 6.64 × 10 × 6.64 < l j + r N N 5 N 5 2 1 , filtering at FDR < 1%. < at FDR filtering , S 3 4 . The visualization of visualization The . −9 ). Because many of of many Because ). P values below below values 1 5 N . . LD scores s overlap r M 2 < 0.1; 0.1; < is the the is 3 4 l ------. j

also also emphasize that approaches such as this that Weare based imputed. solely on well association been have and analysis the in included been have variants causal true the that assumes approach this that of We note SNPs. number causal the likely identify to configuration each of probabilities posterior the framework Bayesian a within calculating SNPs, of configurations causal ple multi test to algorithm search stochastic shotgun a implements FINEMAP sets defined of further plausible causal SNPs within each Forlocus. each locus, stop_lost. or stop_gained, splice_donor_variant, variant, inframe_insertion, initator_codon_variant, missense_variant, splice_acceptor_ inframe_deletion, the ontology terms: following frameshift_variant, sequence ( eBMD with associated significantly were they if annotation variation coding (defined as we First, significance). (VEP) Predictor Variantthe used Effect genome-wide attained that SNP lead independent at each here eBMD (defined signal as all SNPs within 500 kb of a conditionally eBMD each locus. at variants causal possible and genes candidate Prioritizing databases. Reactome and BioCarta (PANTHER), Relationships from sets gene Ontology, the Gene Ingenuity, Evolutionary through Protein Analysis KEGG, prespecified 3,217 tested We analysis. either in 0.05 < FDR reached pathway individual an when significant declared was set gene A set. This generates an empirical gene set enrichment analysis size. pathways of permuted identical randomly is to compared then 1,000,000 bone mineral content (BMC) and length of the femur and caudal vertebrae vertebrae caudal and femur the of length and (BMC) content mineral bone relative The fashion. unselected an in analysis rapid-throughput for batches to assigned randomly and anonymized ethanol, 70% in stored were mice out methods. OBCD effort. IMPC and IKMC the of part as Institute pheno screen skeletal type multiparameter validated a undertaking is (“URLs”) study (OBCD) Disease of The ously genes. and Origins Bone unpublished Cartilage and previ or traits, annotated poorly for or functions novel disease ascribed already have human studies of GWAS a by identified genes candidate of screen phenotyping C57BL/6 a on mice background in genes genetic protein-coding all for alleles null generating (“URLs”) validation. functional for used animals modified Genetically set training initial the in rate predictive positive 51% a to (corresponding evidence functional strong very having as 0.1 than CATO greater SNPs with scores we considered and 1, and 0 between range CATO scores families. motif factor transcription 44 for sequences recognition factor transcription the on effects direct and context of a imbalance sequence DHS cause allelic variant will by local both modeling Maurano by described CATO,previously (CATO) of Transcription Analysis scores. Factor Occupancy DHS Contextual with a inhabiting SNP each annotated binding Wefurther type. factor cell given a in transcription sites collective the comprising chromatin open of types cell 115 from derived list master a using DHSs, locus. 100, than log greater or factors Bayes with SNPs only retained We causal. is SNP particular the that evidence the quantifies which factor, Bayes the SNP each association. statistical the underlying gene/variant(s) the of of identity the confidence is there greater and studies), eQTL gene expression knockout, human knockout, mouse example, (for approaches independent in osteoporosis etiology. When the same variant/gene is implicated by multiple one of approaches that several can be variants/genes to used implicate specific as analyses fine-mapping we these Thus, regard variants/genes. of tion causal test statistics and LD are unlikely to be definitive with respect to the identifica P < 6.6 × 10 × 6.6 < et uig FINEMAP using Next, We then annotated each set of plausible causal SNPs for overlap with with overlap for SNPs causal plausible of set each annotated then We for calculate will FINEMAP SNPs, causal plausible of number given a For 10 WeSNPs causal possible a of combined to number approaches identify Bayes factors greater than 2, as our plausible causal SNPs for each each for SNPs causal plausible our as 2, than greater factors Bayes 5 8 ± and the International Knockout Mouse Consortium (IKMC) are are (IKMC) Consortium Mouse Knockout International the and 3 6 500 kb from a conditionally independent lead SNP) for deleterious −9 of mutant mouse lines generated by the Wellcomeby the Trust generated Sanger lines of mutant mouse ). Deleterious SNPs were classified as such if they had one of of one had they if such as classified were SNPs Deleterious ). Samples from 16-week-old female wild-type and knock and wild-type female 16-week-old from Samples 6 5 0 9 . This approach can be used for functional investigation investigation . for approach can This be used functional . These mice are phenotyped through a broad-based broad-based a through phenotyped are mice These . 4 ). 5 7 , we identified 305 autosomal lead SNPs and and SNPs lead autosomal 305 identified we , 3 0 to annotate all SNPs within a locus a locus SNPs within all to annotate et al. et 4 , scores the likelihood that a that likelihood the scores , 4 . DHSs are focal sites sites focal are DHSs . P doi: value for each gene 10.1038/ng.3949 The IMPC IMPC The - - - - -

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. mouse mouse osteoblasts undergoing differentiation. These data have been described (i.e., association of evidence strong exhibited that SNPs our only included we affecting results, potentially from instruments SNP weak prevent To analyses. listed in SNP–eBMD association. We therefore performed HEIDI tests for all the sug probes test HEIDI that gested of significant expression not does the relevant the gene mediate in osteoblasts a study, our of context the In differ. nificantly sig may analysis randomization Mendelian the from estimates the affecting eBMD), other the and the osteoblasts in in expression signals gene separate affecting one two region, (i.e., linkage of model a under whereas error), sampling to (subject estimate causal same the produce SNPs should different model, causal a Under SNPs. the between dependencies account into taking on eBMD obtained by Mendelian randomization analysis of each variant while of expression gene effect causal of putative the estimates by works comparing test the Intuitively eBMD. and SNP the between relationship the mediating other eBMD affecting variation), as opposed to expression of the relevant gene the and expression, gene affecting (one variants causal distinct two with LD lead the which in situations identify to used was GWASresults sum and eQTL eBMD heel sample on osteoblast analyses randomization two Mendelian mary performing by eBMD) on expression osteoblast of effect causal a to opposed (as signals different represent may osteoblasts in effects SNPs. causal plausible of targets gene possible identify 1 panel phase v3 reference and Genomes 1000 al. et by Grundberg described as previously SNPs human osteoblasts in 95 primary undertook we osteoblasts, Gene expression in human primary and mouse osteoblasts. report. Weatherall the of recommendations the and 1986 Act Procedures) (Scientific Animals the with accordance in Office Home UK the by licensed and IKMC the of part as Project Genetics Mouse Institute Sanger Trust Wellcome the by undertaken were studies mouse All 100,000. by divided permutations extreme of number the as calculated then extreme least the as extreme as phenotypes both with animals knockout two observed we times of number the observe to times 100,000 labels knockout the permuted Wethen tested. the for phenotype extreme least the identified To first we so do P We mice. 2 than greater away s.d. from types of the mean wild-type generated (13.3%). stiffness and (10.3%) load maximum and energy dissipated before fracture (26.7%); and vertebra yield load (13.0%), (13.7%) stiffness load (29.0%), fracture maximum load (10.0%), load (13.2%), cortical bone internal (4.3%), diameter thickness (6.0%) and (8.3%); BMD femur (4.0%); yield spacing trabecular and (7.9%) thickness trabecular number (7.3%), trabecular (18.5%), volume volume/tissue bone trabecular (2.3%); and length BMC (2.1%) vertebra (2.1%); and length BMC (2.0%) femur lows: were as fol parameter skeletal for each of variation Coefficients mice. female C57BL/6 wild-type 16-week-old >250 from obtained data reference to pared skeletal parameters were cell) reported for each individual load mouse studied and com 100-N frame, load 5543 (Instron 7 and 6 vertebrae caudal of testing compression and femur the of testing bend three-point tive destruc from derived were fracture) before dissipated energy of percentage the load, fracture load, maximum load, (yield toughness and strength bone 100 ning femur the of length number, atspacing) thickness, 5- the along way the of distal to the femoral 56% head, and trabecular parameters (bone volume, trabecular region mid-shaft the on BMD, (thickness, parameters 10- at bone diameter) medullary cortical determine to used was filter) (Faxitron MX20). Micro-CT (Scanco uCT50, 70 kV, 200 at were 10- determined doi: previously detail in values for the reported reported the for values Gene expression profiles of candidate genes were examined in primary primary in examined were genes candidate of profiles expression Gene and associations eBMD heel that possibility the We investigated In 10.1038/ng.3949 3 F 3 Supplementary Table 15 Table Supplementary statistic > 10) in the eQTL analysis eQTL the in 10) > statistic , performed with an updated imputation panel, the combined UK10K UK10K combined the panel, imputation updated an with performed , Supplementary Table Supplementary 10 µ m proximal to the distal growth plate. Biomechanical variables of variables Biomechanical plate. growth distal the to proximal m 62 , 6 3 . 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bones with the marrow left intact ( intact left marrow the with bones tome-sequencing data from bone samples with osteocytes isolated to data from transcrip by comparing skeleton the in expression genes’ these of specificity the Wedetermined type. bone any in replicates eight of eight for threshold Hart from approach statistical modi fied a using sample, each for expression gene normalized of distribution the of basis the on determined was expression of threshold A removed; bone). per 8 (marrow = calvaria and humerus different femur, four tibia, the from bones: mouse derived sequences whole-transcriptome analyzing by osteocytes. mouse in expression Gene quartile. upper per-sample the to relative ized 50, --fragment-length-sd and the expression level for each sample was normal with 280 RSEM and version 1.2.0 with of parameters --fragment-length-mean gene per level expression the We genome. reference calculated NCBIM37 the of dance were estimation using version created transcripts 0.12.9, with abun Bowtie for alignments The sequenced. Three were samples 2000. per HiSeq replicates Illumina technical an with point time each at transcriptome the 2 every d from day 2 to 18 d post-differentiation. We used RNA-seq to evaluate and RNA collected was cocktail, re-plated to an osteoblast-differentiation and exposed were cells pre-osteoblast remaining The FACS. by period culture removed that were of end the at CFP express not growth did that in d cells 4 and for media, culture into placed were cells The promoter. 3.6-Kb Col the of control the a under (CFP) protein carrying florescent mice cyan expressing C57BL/6J transgene neonatal from collected calvaria from cells like Omnibus ( 56. 55. 54. 53. 52. 51. 50. 49. 48. 47. 46. 45. (“URLs”). OBCD and (“URLs”) IMPC the generated as part of this study. were Mouse phenotype codes data are availableaccession the online related from or via sets data new No available (“URLs”). are website GEFOS study this from statistics summary GWAS (“URLs”). results of this study are are based available upon application from UK Biobank availability. Data accession (GEO obtained from osteoclasts C57BL/6 mice 6–8-week-old bone-marrow-derived RNA-seq via of data obtained available from publically was determined clasts osteoclasts. mouse in expression Gene preparation). in P.I.C.,and manuscript A

Segrè, A.V., Groop, L., Mootha, V.K., Daly, M.J. & Altshuler, D. Common inherited Common D. Altshuler, & V.K.,M.J. Daly,Mootha, L., A.V.,Groop, Segrè, R. Saito, T.B.Bigdeli, forcomparing Loh, P.R. of utilities suite flexible a BEDTools: I.M. Hall, & A.R. Quinlan, J. Yang, R.J. Pruim, Winkler, T.W. C.C. Chang, Loh, P.R. of thousands with imputation Genotype M. Stephens, & J. Marchini, B., Howie, A.A. Ismail, or related glycemic traits. glycemic related or variation in mitochondrial genes is not enriched for associations with type 2 diabetes (2012). (2016). scans. genome larger much in discovered signals (2015). analysis. variance-components fast using diseases features. genomic (2012). 369–375 traits. complex influencing variants additional identifies statistics results. scan data. meta-analysis association datasets. richer cohorts. large in genomes. Europe. across women and (2000). men in study Life Sciences Reporting Summary Summary Reporting Sciences Life GSE5446 et al. t al. et et al. et al. et G3 (Bethesda) G3 t al. et et al. et t al. et et al. et al. et Bioinformatics Contrasting genetic architectures of schizophrenia and other complex Efficient Bayesian mixed-model analysis increases association power GSM187336 A travel guide to Cytoscape plugins. Cytoscape to guide travel A odtoa ad on mlil-N aayi o GA summary GWAS of analysis multiple-SNP joint and Conditional Gigascience The human genotype and phenotype data on which the the which on data phenotype and genotype human The Nat. Genet. Nat. Second-generation PLINK: rising to the challenge of larger and larger of challenge the to rising PLINK: Second-generation EasyStrata: evaluation and visualization of stratified genome-wide 1 ouZo: einl iulzto o gnm-ie association genome-wide of visualization regional LocusZoom: A simple yet accurate correction for winner’s curse can predict can curse winner’s for correction accurate yet simple A Validity of self-report of fractures: results from a prospective prospective a from results fractures: of self-report of Validity Bioinformatics ). To study mouse osteoblasts, we obtained pre-osteoblast-

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nature research | life sciences reporting summary

DAVID M EVANS Corresponding author(s): J BRENT RICHARDS Initial submission Revised version Final submission Life Sciences Reporting Summary Nature Research wishes to improve the reproducibility of the work that we publish. This form is intended for publication with all accepted life science papers and provides structure for consistency and transparency in reporting. Every life science submission will use this form; some list items might not apply to an individual manuscript, but all fields must be completed for clarity. For further information on the points included in this form, see Reporting Life Sciences Research. For further information on Nature Research policies, including our data availability policy, see Authors & Referees and the Editorial Policy Checklist.

` Experimental design 1. Sample size Describe how sample size was determined. Skeletal phenotyping of knockout mice. The reference ranges for each skeletal parameter were derived from >250 female 16 week old C57BL/6 wild-type mice. Using these data together with coefficients of variation for each test, power calculations indicate an 80% power to detect outlier phenotype of greater or equal to 2SD with a sample size of n=2 2. Data exclusions Describe any data exclusions. If skeletal samples were damaged or incomplete on receipt they were excluded from the analysis. 3. Replication Describe whether the experimental findings were No replication of knockout mouse lines. reliably reproduced. 4. Randomization Describe how samples/organisms/participants were Not applicable allocated into experimental groups. 5. Blinding Describe whether the investigators were blinded to All skeletal samples from knockout mice generated by the Wellcome Trust Sanger group allocation during data collection and/or analysis. Institute were bar coded. Samples were sent to Imperial College in anonymized batches and all skeletal phenotyping and analysis was performed blind to genotype. Note: all studies involving animals and/or human research participants must disclose whether blinding and randomization were used. June 2017

1 Nature Genetics: doi:10.1038/ng.3949 6. Statistical parameters nature research | life sciences reporting summary For all figures and tables that use statistical methods, confirm that the following items are present in relevant figure legends (or in the Methods section if additional space is needed).

n/a Confirmed

The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement (animals, litters, cultures, etc.) A description of how samples were collected, noting whether measurements were taken from distinct samples or whether the same sample was measured repeatedly A statement indicating how many times each experiment was replicated The statistical test(s) used and whether they are one- or two-sided (note: only common tests should be described solely by name; more complex techniques should be described in the Methods section) A description of any assumptions or corrections, such as an adjustment for multiple comparisons The test results (e.g. P values) given as exact values whenever possible and with confidence intervals noted A clear description of statistics including central tendency (e.g. median, mean) and variation (e.g. standard deviation, interquartile range) Clearly defined error bars

See the web collection on statistics for biologists for further resources and guidance.

` Software Policy information about availability of computer code 7. Software Describe the software used to analyze the data in this NA study.

For manuscripts utilizing custom algorithms or software that are central to the paper but not yet described in the published literature, software must be made available to editors and reviewers upon request. We strongly encourage code deposition in a community repository (e.g. GitHub). Nature Methods guidance for providing algorithms and software for publication provides further information on this topic.

` Materials and reagents Policy information about availability of materials 8. Materials availability Indicate whether there are restrictions on availability of All knockout lines and primary phenotype data are available on line at the IMPC unique materials or if these materials are only available http://www.mousephenotype.org/ and OBCD http://www.boneandcartilage.com/ for distribution by a for-profit company. 9. Antibodies Describe the antibodies used and how they were validated NA for use in the system under study (i.e. assay and species). 10. Eukaryotic cell lines a. State the source of each eukaryotic cell line used. NA

b. Describe the method of cell line authentication used. NA

c. Report whether the cell lines were tested for NA mycoplasma contamination.

d. If any of the cell lines used are listed in the database NA of commonly misidentified cell lines maintained by ICLAC, provide a scientific rationale for their use. June 2017

2 Nature Genetics: doi:10.1038/ng.3949 ` Animals and human research participants nature research | life sciences reporting summary Policy information about studies involving animals; when reporting animal research, follow the ARRIVE guidelines 11. Description of research animals Provide details on animals and/or animal-derived Knockout mice were generated at the Wellcome Trust Sanger Institute for the materials used in the study. International Mouse Phenotyping Consortium. Skeletal samples from female 16 week old C57BL/6 wild type and mutant mice in an identical genetic background were analysed.

Policy information about studies involving human research participants 12. Description of human research participants Describe the covariate-relevant population NA characteristics of the human research participants. June 2017

3 Nature Genetics: doi:10.1038/ng.3949