Cited by 44Bone health and osteoporosis researchBone Metabolism and DiseasesConnective tissue disorders research

A Rare Mutation in SMAD9 Associated With High Bone Mass Identifies the SMAD-Dependent BMP Signaling Pathway as a Potential Anabolic Target for Osteoporosis

Open access
Gregson, Celia L, Bergen, Dylan J. M., Leo, Paul, Sessions, Richard B, Wheeler, Lawrie, Hartley, April, Youlten, Scott, Croucher, Peter I +14 more·2020·Journal of Bone and Mineral Research

Abstract

Novel anabolic drug targets are needed to treat osteoporosis. Having established a large national cohort with unexplained high bone mass (HBM), we aimed to identify a novel monogenic cause of HBM and provide insight into a regulatory pathway potentially amenable to therapeutic intervention. We investigated a pedigree with unexplained HBM in whom previous sequencing had excluded known causes of monogenic HBM. Whole exome sequencing identified a rare (minor allele frequency 0.0023), highly evolutionarily conserved missense mutation in SMAD9 (c.65T>C, p.Leu22Pro) segregating with HBM in this autosomal dominant family. The same mutation was identified in another two unrelated individuals both with HBM. In silico protein modeling predicts the mutation severely disrupts the MH1 DNA-binding domain of SMAD9. Affected individuals have bone mineral density (BMD) Z-scores +3 to +5, mandible enlargement, a broad frame, torus palatinus/mandibularis, pes planus, increased shoe size, and a tendency to sink when swimming. Peripheral quantitative computed tomography (pQCT) measurement demonstrates increased trabecular volumetric BMD and increased cortical thickness conferring greater predicted bone strength; bone turnover markers are low/normal. Notably, fractures and nerve compression are not found. Both genome-wide and gene-based association testing involving estimated BMD measured at the heel in 362,924 white British subjects from the UK Biobank Study showed strong associations with SMAD9 (PGWAS = 6 × 10−16; PGENE = 8 × 10−17). Furthermore, we found Smad9 to be highly expressed in both murine cortical bone–derived osteocytes and skeletal elements of zebrafish larvae. Our findings support SMAD9 as a novel HBM gene and a potential novel osteoanabolic target for osteoporosis therapeutics. SMAD9 is thought to inhibit bone morphogenetic protein (BMP)-dependent target gene transcription to reduce osteoblast activity. Thus, we hypothesize SMAD9 c.65T>C is a loss-of-function mutation reducing BMP inhibition. Lowering SMAD9 as a potential novel anabolic mechanism for osteoporosis therapeutics warrants further investigation. © 2019 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/jbmr.3875

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

References 71 · Cited by 44

Research works printed but not linked: 62

  1. [1]Wright NC, Looker AC, Saag KG, et al. The recent prevalence of osteoporosis and low bone mass in the United States based on bone mineral density at the femoral neck or lumbar spine. J Bone Miner Res. 2014; 29(11): 2520– 6. 24771492 PMC4757905
  2. [4]McClung MR, Brown JP, Diez‐Perez A, et al. Effects of 24 months of treatment with romosozumab followed by 12 months of denosumab or placebo in postmenopausal women with low bone mineral density: a randomized, double‐blind, phase 2, parallel group study. J Bone Miner Res. 2018; 33(8): 1397– 406. 29694685
  3. [5]Brunkow ME, Gardner JC, Van Ness J, et al. Bone dysplasia sclerosteosis results from loss of the SOST gene product, a novel cystine knot‐containing protein. Am J Med Genet. 2001; 68(3): 577– 89. PMC1274471 11179006
  4. [6]Staehling‐Hampton K, Proll S, Paeper BW, et al. A 52‐kb deletion in the SOST‐MEOX1 intergenic region on 17q12‐q21 is associated with van Buchem disease in the Dutch population. Am J Med Genet. 2002; 110(2): 144– 52. 12116252
  5. [7]Little RD, Carulli JP, Del Mastro RG, et al. A mutation in the LDL receptor‐related protein 5 gene results in the autosomal dominant high‐bone‐mass trait. Am J Hum Genet. 2002; 70(1): 11– 9. 11741193 PMC419982
  6. [8]Whyte MP, McAlister WH, Zhang F, et al. New explanation for autosomal dominant high bone mass: Mutation of low‐density lipoprotein receptor‐related protein 6. Bone. 2019; 127: 228– 43. 31085352
  7. [9]Gregson CL, Wheeler L, Hardcastle SA, et al. Mutations in known monogenic high bone mass loci only explain a small proportion of high bone mass cases. J Bone Miner Res. 2015; 31(3): 640– 9. 26348019 PMC4832273
  8. [10]Gregson CL, Steel SA, O'Rourke KP, et al. “Sink or swim”: an evaluation of the clinical characteristics of individuals with high bone mass. Osteoporos Int. 2012; 23(2): 643– 54. 21455762 PMC3261396
  9. [11]Gregson CL, Newell F, Leo PJ, et al. Genome‐wide association study of extreme high bone mass: contribution of common genetic variation to extreme BMD phenotypes and potential novel BMD‐associated genes. Bone. 2018; 114: 62– 71. 29883787 PMC6086337
  10. [12]Gregson CL, Sayers A, Lazar V, et al. The high bone mass phenotype is characterised by a combined cortical and trabecular bone phenotype: findings from a pQCT case–control study. Bone. 2013; 52(1): 380– 8. 23103330 PMC3526774
  11. [13]Duncan EL, Danoy P, Kemp JP, et al. Genome‐wide association study using extreme truncate selection identifies novel genes affecting bone mineral density and fracture risk. PLoS Genet. 2011; 7(4): e1001372. 21533022 PMC3080863
  12. [14]McInerney‐Leo AM, Schmidts M, Cortes CR, et al. Short‐rib polydactyly and Jeune syndromes are caused by mutations in WDR60. Am J Hum Genet. 2013; 93(3): 515– 23. 23910462 PMC3769922
  13. [15]Adzhubei IA, Schmidt S, Peshkin L, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010; 7(4): 248– 9. 20354512 PMC2855889
  14. [16]Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non‐synonymous variants on protein function using the SIFT algorithm. Nat Protoc. 2009; 4(7): 1073– 81. 19561590
  15. [17]Morris JA, Kemp JP, Youlten SE, et al. An atlas of genetic influences on osteoporosis in humans and mice. Nat Genet. 2019; 51: 258– 66. 30598549 PMC6358485
  16. [19]Watanabe K, Stringer S, Frei O, et al. A global overview of pleiotropy and genetic architecture in complex traits. Nat Genet. 2019; 51(9): 1339– 48. 31427789
  17. [20]Hart T, Komori HK, LaMere S, Podshivalova K, Salomon DR. Finding the active genes in deep RNA‐seq gene expression studies. BMC Genomics. 2013; 14: 778. 24215113 PMC3870982
  18. [22]Ferrer‐Costa C, Gelpí JL, Zamakola L, Parraga I, de la Cruz X, Orozco M. PMUT: a web‐based tool for the annotation of pathological mutations on proteins. Bioinformatics. 2005; 21(14): 3176– 8. 15879453
  19. [23]Schwarz JM, Rodelsperger C, Schuelke M, Seelow D. MutationTaster evaluates disease‐causing potential of sequence alterations. Nat Methods. 2010; 7(8): 575– 6. 20676075
  20. [24]Zimmermann L, Stephens A, Nam SZ, et al. A completely reimplemented MPI bioinformatics toolkit with a new HHpred server at its core. J Mol Biol. 2018; 430(15): 2237– 43. 29258817
  21. [25]Webb B, Sali A. Comparative protein structure modeling using modeller. Curr Protoc Bioinformatics. 2016; 54: 5.6.1– 5.6.37. 27322406 PMC5031415
  22. [26]Pettersen EF, Goddard TD, Huang CC, et al. UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem. 2004; 25(13): 1605– 12. 15264254
  23. [27]Alexander C, Zuniga E, Blitz IL, et al. Combinatorial roles for BMPs and Endothelin 1 in patterning the dorsal‐ventral axis of the craniofacial skeleton. Development. 2011; 138(23): 5135– 46. 22031543 PMC3210495
  24. [28]Spoorendonk KM, Peterson‐Maduro J, Renn J, et al. Retinoic acid and Cyp26b1 are critical regulators of osteogenesis in the axial skeleton. Development. 2008; 135(22): 3765– 74. 18927155
  25. [29]Westerfield M. The zebrafish book. A guide for the laboratory use of zebrafish (Danio Rerio). Eugene, OR: University of Oregon Press; 2000.
  26. [30]Bergen DJM, Stevenson NL, Skinner REH, Stephens DJ, Hammond CL. The Golgi matrix protein giantin is required for normal cilia function in zebrafish. Biol Open. 2017; 6(8): 1180–9. 28546340 PMC5576078
  27. [31]Hammond CL, Schulte‐Merker S. Two populations of endochondral osteoblasts with differential sensitivity to hedgehog signalling. Development. 2009; 136(23): 3991– 4000. 19906866
  28. [32]Schindelin J, Arganda‐Carreras I, Frise E, et al. Fiji: an open‐source platform for biological‐image analysis. Nat Methods. 2012; 9(7): 676– 82. 22743772 PMC3855844
  29. [33]Zheng HF, Forgetta V, Hsu YH, et al. Whole‐genome sequencing identifies EN1 as a determinant of bone density and fracture. Nature. 2015; 526(7571): 112– 7. 26367794 PMC4755714
  30. [35]Webb TR, Erdmann J, Stirrups KE, et al. Systematic evaluation of pleiotropy identifies 6 further loci associated with coronary artery disease. J Am Coll Cardiol. 2017; 69(7): 823– 36. 28209224 PMC5314135
  31. [36]Nelson CP, Goel A, Butterworth AS, et al. Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nat Genet. 2017; 49(9): 1385– 91. 28714975
  32. [37]Dallas SL, Bonewald LF. Dynamics of the transition from osteoblast to osteocyte. Ann N Y Acad Sci. 2010; 1192: 437– 43. 20392270 PMC2981593
  33. [38]Bergen DJM, Kague E, Hammond CL. Zebrafish as an emerging model for osteoporosis: a primary testing platform for screening new osteo‐active compounds. Front Endocrinol. 2019; 10: 6. PMC6361756 30761080
  34. [40]Butler WT, Mikulski A, Urist MR, Bridges G, Uyeno S. Noncollagenous proteins of a rat dentin matrix possessing bone morphogenetic activity. J Dent Res. 1977; 56(3): 228– 32. 265954
  35. [41]Lowery JW, Rosen V. The BMP pathway and its inhibitors in the skeleton. Physiol Rev. 2018; 98(4): 2431– 52. 30156494
  36. [42]Huang Z, Wang D, Ihida‐Stansbury K, Jones PL, Martin JF. Defective pulmonary vascular remodeling in Smad8 mutant mice. Hum Mol Genet. 2009; 18(15): 2791– 801. 19419974 PMC2706683
  37. [43]Arnold SJ, Maretto S, Islam A, Bikoff EK, Robertson EJ. Dose‐dependent Smad1, Smad5 and Smad8 signaling in the early mouse embryo. Dev Biol. 2006; 296(1): 104– 18. 16765933 PMC7116376
  38. [44]Kemp JP, Morris JA, Medina‐Gomez C, et al. Identification of 153 new loci associated with heel bone mineral density and functional involvement of GPC6 in osteoporosis. Nat Genet. 2017; 49(10): 1468– 75. 28869591 PMC5621629
  39. [45]Medina‐Gomez C, Kemp JP, Trajanoska K, et al. Life‐course genome‐wide association study meta‐analysis of total body BMD and assessment of age‐specific effects. Am J Hum Genet. 2018; 102(1): 88– 102. 29304378 PMC5777980
  40. [46]Koay MA, Woon PY, Zhang Y, et al. Influence of LRP5 polymorphisms on normal variation in BMD. J Bone Miner Res. 2004; 19(10): 1619– 27. 15355556
  41. [47]Uitterlinden AG, Arp PP, Paeper BW, et al. Polymorphisms in the sclerosteosis/van Buchem disease gene (SOST) region are associated with bone‐mineral density in elderly whites. Am J Hum Genet. 2004; 75(6): 1032– 45. 15514891 PMC1182139
  42. [48]Boyden LM, Mao J, Belsky J, et al. High bone density due to a mutation in LDL‐receptor‐related protein 5. N Engl J Med. 2002; 346(20): 1513– 21. 12015390
  43. [49]Hamersma H, Gardner J, Beighton P. The natural history of sclerosteosis. Clin Genet. 2003; 63(3): 192– 7. 12694228
  44. [50]Xiao J, Purcell SA, Prado CM, Gonzalez MC. Fat mass to fat‐free mass ratio reference values from NHANES III using bioelectrical impedance analysis. Clin Nutr. 2018; 37(6, Part A): 2284– 7. 29056283
  45. [51]Frost M, Andersen T, Gossiel F, et al. Levels of serotonin, sclerostin, bone turnover markers as well as bone density and microarchitecture in patients with high‐bone‐mass phenotype due to a mutation in Lrp5. J Bone Miner Res. 2011; 26(8): 1721– 8. 21351148
  46. [52]Gregson CL, Poole KES, McCloskey EV, et al. Elevated circulating Sclerostin concentrations in individuals with high bone mass, with and without LRP5 mutations. J Clin Endocrinol Metab. 2014; 99(8): 2897– 907. 24606091 PMC4207929
  47. [53]Bonewald L. Use it or lose it to age: a review of bone and muscle communication. Bone. 2018; 120: 212– 8. 30408611 PMC6360108
  48. [54]Tosca L, Brisset S, Petit FM, et al. Genotype‐phenotype correlation in 13q13.3‐q21.3 deletion. Eur J Med Genet. 2011; 54(5): e489– e494. 21741501
  49. [55]Shintani M, Yagi H, Nakayama T, Saji T, Matsuoka R. A new nonsense mutation of SMAD8 associated with pulmonary arterial hypertension. J Med Genet. 2009; 46(5): 331– 7. 19211612
  50. [56]Drake KM, Zygmunt D, Mavrakis L, et al. Altered MicroRNA processing in heritable pulmonary arterial hypertension: an important role for Smad‐8. Am J Respir Crit Care Med. 2011; 184(12): 1400– 8. 21920918 PMC3262031
  51. [57]Walcott BP, Winkler EA, Zhou S, et al. Identification of a rare BMP pathway mutation in a non‐syndromic human brain arteriovenous malformation via exome sequencing. Hum Genome Var. 2018; 5: 18001. 29844917 PMC5966745
  52. [58]Ngeow J, Yu W, Yehia L, et al. Exome sequencing reveals germline SMAD9 mutation that reduces phosphatase and Tensin homolog expression and is associated with hamartomatous polyposis and gastrointestinal ganglioneuromas. Gastroenterology. 2015; 149(4): 886– 9.e5. 26122142
  53. [59]Le Goff C, Mahaut C, Wang Lauren W, et al. Mutations in the TGFβ binding‐protein‐like domain 5 of FBN1 are responsible for acromicric and geleophysic dysplasias. Am J Hum Genet. 2011; 89(1): 7– 14. 21683322 PMC3135800
  54. [60]Loeys BL, Gerber EE, Riegert‐Johnson D, et al. Mutations in fibrillin‐1 cause congenital scleroderma: stiff skin syndrome. Sci Transl Med. 2010; 2(23): 23ra0. PMC2953713 20375004
  55. [61]Rommel K, Karck M, Haverich A, et al. Identification of 29 novel and nine recurrent fibrillin‐1 (FBN1) mutations and genotype‐phenotype correlations in 76 patients with Marfan syndrome. Hum Mutat. 2005; 26(6): 529– 39. 16220557
  56. [62]Timberlake AT, Choi J, Zaidi S, et al. Two locus inheritance of non‐syndromic midline craniosynostosis via rare SMAD6 and common BMP2 alleles. Elife. 2016;5.pii:e20125. PMC5045293 27606499
  57. [63]Shore EM, Xu M, Feldman GJ, et al. A recurrent mutation in the BMP type I receptor ACVR1 causes inherited and sporadic fibrodysplasia ossificans progressiva. Nat Genet. 2006; 38(5): 525– 7. 16642017
  58. [64]Barruet E, Morales BM, Cain CJ, et al. NF‐κB/MAPK activation underlies ACVR1‐mediated inflammation in human heterotopic ossification. JCI Insight. 2018; 3(22): e122958. PMC6302947 30429363
  59. [65]Sheu TJ, Zhou W, Fan J, et al. Decreased BMP2 signal in GIT1 knockout mice slows bone healing. Mol Cell Biochem. 2014; 397(1): 67– 74. 25138700 PMC4418226
  60. [66]Hankenson KD, Gagne K, Shaughnessy M. Extracellular signaling molecules to promote fracture healing and bone regeneration. Adv Drug Deliv. Rev. 2015; 94: 3– 12. 26428617
  61. [67]Salazar VS, Gamer LW, Rosen V. BMP signalling in skeletal development, disease and repair. Nat Rev Endocrinol. 2016; 12(4): 203– 21. 26893264
  62. [68]Duncan EL, Cardon LR, Sinsheimer JS, Wass JA, Brown MA. Site and gender specificity of inheritance of bone mineral density. J Bone Miner Res. 2003; 18(8): 1531– 8. 12929944

Authors
Gregson, C. L., Bergen, D. J. M., Leo, P., Sessions, R. B., Wheeler, L., Hartley, A., Youlten, S., Croucher, P. I., McInerney-Leo, A. M., Fraser, W., Tang, J. C., Anderson, L., Marshall, M., Sergot, L., Paternoster, L., Davey Smith, G., The AOGC Consortium, Brown, M. A., Hammond, C., Kemp, J. P., Tobias, J. H., & Duncan, E. L.
Affiliations
  • University of Bristol (GB)
  • Translational Research Institute (AU)
  • Garvan Institute of Medical Research (AU)
  • University of East Anglia (GB)
  • Severn School of Radiology, Severn Deanery Bristol UK
  • Medical Research Council Integrative Epidemiology Unit, Population Health Sciences Bristol Medical School, University of Bristol Bristol UK
  • The University of Queensland (AU)
  • Musculoskeletal Research Unit, Translational Health Sciences Bristol Medical School, University of Bristol Bristol UK
Corresponding author
Gregson, Celia L
Venue
Journal of Bone and Mineral Research
Published
2019-09-16
Volume
35
Issue
1
Pages
92-105
ISSN
  • 0884-0431 (ISSN-L)
  • 1523-4681
OpenAlex
W2973985024
Cited by
44
References
71
Citations by year
2026: 7 · 2025: 3 · 2024: 5 · 2023: 2 · 2022: 6 · 2021: 13 · 2020: 8
FWCI
7.17
Type
journal article
Language
en
Open access
Locations
  • Journal of Bone and Mineral Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Portal (King's College London) (publishedVersion, cc-by)
  • Explore Bristol Research (publishedVersion, other-oa)
  • UEA Digital Repository (University of East Anglia) (acceptedVersion)
  • Bristol Research (University of Bristol) (acceptedVersion, other-oa)
  • QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
Funders
  • Arthritis Research UK (19476, 20000, 21211, 21937)
  • British Geriatrics Society
  • FP7 Health (247642)
  • Harold Hyam Wingate Foundation (DMMTF-180208, DMMTF‐180208)
  • Medical Research Council (MC_UU_12013/4)
  • National Health and Medical Research Council (1032571, 511132, GNT1158758)
  • University of Queensland (UQFEL1718945)
  • Wellcome Trust (080280/Z/06/Z, 101123, 20378/Z/16/Z, 204813/Z/16/Z)
  • NIHR (5163)
  • Medical Research Council Canada (MC_UU_12013/4)
Topics
  • Health Sciences › Medicine › Orthopedics and Sports Medicine › Bone health and osteoporosis research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bone Metabolism and Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Connective tissue disorders research
Keywords
SMAD9, high bone mass, osteoporosis, anabolic therapy, BMP signaling, missense mutations, loss-of-function mutations, bone mineral density, osteocytes, genetic association, autosomal dominant inheritance
MeSH terms
Animals, Bone and Bones, Humans, Mutation, Osteoporosis, Zebrafish, Signal Transduction, Mice, Smad8 Protein

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review