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Evaluation of Volumetric Bone Mineral Density, Bone Microarchitecture, and Bone Strength in Patients with Achondroplasia Caused by FGFR3 c.1138G > A Mutation

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Abstract

Achondroplasia (ACH) is a skeletal disorder caused by fibroblast growth factor receptor 3 (FGFR3) variants. Volumetric bone mineral density (vBMD), bone microarchitecture, and strength have not been evaluated in these patients previously. This study aims to evaluate vBMD, bone microarchitecture, and strength in ACH patients. Seventeen patients underwent clinical and biochemical evaluations, and genetic testing. High-resolution peripheral quantitative computed tomography was performed in 10 ACH patients and 21 age- and sex-matched healthy subjects. All individuals had the hotspot mutation of c.1138G > A in FGFR3. Linear growth retardation, disproportionate short stature, and genu varum are the most common manifestations. The mean height was 108.82 ± 24.08 cm (Z score: − 5.72 ± 0.96). Total vBMD in the ACH and the control groups was 427.08 ± 49.29 mg HA/cm3 versus 300.35 ± 69.92 mg HA/cm3 (p < 0.001) at the radius and 336.90 ± 79.33 mg HA/cm3 versus 292.20 ± 62.35 mg HA/cm3 (p = 0.098) at the tibia; both at the radius and tibia, vBMD of trabecular bones was significantly lower in the ACH group than in the control group, but vBMD of cortical bones was slightly higher in the ACH group. Trabecular separation and cortical thickness in the ACH group were significantly higher than those in the control group, but trabecular number was significantly decreased in the ACH group. Stiffness and failure load were only better at the radius in the ACH group. ACH patients have higher total and cortical vBMD, lower trabecular vBMD, worse trabecular bone microarchitecture, thicker cortical bone thickness, and better estimated bone strength.

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Data Availability

The raw datasets generated and/or analyzed during this study are not publicly available but are available from the corresponding author on reasonable request.

References

  1. Ornitz DM, Legeai-Mallet L (2017) Achondroplasia: development, pathogenesis, and therapy. Dev Dyn 246:291–309

    Article  CAS  Google Scholar 

  2. Shiang R, Thompson LM, Zhu YZ, Church DM, Fielder TJ, Bocian M, Winokur ST, Wasmuth JJ (1994) Mutations in the transmembrane domain of FGFR3 cause the most common genetic form of dwarfism, achondroplasia. Cell 78:335–342

    Article  CAS  Google Scholar 

  3. Rousseau F, Bonaventure J, Legeai-Mallet L, Pelet A, Rozet JM, Maroteaux P, Le Merrer M, Munnich A (1994) Mutations in the gene encoding fibroblast growth factor receptor-3 in achondroplasia. Nature 371:252–254

    Article  CAS  Google Scholar 

  4. Pauli RM (2019) Achondroplasia: a comprehensive clinical review. Orphanet J Rare Dis 14:1

    Article  Google Scholar 

  5. Coi A, Santoro M, Garne E, Pierini A, Addor MC, Alessandri JL, Bergman JEH, Bianchi F, Boban L, Braz P, Cavero-Carbonell C, Gatt M, Haeusler M, Klungsøyr K, Kurinczuk JJ, Lanzoni M, Lelong N, Luyt K, Mokoroa O, Mullaney C, Nelen V, Neville AJ, O’Mahony MT, Perthus I, Rankin J, Rissmann A, Rouget F, Schaub B, Tucker D, Wellesley D, Wisniewska K, Zymak-Zakutnia N, Barišić I (2019) Epidemiology of achondroplasia: a population-based study in Europe. Am J Med Genet A 179:1791–1798

    Google Scholar 

  6. Legare JM (1993) Achondroplasia. In: Adam MP, Ardinger HH, Pagon RA, Wallace SE, Bean LJH, Mirzaa G, Amemiya A (eds) GeneReviews(®). University of Washington, Seattle

    Google Scholar 

  7. McDonald EJ, De Jesus O (2021) Achondroplasia. In: StatPearls. StatPearls Publishing, Treasure Island

  8. Högler W, Ward LM (2020) New developments in the management of achondroplasia. Wien Med Wochenschr 170:104–111

    Article  Google Scholar 

  9. Arita ES, Pippa MG, Marcucci M, Cardoso R, Cortes AR, Watanabe PC, Oliveira JX (2013) Assessment of osteoporotic alterations in achondroplastic patients: a case series. Clin Rheumatol 32:399–402

    Article  Google Scholar 

  10. Matsushita M, Kitoh H, Mishima K, Kadono I, Sugiura H, Hasegawa S, Nishida Y, Ishiguro N (2016) Low bone mineral density in achondroplasia and hypochondroplasia. Pediatr Int 58:705–708

    Article  CAS  Google Scholar 

  11. Sims D, Onambélé-Pearson G, Burden A, Payton C, Morse C (2019) Whole-body and segmental analysis of body composition in adult males with achondroplasia using dual X-ray absorptiometry. PLoS ONE 14:e0213806

    Article  CAS  Google Scholar 

  12. Carey JJ, Delaney MF (2017) Utility of DXA for monitoring, technical aspects of DXA BMD measurement and precision testing. Bone 104:44–53

    Article  Google Scholar 

  13. Adams JE (2013) Advances in bone imaging for osteoporosis. Nat Rev Endocrinol 9:28–42

    Article  CAS  Google Scholar 

  14. Nishiyama KK, Shane E (2013) Clinical imaging of bone microarchitecture with HR-pQCT. Curr Osteoporos Rep 11:147–155

    Article  Google Scholar 

  15. Dash AS, Agarwal S, McMahon DJ, Cosman F, Nieves J, Bucovsky M, Guo XE, Shane E, Stein EM (2020) Abnormal microarchitecture and stiffness in postmenopausal women with isolated osteoporosis at the 1/3 radius. Bone 132:115211

    Article  CAS  Google Scholar 

  16. Mendes DAB, Coelho MCA, Gehrke B, de Pinho LKJ, Cardoso Lima LF, Paranhos-Neto F, de Mendonça LMC, Farias MLF, Madeira M (2021) Microarchitectural parameters and bone mineral density in patients with tumour-induced osteomalacia by HR-pQCT and DXA. Clin Endocrinol 95:587–594

    Article  CAS  Google Scholar 

  17. Folkestad L, Groth KA, Shanbhogue V, Hove H, Kyhl K, Østergaard JR, Jørgensen NR, Andersen NH, Gravholt CH (2020) Bone geometry, density, and microarchitecture in the distal radius and tibia in adults with Marfan syndrome assessed by HR-pQCT. J Bone Miner Res 35:2335–2344

    Article  CAS  Google Scholar 

  18. Li H, Ji C, Zong X, Zhang Y (2009) Height and weight standardized growth charts for Chinese children and adolescents aged 0 to 18 years. Chin J Pediatr 47:487–492

    Google Scholar 

  19. MacNeil JA, Boyd SK (2008) Improved reproducibility of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys 30:792–799

    Article  Google Scholar 

  20. Yu F, Xu Y, Hou Y, Lin Y, Jiajue R, Jiang Y, Wang O, Li M, Xing X, Zhang L, Qin L, Hsieh E, Xia W (2020) Age-, site-, and sex-specific normative centile curves for HR-pQCT-derived microarchitectural and bone strength parameters in a Chinese Mainland population. J Bone Miner Res 35:2159–2170

    Article  CAS  Google Scholar 

  21. Buie HR, Campbell GM, Klinck RJ, MacNeil JA, Boyd SK (2007) Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo micro-CT bone analysis. Bone 41:505–515

    Article  Google Scholar 

  22. Burghardt AJ, Buie HR, Laib A, Majumdar S, Boyd SK (2010) Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT. Bone 47:519–528

    Article  Google Scholar 

  23. Manske SL, Zhu Y, Sandino C, Boyd SK (2015) Human trabecular bone microarchitecture can be assessed independently of density with second generation HR-pQCT. Bone 79:213–221

    Article  CAS  Google Scholar 

  24. Hildebrand T, Laib A, Müller R, Dequeker J, Rüegsegger P (1999) Direct three-dimensional morphometric analysis of human cancellous bone: microstructural data from spine, femur, iliac crest, and calcaneus. J Bone Miner Res 14:1167–1174

    Article  CAS  Google Scholar 

  25. Pistoia W, van Rietbergen B, Lochmüller EM, Lill CA, Eckstein F, Rüegsegger P (2002) Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images. Bone 30:842–848

    Article  CAS  Google Scholar 

  26. Ajmal M, Mir A, Shoaib M, Malik SA, Nasir M (2017) Identification and in silico characterization of p.G380R substitution in FGFR3, associated with achondroplasia in a non-consanguineous Pakistani family. Diagn Pathol 12:47

  27. Liang H, Qi W, Jin C, Pang Q, Liu W, Jiang Y, Wang O, Li M, Xing X, Pan H, Xia W. Data from: evaluation of volumetric bone mineral density, bone microarchitecture and bone strength in patients with achondroplasia caused by FGFR3 c.1138G>A mutation. figshare. Dataset. https://doi.org/10.6084/m9.figshare.19071713.v1

  28. Klag KA, Horton WA (2016) Advances in treatment of achondroplasia and osteoarthritis. Hum Mol Genet 25:R2-8

    Article  CAS  Google Scholar 

  29. Daugherty A (2017) Achondroplasia: etiology, clinical presentation, and management. Neonatal Netw 36:337–342

    Article  Google Scholar 

  30. Han J, Yang YD, He Y, Liu WJ, Zhen L, Pan M, Yang X, Zhang VW, Liao C, Li DZ (2020) Rapid prenatal diagnosis of skeletal dysplasia using medical trio exome sequencing: benefit for prenatal counseling and pregnancy management. Prenat Diagn 40:577–584

    Article  CAS  Google Scholar 

  31. Dai WQ, Gu XF, Yu YG (2020) Exploring the clinical genetic characteristics and height for age growth curve of 210 patients with achondroplasia in China. Zhonghua Er Ke Za Zhi 58:461–467

    CAS  Google Scholar 

  32. Rao GN, Greger NG, Nelson DA (1999) Whole body bone mass and body composition in a girl with achondroplasia, at ages 9 through 12. J Clin Densitom 2:185–190

    Article  CAS  Google Scholar 

  33. de Vries OM, Johansen H, Fredwall SO (2021) Physical fitness and activity level in Norwegian adults with achondroplasia. Am J Med Genet A 185:1023–1032

    Article  Google Scholar 

  34. Okura T, Matsushita M, Mishima K, Esaki R, Seki T, Ishiguro N, Kitoh H (2018) Activated FGFR3 prevents subchondral bone sclerosis during the development of osteoarthritis in transgenic mice with achondroplasia. J Orthop Res 36:300–308

    CAS  Google Scholar 

  35. Chen H, Sun X, Yin L, Chen S, Zhu Y, Huang J, Jiang W, Chen B, Zhang R, Chen L, Nie M, Xie Y, Deng Z (2017) PTH 1–34 ameliorates the osteopenia and delayed healing of stabilized tibia fracture in mice with achondroplasia resulting from gain-of-function mutation of FGFR3. Int J Biol Sci 13:1254–1265

    Article  CAS  Google Scholar 

  36. Katsimbri P (2017) The biology of normal bone remodelling. Eur J Cancer Care 26:e12740

    Article  Google Scholar 

  37. Rowe P, Koller A, Sharma S (2021) Physiology, bone remodeling. In: StatPearls. StatPearls Publishing, Treasure Island

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Acknowledgements

We are so grateful to all of the participants in this study.

Funding

This study was supported by the National Natural Science Foundation of China (Grant No. 81970757), the Chinese National Key Technology R & D Program, Ministry of Science and Technology (Grant No. 2021YFC2501700), and the Chinese Academy of Medical Sciences-CAMS Innovation Fund for Medical Sciences (Grant No. CIFMS-2021-12M-1-002).

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Authors and Affiliations

  1. Key Laboratory of Endocrinology of National Health Commission, State Key Laboratory of Complex Severe and Rare Diseases, Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China

    Hanting Liang, Wenting Qi, Chenxi Jin, Qianqian Pang, Wei Liu, Yan Jiang, Ou Wang, Mei Li, Xiaoping Xing, Hui Pan & Weibo Xia

  2. Department of Endocrinology and Metabolism, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China

    Chenxi Jin

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  1. Hanting Liang
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Contributions

WBX designed the study and revised the manuscript. HTL and QQP analyzed the genetic results. HTL analyzed all data and draft the manuscript. WTQ and CXJ collected HR-pQCT data. WL, YJ, OW, ML, XPX, HP, and WBX collected clinical information of patients. HTL and WBX are responsible for the integrity of the data analysis. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Weibo Xia.

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Conflict of interest

Hanting Liang, Wenting Qi, Chenxi Jin, Qianqian Pang, Wei Liu, Yan Jiang, Ou Wang, Mei Li, Xiaoping Xing, Hui Pan, and Weibo Xia declares no competing interest.

Ethical Approval

The study was performed with the approval of the Ethics Committee of Peking Union Medical College Hospital (JS-1689).

Informed Consent

All of the subjects agreed to participate in this study and signed informed consent forms.

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All of the authors agreed to publish the manuscript.

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Liang, H., Qi, W., Jin, C. et al. Evaluation of Volumetric Bone Mineral Density, Bone Microarchitecture, and Bone Strength in Patients with Achondroplasia Caused by FGFR3 c.1138G > A Mutation. Calcif Tissue Int 112, 13–23 (2023). https://doi.org/10.1007/s00223-022-01027-2

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