Calcified Tissue International

, Volume 105, Issue 4, pp 373–382 | Cite as

The Local and Systemic Interactions Between Muscle and Bone in Postmenopausal Korean Women

  • Mi Kyung Kwak
  • Beom-Jun Kim
  • Jae Seung Kim
  • Seung Hun LeeEmail author
  • Jung-Min KohEmail author
Original Research


Despite many studies about local and systemic interactions between bone and muscle, the more dominant interaction remains unclear. We aimed to compare the association of skeletal muscle mass with bone mineral density (BMD) at the femur, which seemed more likely affected by local interaction, and the association of skeletal muscle mass with BMD at the lumbar spine (LS-BMD) and the trabecular bone score (TBS), which seemed more likely affected by systemic interaction. In 279 women, we measured the femoral neck BMD (FN-BMD), total hip BMD (TH-BMD), LS-BMD, and TBS. Appendicular skeletal muscle mass (ASM), lean mass (LM), and other LM (OLM; remaining LM excluding ASM) were measured using bioelectrical impedance analysis. ASM (β = 0.008–0.014, p < 0.001–0.014), OLM (β = 0.006–0.011, p < 0.001–0.044), and LM (β = 0.004–0.007, p < 0.001–0.020) were positively associated with FN-BMD and TH-BMD, but not with LS-BMD or TBS. The positive association of ASM, but not of OLM, was stronger than that of LM (p = 0.023). Odd ratios (ORs) with 95% confidence intervals (95% CIs) for osteoporosis were statistically significant for ASM (OR 0.74, 95% CI 0.59–0.93) and marginally significant for OLM (OR 0.80, 95% CI 0.64–1.01) in the femur, but not in the LS. The direct and indirect (through OLM) effects of ASM on BMD were 69.1–72.2% and 27.8–30.9%, respectively. In the conclusion, ASM was more positively associated with FN-BMD, but not with LS-BMD and TBS, than OLM. This suggests stronger effects of local interaction than systemic interaction between muscle and bone.


Bone Bone–muscle crosstalk Muscle Trabecular bone score 



This study was supported by Grants from the Korea Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (Project No. HI15C2792).

Compliance with Ethical Standards

Conflict of interest

MK Kwak, B-J Kim, JS Kim, SH Lee, and J-M Koh declare that they have no conflicts of interest.

Human and Animal Rights and Informed Consent

The study was approved by the institutional review board at Asan Medical Center (2018-0157), and all participants provided written informed consent.

Supplementary material

223_2019_585_MOESM1_ESM.tif (625 kb)
Supplementary material 1 (TIFF 625 kb). Fig. S1 Flowchart of patient inclusion in this study
223_2019_585_MOESM2_ESM.tif (296 kb)
Supplementary material 2 (TIFF 295 kb). Fig. S2 A model for explaining the relationship between appendicular skeletal muscle mass (ASM) and bone mineral density (BMD) at the femur, with other lean mass (OLM) except for ASM as a mediator. Model 1 assumes that ASM is directly associated with higher BMD by a coefficient of C. Model 2 considers that ASM affects other LM (represented by the coefficient A), which, in turn, affects BMD (represented by coefficient B). The direct effect (C′) was estimated using the product of coefficients A and B


  1. 1.
    Ethgen O, Beaudart C, Buckinx F, Bruyère O, Reginster JY (2017) The future prevalence of sarcopenia in Europe: a claim for public health action. Calcif Tissue Int 100:229–234. CrossRefGoogle Scholar
  2. 2.
    Reginster JY, Burlet N (2006) Osteoporosis: a still increasing prevalence. Bone 38:S4–S9. CrossRefGoogle Scholar
  3. 3.
    Yoo JI, Ha YC (2018) Review of epidemiology, diagnosis, and treatment of osteosarcopenia in Korea. J Bone Metab 25:1–7. CrossRefGoogle Scholar
  4. 4.
    Bruyère O, Beaudart C, Ethgen O, Reginster J-Y, Locquet M (2019) The health economics burden of sarcopenia: a systematic review. Maturitas 119:61–69. CrossRefGoogle Scholar
  5. 5.
    Hirschfeld HP, Kinsella R, Duque G (2017) Osteosarcopenia: where bone, muscle, and fat collide. Osteoporos Int 28:2781–2790. CrossRefGoogle Scholar
  6. 6.
    Bonewald LF, Kiel DP, Clemens TL, Esser K, Orwoll ES, O’Keefe RJ, Fielding RA (2013) Forum on bone and skeletal muscle interactions: summary of the proceedings of an ASBMR workshop. J Bone Miner Res 28:1857–1865. CrossRefGoogle Scholar
  7. 7.
    Maurel DB, Jahn K, Lara-Castillo N (2017) Muscle-bone crosstalk: emerging opportunities for novel therapeutic approaches to treat musculoskeletal pathologies. Biomedicines 5:62. CrossRefGoogle Scholar
  8. 8.
    Huang J, Hsu YH, Mo C, Abreu E, Kiel DP, Bonewald LF, Brotto M, Karasik D (2014) METTL21C is a potential pleiotropic gene for osteoporosis and sarcopenia acting through the modulation of the NF-kappaB signaling pathway. J Bone Miner Res 29:1531–1540. CrossRefGoogle Scholar
  9. 9.
    Karasik D, Kiel DP (2010) Evidence for pleiotropic factors in genetics of the musculoskeletal system. Bone 46:1226–1237. CrossRefGoogle Scholar
  10. 10.
    Sun L, Tan LJ, Lei SF, Chen XD, Li X, Pan R, Yin F, Liu QW, Yan XF, Papasian CJ, Deng HW (2011) Bivariate genome-wide association analyses of femoral neck bone geometry and appendicular lean mass. PLoS ONE 6:e27325. CrossRefGoogle Scholar
  11. 11.
    Natsui K, Tanaka K, Suda M, Yasoda A, Sakuma Y, Ozasa A, Ozaki S, Nakao K (2006) High-dose glucocorticoid treatment induces rapid loss of trabecular bone mineral density and lean body mass. Osteoporos Int 17:105–108. CrossRefGoogle Scholar
  12. 12.
    Shah K, Armamento-Villareal R, Parimi N, Chode S, Sinacore DR, Hilton TN, Napoli N, Qualls C, Villareal DT (2011) Exercise training in obese older adults prevents increase in bone turnover and attenuates decrease in hip bone mineral density induced by weight loss despite decline in bone-active hormones. J Bone Miner Res 26:2851–2859. CrossRefGoogle Scholar
  13. 13.
    Sipila S (2003) Body composition and muscle performance during menopause and hormone replacement therapy. J Endocrinol Invest 26:893–901. CrossRefGoogle Scholar
  14. 14.
    Villareal DT, Chode S, Parimi N, Sinacore DR, Hilton T, Armamento-Villareal R, Napoli N, Qualls C, Shah K (2011) Weight loss, exercise, or both and physical function in obese older adults. N Engl J Med 364:1218–1229. CrossRefGoogle Scholar
  15. 15.
    Brotto M, Bonewald L (2015) Bone and muscle: interactions beyond mechanical. Bone 80:109–114. CrossRefGoogle Scholar
  16. 16.
    Cianferotti L, Brandi ML (2014) Muscle-bone interactions: basic and clinical aspects. Endocrine 45:165–177. CrossRefGoogle Scholar
  17. 17.
    Pedersen BK (2011) Muscles and their myokines. J Exp Biol 214:337–346. CrossRefGoogle Scholar
  18. 18.
    Pedersen BK, Febbraio MA (2012) Muscles, exercise and obesity: skeletal muscle as a secretory organ. Nat Rev Endocrinol 8:457–465. CrossRefGoogle Scholar
  19. 19.
    Hamrick MW (2011) A role for myokines in muscle-bone interactions. Exerc Sport Sci Rev 39:43CrossRefGoogle Scholar
  20. 20.
    Hamrick MW, McNeil PL, Patterson SL (2010) Role of muscle-derived growth factors in bone formation. J Musculoskelet Neuronal Interact 10:64–70Google Scholar
  21. 21.
    Manolagas SC, Jilka RL (1995) Bone marrow, cytokines, and bone remodeling: emerging insights into the pathophysiology of osteoporosis. N Engl J Med 332:305–311. CrossRefGoogle Scholar
  22. 22.
    Hans D, Stenova E, Lamy O (2017) The trabecular bone score (TBS) complements DXA and the FRAX as a fracture risk assessment tool in routine clinical practice. Curr Osteoporos Rep 15:521–531. CrossRefGoogle Scholar
  23. 23.
    Kiel D (1995) Assessing vertebral fractures: national osteoporosis foundation working group on vertebral fractures. J Bone Miner Res 10:518–523. Google Scholar
  24. 24.
    WHO Collaborating Centre for Drug Statistics Methodology (2019) ATC/DDD Index. Accessed 27 May 2019
  25. 25.
    Chen L-K, Liu L-K, Woo J, Assantachai P, Auyeung T-W, Bahyah KS, Chou M-Y, Chen L-Y, Hsu P-S, Krairit O (2014) Sarcopenia in Asia: consensus report of the Asian working group for sarcopenia. J Am Med Dir Assoc 15:95–101CrossRefGoogle Scholar
  26. 26.
    Kanis JA, Melton LJ 3rd, Christiansen C, Johnston CC, Khaltaev N (1994) The diagnosis of osteoporosis. J Bone Miner Res 9:1137–1141. CrossRefGoogle Scholar
  27. 27.
    Silva BC, Leslie WD, Resch H, Lamy O, Lesnyak O, Binkley N, McCloskey EV, Kanis JA, Bilezikian JP (2014) Trabecular bone score: a noninvasive analytical method based upon the DXA image. J Bone Miner Res 29:518–530. CrossRefGoogle Scholar
  28. 28.
    McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, Barkmann R, Boutroy S, Brown J, Chapurlat R, Elders PJM, Fujita Y, Gluer CC, Goltzman D, Iki M, Karlsson M, Kindmark A, Kotowicz M, Kurumatani N, Kwok T, Lamy O, Leung J, Lippuner K, Ljunggren O, Lorentzon M, Mellstrom D, Merlijn T, Oei L, Ohlsson C, Pasco JA, Rivadeneira F, Rosengren B, Sornay-Rendu E, Szulc P, Tamaki J, Kanis JA (2016) A meta-analysis of trabecular bone score in fracture risk prediction and its relationship to FRAX. J Bone Miner Res 31:940–948. CrossRefGoogle Scholar
  29. 29.
    Yajnik CS, Yudkin JS (2004) The Y-Y paradox. Lancet 363:163. CrossRefGoogle Scholar
  30. 30.
    Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA, Schneider SM, Sieber CC, Topinkova E, Vandewoude M, Visser M, Zamboni M (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48:16–31. CrossRefGoogle Scholar
  31. 31.
    Weaver B, Wuensch KL (2013) SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients. Behav Res Methods 45:880–895. CrossRefGoogle Scholar
  32. 32.
    Baron RM, Kenny DA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51:1173–1182CrossRefGoogle Scholar
  33. 33.
    Burr DB, Robling AG, Turner CH (2002) Effects of biomechanical stress on bones in animals. Bone 30:781–786CrossRefGoogle Scholar
  34. 34.
    Frost HM (2003) Bone’s mechanostat: a 2003 update. Anat Rec Part A 275:1081–1101. CrossRefGoogle Scholar
  35. 35.
    Elkasrawy MN, Hamrick MW (2010) Myostatin (GDF-8) as a key factor linking muscle mass and bone structure. J Musculoskelet Neuronal Interact 10:56–63Google Scholar
  36. 36.
    Harry LE, Sandison A, Paleolog EM, Hansen U, Pearse MF, Nanchahal J (2008) Comparison of the healing of open tibial fractures covered with either muscle or fasciocutaneous tissue in a murine model. J Orthop Res 26:1238–1244. CrossRefGoogle Scholar
  37. 37.
    Kim KM, Lee EY, Lim S, Jang H-C, Kim C-O (2017) Favorable effects of skeletal muscle on bone are distinguished according to gender and skeletal sites. Osteoporos Sarcopenia 3:32–36. CrossRefGoogle Scholar
  38. 38.
    Locquet M, Beaudart C, Bruyere O, Kanis JA, Delandsheere L, Reginster JY (2018) Bone health assessment in older people with or without muscle health impairment. Osteoporos Int 29:1057–1067. CrossRefGoogle Scholar
  39. 39.
    Lloyd SA, Lang CH, Zhang Y, Paul EM, Laufenberg LJ, Lewis GS, Donahue HJ (2014) Interdependence of muscle atrophy and bone loss induced by mechanical unloading. J Bone Miner Res 29:1118–1130. CrossRefGoogle Scholar
  40. 40.
    Ausk BJ, Huber P, Srinivasan S, Bain SD, Kwon RY, McNamara EA, Poliachik SL, Sybrowsky CL, Gross TS (2013) Metaphyseal and diaphyseal bone loss in the tibia following transient muscle paralysis are spatiotemporally distinct resorption events. Bone 57:413–422. CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Division of Endocrinology and Metabolism, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulRepublic of Korea
  2. 2.Division of Endocrinology and MetabolismHallym University Dongtan Sacred Heart HospitalHwaseong-siRepublic of Korea
  3. 3.Division of Nuclear Medicine, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulRepublic of Korea

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