Skip to main content
SpringerLink
Log in

Prediction of changes in bone mineral density in the elderly: contribution of “osteogenomic profile”

  • Original Article
  • Published:
Archives of Osteoporosis Aims and scope Submit manuscript

Abstract

Summary

The contribution of genetic variants to longitudinal bone loss has not been well documented. We constructed an “osteogenomic profile” based on 62 BMD-associated genetic variants and showed that the profile was significantly associated with bone loss, independently from baseline BMD and age. The osteogenomic profile can help predict bone loss in an individual.

Introduction

The rate of longitudinal bone loss (ΔBMD) is a risk factor for fracture. The variation in ΔBMD is partly determined by genetic factors. This study sought to define the association between an osteogenomic profile and ΔBMD.

Methods

The osteogenomic profile was created from 62 BMD-associated SNPs from genome-wide association studies (GWAS) that were genotyped in 1384 elderly men and women aged 60+ years. Weighted genetic risk scores (GRS) were constructed for each individual by summing the products of the number of risk alleles and the sex-specific regression coefficients [associated with BMD from GWAS]. ΔBMD, expressed as annual percent change-in-BMD, was determined by linear regression analysis for each individual who had had at least two femoral neck BMD measurements.

Results

The mean ΔBMD was − 0.65% (SD 1.64%) for women and − 0.57% (SD 1.40%) for men, and this difference was not statistically significant (P = 0.32). In women, each unit increase in GRS was associated with 0.21% (SE 0.10) higher ΔBMD at the femoral neck (P = 0.036), and this association was independent of baseline BMD and age. In logistic regression analysis, each unit increase of GRS was associated with 41% odds (95%CI: 1.07–1.87) of rapid bone loss (ΔBMD ≤ − 1.2%/year; mean of rapid loss group = − 2.2%/year). There was no statistically significant association between ΔBMD and GRS in men.

Conclusions

We conclude that the osteogenomic profile constructed from BMD-associated genetic variants is modestly associated with long-term changes in femoral neck BMD in women, but not in men.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Abbreviations

BMD:

Bone mineral density

ΔBMD:

Rate of longitudinal bone loss

GWAS:

Genome-wide association study

SNP:

Single-nucleotide polymorphism

GRS:

Genetic risk score

DOES:

Dubbo Osteoporosis Epidemiology Study

MrOS:

Osteoporotic Fractures in Men Study

SOF:

Study of Osteoporotic Fractures

References

  1. Nguyen TV, Sambrook PN, Eisman JA (1998) Bone loss, physical activity, and weight change in elderly women: the Dubbo osteoporosis epidemiology study. J Bone Miner Res 13(9):1458–1467

    Article  CAS  Google Scholar 

  2. Nguyen TV, Center JR, Eisman JA (2005) Femoral neck bone loss predicts fracture risk independent of baseline BMD. J Bone Miner Res Off J Am Soc Bone Miner Res 20(7):1195–1201. https://doi.org/10.1359/jbmr.050215

    Article  Google Scholar 

  3. Nguyen ND, Center JR, Eisman JA, Nguyen TV (2007) Bone loss, weight loss, and weight fluctuation predict mortality risk in elderly men and women. J Bone Miner Res Off J Am Soc Bone Miner Res 22(8):1147–1154. https://doi.org/10.1359/jbmr.070412

    Article  Google Scholar 

  4. Ensrud KE, Palermo L, Black DM, Cauley J, Jergas M, Orwoll ES, Nevitt MC, Fox KM, Cummings SR (1995) Hip and calcaneal bone loss increase with advancing age: longitudinal results from the study of osteoporotic fractures. J Bone Miner Res Off J Am Soc Bone Miner Res 10(11):1778–1787. https://doi.org/10.1002/jbmr.5650101122

    Article  CAS  Google Scholar 

  5. Jones G, Nguyen T, Sambrook P, Kelly PJ, Eisman JA (1994) Progressive loss of bone in the femoral neck in elderly people: longitudinal findings from the Dubbo osteoporosis epidemiology study. Br Med J 309(6956):691–695

    Article  CAS  Google Scholar 

  6. Makovey J, Nguyen TV, Naganathan V, Wark JD, Sambrook PN (2007) Genetic effects on bone loss in peri- and postmenopausal women: a longitudinal twin study. J Bone Miner Res Off J Am Soc Bone Miner Res 22(11):1773–1780. https://doi.org/10.1359/jbmr.070708

    Article  Google Scholar 

  7. Styrkarsdottir U, Halldorsson BV, Gretarsdottir S, Gudbjartsson DF, Walters GB, Ingvarsson T, Jonsdottir T, Saemundsdottir J, Center JR, Nguyen TV, Bagger Y, Gulcher JR, Eisman JA, Christiansen C, Sigurdsson G, Kong A, Thorsteinsdottir U, Stefansson K (2008) Multiple genetic loci for bone mineral density and fractures. N Engl J Med 358(22):2355–2365. https://doi.org/10.1056/NEJMoa0801197

    Article  CAS  PubMed  Google Scholar 

  8. Estrada K, Styrkarsdottir U, Evangelou E, Hsu YH, Duncan EL, Ntzani EE, Oei L, Albagha OME, Amin N, Kemp JP, Koller DL, Li G, Liu CT, Minster RL, Moayyeri A, Vandenput L, Willner D, Xiao SM, Yerges-Armstrong LM, Zheng HF, Alonso N, Eriksson J, Kammerer CM, Kaptoge SK, Leo PJ, Thorleifsson G, Wilson SG, Wilson JF, Aalto V, Alen M, Aragaki AK, Aspelund T, Center JR, Dailiana Z, Duggan DJ, Garcia M, Garcia-Giralt N, Giroux S, Hallmans G, Hocking LJ, Husted LB, Jameson KA, Khusainova R, Kim GS, Kooperberg C, Koromila T, Kruk M, Laaksonen M, Lacroix AZ, Lee SH, Leung PC, Lewis JR, Masi L, Mencej-Bedrac S, Nguyen TV, Nogues X, Patel MS, Prezelj J, Rose LM, Scollen S, Siggeirsdottir K, Smith AV, Svensson O, Trompet S, Trummer O, van Schoor NM, Woo J, Zhu K, Balcells S, Brandi ML, Buckley BM, Cheng S, Christiansen C, Cooper C, Dedoussis G, Ford I, Frost M, Goltzman D, González-Macías J, Kähönen M, Karlsson M, Khusnutdinova E, Koh JM, Kollia P, Langdahl BL, Leslie WD, Lips P, Ljunggren Ö, Lorenc RS, Marc J, Mellström D, Obermayer-Pietsch B, Olmos JM, Pettersson-Kymmer U, Reid DM, Riancho JA, Ridker PM, Rousseau F, lagboom PES, Tang NLS, Urreizti R, van Hul W, Viikari J, Zarrabeitia MT, Aulchenko YS, Castano-Betancourt M, Grundberg E, Herrera L, Ingvarsson T, Johannsdottir H, Kwan T, Li R, Luben R, Medina-Gómez C, Th Palsson S, Reppe S, Rotter JI, Sigurdsson G, van Meurs JBJ, Verlaan D, Williams FMK, Wood AR, Zhou Y, Gautvik KM, Pastinen T, Raychaudhuri S, Cauley JA, Chasman DI, Clark GR, Cummings SR, Danoy P, Dennison EM, Eastell R, Eisman JA, Gudnason V, Hofman A, Jackson RD, Jones G, Jukema JW, Khaw KT, Lehtimäki T, Liu Y, Lorentzon M, McCloskey E, Mitchell BD, Nandakumar K, Nicholson GC, Oostra BA, Peacock M, Pols HAP, Prince RL, Raitakari O, Reid IR, Robbins J, Sambrook PN, Sham PC, Shuldiner AR, Tylavsky FA, van Duijn CM, Wareham NJ, Cupples LA, Econs MJ, Evans DM, Harris TB, Kung AWC, Psaty BM, Reeve J, Spector TD, Streeten EA, Zillikens MC, Thorsteinsdottir U, Ohlsson C, Karasik D, Richards JB, Brown MA, Stefansson K, Uitterlinden AG, Ralston SH, Ioannidis JPA, Kiel DP, Rivadeneira F (2012) Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat Genet 44(5):491–501. https://doi.org/10.1038/ng.2249

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Mitchell JA, Chesi A, Elci O, McCormack SE, Roy SM, Kalkwarf HJ, Lappe JM, Gilsanz V, Oberfield SE, Shepherd JA, Kelly A, Grant SFA, Zemel BS (2016) Genetic risk scores implicated in adult bone fragility associate with pediatric bone density. J Bone Miner Res Off J Am Soc Bone Miner Res 31(4):789–795. https://doi.org/10.1002/jbmr.2744

    Article  CAS  Google Scholar 

  10. Rathbun AM, Shardell M, Orwig D, Hebel JR, Hicks GE, Beck T, Hochberg MC, Magaziner J (2016) Differences in the trajectory of bone mineral density change measured at the total hip and femoral neck between men and women following hip fracture. Arch Osteoporos 11:9–9. https://doi.org/10.1007/s11657-016-0263-6

    Article  PubMed  PubMed Central  Google Scholar 

  11. Greenspan SL, Maitland LA, Myers ER, Krasnow MB, Kido TH (1994) Femoral bone loss progresses with age: a longitudinal study in women over age 65. J Bone Miner Res Off J Am Soc Bone Miner Res 9(12):1959–1965. https://doi.org/10.1002/jbmr.5650091216

    Article  CAS  Google Scholar 

  12. Nguyen T, Sambrook P, Kelly P, Jones G, Lord S, Freund J, Eisman J (1993) Prediction of osteoporotic fractures by postural instability and bone density. Br Med J 307(6912):1111–1115

    Article  CAS  Google Scholar 

  13. Jones G, Nguyen T, Sambrook PN, Kelly PJ, Gilbert C, Eisman JA (1994) Symptomatic fracture incidence in elderly men and women: the Dubbo osteoporosis epidemiology study (DOES). Osteoporos Int 4(5):277–282. https://doi.org/10.1007/BF01623352

    Article  CAS  PubMed  Google Scholar 

  14. Simons LA, McCallum J, Simons J, Powell I, Ruys J, Heller R, Lerba C (1990) The Dubbo study: an Australian prospective community study of the health of elderly. Aust NZ J Med 20(6):783–789

    Article  CAS  Google Scholar 

  15. Browning SR, Browning BL (2007) Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet 81(5):1084–1097. https://doi.org/10.1086/521987

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ho-Le TP, Center JR, Eisman JA et al (2017) Prediction of bone mineral density and fragility fracture by genetic profiling. J Bone Miner Res 32(2):285–293. https://doi.org/10.1002/jbmr.2998

    Article  CAS  PubMed  Google Scholar 

  17. Grömping U (2007) Estimators of relative importance in linear regression based on variance decomposition. Am Stat 61(2):139–147. https://doi.org/10.1198/000313007X188252

    Article  Google Scholar 

  18. Nguyen TV, Sambrook PN, Eisman JA (1997) Sources of variability in bone mineral density measurements: implications for study design and analysis of bone loss. J Bone Miner Res 12(1):124–135. https://doi.org/10.1359/jbmr.1997.12.1.124

    Article  CAS  PubMed  Google Scholar 

  19. Burger H, de Laet CE, van Daele PL et al (1998) Risk factors for increased bone loss in an elderly population: the Rotterdam study. Am J Epidemiol 147(9):871–879

    Article  CAS  Google Scholar 

  20. Yang S, Center JR, Eisman JA et al (2015) Erratum to: association between fat mass, lean mass, and bone loss: the Dubbo osteoporosis epidemiology study. Osteoporosis Int 26(6):1865–1866. https://doi.org/10.1007/s00198-015-3101-6

    Article  CAS  Google Scholar 

  21. Genuer R, Poggi J-M, Tuleau-Malot C (2010) Variable selection using random forests. Pattern Recogn Lett 31(14):2225–2236. https://doi.org/10.1016/j.patrec.2010.03.014

    Article  Google Scholar 

  22. Genuer R, Poggi J-M, Tuleau-Malot C (2015) VSURF: an R package for variable selection using random forests. The R J 7(2):19–33

    Article  Google Scholar 

  23. Liaw A, Wiener M (2002) Classification and Regression by randomForest. R News 2(3):18–22

    Google Scholar 

  24. Eriksson J, Evans DS, Nielson CM, Shen J, Srikanth P, Hochberg M, McWeeney S, Cawthon PM, Wilmot B, Zmuda J, Tranah G, Mirel DB, Challa S, Mooney M, Crenshaw A, Karlsson M, Mellström D, Vandenput L, Orwoll E, Ohlsson C (2015) Limited clinical utility of a genetic risk score for the prediction of fracture risk in elderly subjects. J Bone Miner Res Off J Am Soc Bone Miner Res 30(1):184–194. https://doi.org/10.1002/jbmr.2314

    Article  Google Scholar 

  25. Frost SA, Nguyen ND, Center JR et al (2009) Timing of repeat BMD measurements: development of an absolute risk-based prognostic model. J Bone Miner Res Off J Am Soc Bone Miner Res 24(11):1800–1807. https://doi.org/10.1359/jbmr.090514

    Article  Google Scholar 

  26. Bliuc D, Nguyen ND, Alarkawi D, Nguyen TV, Eisman JA, Center JR (2015) Accelerated bone loss and increased post-fracture mortality in elderly women and men. Osteoporos Int 26(4):1331–1339. https://doi.org/10.1007/s00198-014-3014-9

    Article  CAS  PubMed  Google Scholar 

  27. Kado DM, Browner WS, Blackwell T, Gore R, Cummings SR (2000) Rate of bone loss is associated with mortality in older women: a prospective study. J Bone Miner Res Off J Am Soc Bone Miner Res 15(10):1974–1980. https://doi.org/10.1359/jbmr.2000.15.10.1974

    Article  CAS  Google Scholar 

  28. Jones G, Nguyen T, Sambrook P, Kelly PJ, Eisman JA (1994) Progressive loss of bone in the femoral neck in elderly people: longitudinal findings from the Dubbo osteoporosis epidemiology study. BMJ (Clinical research ed) 309(6956):691–695

    Article  CAS  Google Scholar 

  29. Kemp JP, Morris JA, Medina-Gomez C, Forgetta V, Warrington NM, Youlten SE, Zheng J, Gregson CL, Grundberg E, Trajanoska K, Logan JG, Pollard AS, Sparkes PC, Ghirardello EJ, Allen R, Leitch VD, Butterfield NC, Komla-Ebri D, Adoum AT, Curry KF, White JK, Kussy F, Greenlaw KM, Xu C, Harvey NC, Cooper C, Adams DJ, Greenwood CMT, Maurano MT, Kaptoge S, Rivadeneira F, Tobias JH, Croucher PI, Ackert-Bicknell CL, Bassett JHD, Williams GR, Richards JB, Evans DM (2017) Identification of 153 new loci associated with heel bone mineral density and functional involvement of GPC6 in osteoporosis. Nat Genet 49(10):1468–1475. https://doi.org/10.1038/ng.3949

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Coalition TPM (2014) The Case for Personalized Medicine, 4th edn. Personalized Medicine Coalition, Washington, DC

    Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the assistance of Sr Janet Watters, Donna Reeves, Shaye Field, and Jodie Martin for the interview, data collection, and measurement bone mineral density. We also appreciate the invaluable help of the staff of Dubbo Base Hospital. We thank the IT group of the Garvan Institute of Medical Research for the management of the database. The Dubbo Osteoporosis Epidemiology Study was supported by the Australian National Health and Medical Research Council, Grant Number APP1031494 (CIA T. Nguyen).

Authors’ roles: TVN has full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study conception: TVN, JAE, and THL. Study design and data collection: TVN, JAE, and JRC. Data analysis: THL, HMP, HTN, and TVN. Interpretation of results: TVN, JAE, JRC, and THL. Drafting manuscript: THL and TVN. Critical reviews and final approval of manuscript content: THL, HMP, JAE, JRC, HTN, and TVN.

Author information

Authors and Affiliations

  1. School of Biomedical Engineering, University of Technology Sydney (UTS), Ultimo, NSW, 2007, Australia

    Thao P. Ho-Le, Hung T. Nguyen & Tuan V. Nguyen

  2. Bone Biology Division, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, NSW, 2010, Australia

    Thao P. Ho-Le, Hanh M. Pham, Jacqueline R. Center, John A. Eisman & Tuan V. Nguyen

  3. St Vincent Clinical School, UNSW Australia, Sydney, NSW, 2052, Australia

    Hanh M. Pham, Jacqueline R. Center, John A. Eisman & Tuan V. Nguyen

  4. School of Medicine, Notre Dame University, Fremantle, WA, 6160, Australia

    John A. Eisman & Tuan V. Nguyen

  5. School of Public Health and Community Medicine, UNSW Australia, Sydney, NSW, 2052, Australia

    Tuan V. Nguyen

Authors
  1. Thao P. Ho-Le
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hanh M. Pham
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jacqueline R. Center
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. John A. Eisman
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hung T. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tuan V. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tuan V. Nguyen.

Ethics declarations

The study was approved by the St Vincent’s Campus Research Ethics Committee and written informed consent was obtained from all participants.

Conflicts of interest

Professor John A. Eisman has served as consultant on the Scientific Advisory Board for Amgen, Eli Lilly, Merck Sharp & Dohme, Novartis, Sanofi-Aventis, Servier and deCode. Professor J.R. Center has given educational talks for and received travel expenses from Amgen, Merck Sharp & Dohme, Novartis, Sanofi-Aventis. She has received travel expenses from Merck Sharp & Dohme, Amgen and Aspen. Professor Tuan V. Nguyen has received honoraria for consulting and speaking in symposia sponsored by Merck Sharp & Dohme, Roche, Sanofi-Aventis, Novartis, and Bridge Healthcare Pty Ltd. (Vietnam). Professor J. A. Eisman, Professor T. V. Nguyen and Dr. J. R. Center have received grants from Sanofi, BUPA. Professor T. V. Nguyen has received NHMRC project grant. Other authors have no conflicts of interest.

Electronic supplementary material

ESM 1

(PDF 230 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ho-Le, T.P., Pham, H.M., Center, J.R. et al. Prediction of changes in bone mineral density in the elderly: contribution of “osteogenomic profile”. Arch Osteoporos 13, 68 (2018). https://doi.org/10.1007/s11657-018-0480-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11657-018-0480-2

Keywords

Search

Navigation