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Comparison of whole genome linkage scans in premenopausal and postmenopausal women: no bone-loss-specific QTLs were implicated

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Abstract

Summary

This study was conducted to investigate if there exist bone-loss-specific quantitative trait loci (QTLs) for females. Genome-wide linkage scans were conducted in total, premenopausal, and postmenopausal women, respectively. No QTLs exclusively were found in postmenopausal women, suggesting that no bone-loss-specific QTL was implicated independent of BMD in our sample.

Introduction

Bone mineral density (BMD) in elderly women is determined jointly by peak bone mass achieved before menopause and by subsequent bone loss upon and after menopause. Peak bone mass is under strong genetic control, but whether bone loss has genetic determination independent of peak BMD is unknown.

Materials and methods

To investigate if there exist bone-loss-specific quantitative trait loci (QTLs) for females, we conducted genome-wide linkage scans in 2,582 Caucasian females from 451 pedigrees including 1,486 premenopausal and 1,096 postmenopausal women. Linkage analyses were performed in the total sample and premenopausal and postmenopausal women subgroups, respectively, and the results were compared.

Results

No linkage evidence was found exclusively in postmenopausal women. Linkage signals identified are largely consistent in the total, premenopausal, and postmenopausal samples. For example, for spine BMD, for the total sample, a significant linkage was obtained on 15q13 (LOD = 3.67), and LOD scores of 1.52 and 2.49 were achieved on 15q13 in premenopausal and postmenopausal women, respectively.

Conclusions

We did not find any QTLs exclusively in postmenopausal women; hence, no specific QTL for bone loss was implicated independent of BMD in our female sample.

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References

  1. Kamel HK, O’Connell MB (2006) Introduction: postmenopausal osteoporosis as a major public health issue. J Manag Care Pharm 12:2–3

    Google Scholar 

  2. Cooper C, Cawley M, Bhalla A et al (1995) Childhood growth, physical activity, and peak bone mass in women. J Bone Miner Res 10:940–947

    PubMed  CAS  Google Scholar 

  3. Rubin LA, Hawker GA, Peltekova VD et al (1999) Determinants of peak bone mass: clinical and genetic analyses in a young female Canadian cohort. J Bone Miner Res 14:633–643

    Article  PubMed  CAS  Google Scholar 

  4. Kamei T, Aoyagi K, Matsumoto T et al (1999) Age-related bone loss: relationship between age and regional bone mineral density. Tohoku J Exp Med 187:141–147

    Article  PubMed  CAS  Google Scholar 

  5. Recker RR, Heaney RP (1990) Age-related bone loss in women. J Bone Miner Res 5:307–308

    PubMed  CAS  Google Scholar 

  6. Riggs BL, Wahner HW, Melton LJ 3rd et al (1986) Rates of bone loss in the appendicular and axial skeletons of women. Evidence of substantial vertebral bone loss before menopause. J Clin Invest 77:1487–1491

    Article  PubMed  CAS  Google Scholar 

  7. Karasik D, Hannan MT, Cupples LA et al (2004) Genetic contribution to biological aging: the Framingham Study. J Gerontol A Biol Sci Med Sci 59:218–226

    PubMed  Google Scholar 

  8. Richelson LS, Wahner HW, Melton LJ 3rd et al (1984) Relative contributions of aging and estrogen deficiency to postmenopausal bone loss. N Engl J Med 311:1273–1275

    PubMed  CAS  Google Scholar 

  9. Cheng G, Yuan Y, Liu J (1997) Relative contribution of ageing and menopause to the changes of lumbar bone density in 1,400 Beijing women. Zhonghua Fu Chan Ke Za Zhi 32:532–534

    PubMed  CAS  Google Scholar 

  10. Douchi T, Yamamoto S, Yoshimitsu N et al (2002) Relative contribution of aging and menopause to changes in lean and fat mass in segmental regions. Maturitas 42:301–306

    Article  PubMed  Google Scholar 

  11. Gambacciani M, Spinetti A, de Simone L et al (1993) The relative contributions of menopause and aging to postmenopausal vertebral osteopenia. J Clin Endocrinol Metab 77:1148–1151

    Article  PubMed  CAS  Google Scholar 

  12. Steiger P, Cummings SR, Black DM et al (1992) Age-related decrements in bone mineral density in women over 65. J Bone Miner Res 7:625–632

    PubMed  CAS  Google Scholar 

  13. Nuti R, Martini G (1993) Effects of age and menopause on bone density of entire skeleton in healthy and osteoporotic women. Osteoporos Int 3:59–65

    Article  PubMed  CAS  Google Scholar 

  14. McGuigan FE, Murray L, Gallagher A et al (2002) Genetic and environmental determinants of peak bone mass in young men and women. J Bone Miner Res 17:1273–1279

    Article  PubMed  CAS  Google Scholar 

  15. Deng HW, Stegman MR, Davies KM et al (1999) Genetic determination of variation and covariation of peak bone mass at the hip and spine. J Clin Densitom 2:251–263

    Article  PubMed  CAS  Google Scholar 

  16. Yang F, Shen H, Jiang H et al (2006) On genetic studies of bone loss. J Bone Miner Res 21:1676–1677

    Article  PubMed  Google Scholar 

  17. Christian JC, Yu PL, Slemenda CW et al (1989) Heritability of bone mass: a longitudinal study in aging male twins. Am J Hum Genet 44:429–433

    PubMed  CAS  Google Scholar 

  18. Kelly PJ, Nguyen T, Hopper J et al (1993) Changes in axial bone density with age: a twin study. J Bone Miner Res 8:11–17

    PubMed  CAS  Google Scholar 

  19. Brown LB, Streeten EA, Shapiro JR et al (2005) Genetic and environmental influences on bone mineral density in pre- and post-menopausal women. Osteoporos Int 16:1849–1856

    Article  PubMed  Google Scholar 

  20. Liu YJ, Shen H, Xiao P et al (2006) Molecular genetic studies of gene identification for osteoporosis: a 2004 update. J Bone Miner Res 21:1511–1535

    Article  PubMed  CAS  Google Scholar 

  21. Koller DL, Rodriguez LA, Christian JC et al (1998) Linkage of a QTL contributing to normal variation in bone mineral density to chromosome 11q12–13. J Bone Miner Res 13:1903–1908

    Article  PubMed  CAS  Google Scholar 

  22. Karasik D, Cupples LA, Hannan MT et al (2004) Genome screen for a combined bone phenotype using principal component analysis: the Framingham study. Bone 34:547–556

    Article  PubMed  CAS  Google Scholar 

  23. Xiao P, Shen H, Guo YF et al (2006) Genomic regions identified for BMD in a large sample including epistatic interactions and gender-specific effects. J Bone Miner Res 21:1536–1544

    Article  PubMed  CAS  Google Scholar 

  24. Deng HW, Deng H, Liu YJ et al (2002) A genome wide linkage scan for quantitative-trait loci for obesity phenotypes. Am J Hum Genet 70:1138–1151

    Article  PubMed  CAS  Google Scholar 

  25. Cummings SR, Kelsey JL, Nevitt MC et al (1985) Epidemiology of osteoporosis and osteoporotic fractures. Epidemiol Rev 7:178–208

    PubMed  CAS  Google Scholar 

  26. Genant HK, Grampp S, Gluer CC et al (1994) Universal standardization for dual x-ray absorptiometry: patient and phantom cross-calibration results. J Bone Miner Res 9:1503–1514

    Article  PubMed  CAS  Google Scholar 

  27. Recker R, Lappe J, Davies K et al (2000) Characterization of perimenopausal bone loss: a prospective study. J Bone Miner Res 15:1965–1973

    Article  PubMed  CAS  Google Scholar 

  28. Deng HW, Mahaney MC, Williams JT et al (2002) Relevance of the genes for bone mass variation to susceptibility to osteoporotic fractures and its implications to gene search for complex human diseases. Genet Epidemiol 22:12–25

    Article  PubMed  Google Scholar 

  29. Deng HW, Xu FH, Huang QY et al (2002) A whole-genome linkage scan suggests several genomic regions potentially containing quantitative trait Loci for osteoporosis. J Clin Endocrinol Metab 87:5151–5159

    Article  PubMed  CAS  Google Scholar 

  30. O’Connell JR, Weeks DE (1998) PedCheck: a program for identification of genotype incompatibilities in linkage analysis. Am J Hum Genet 63:259–266

    Article  PubMed  Google Scholar 

  31. Abecasis GR, Cherny SS, Cookson WO et al (2002) Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 30:97–101

    Article  PubMed  CAS  Google Scholar 

  32. Almasy L, Blangero J (1998) Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 62:1198–1211

    Article  PubMed  CAS  Google Scholar 

  33. Amos CI (1994) Robust variance-components approach for assessing genetic linkage in pedigrees. Am J Hum Genet 54:535–543

    PubMed  CAS  Google Scholar 

  34. Mukhopadhyay N, Almasy L, Schroeder M et al (2005) Mega2: data-handling for facilitating genetic linkage and association analyses. Bioinformatics 21:2556–2557

    Article  PubMed  CAS  Google Scholar 

  35. Lander E, Kruglyak L (1995) Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet 11:241–247

    Article  PubMed  CAS  Google Scholar 

  36. Davis JW, Ross PD, Wasnich RD et al (1991) Long-term precision of bone loss rate measurements among postmenopausal women. Calcif Tissue Int 48:311–318

    Article  PubMed  CAS  Google Scholar 

  37. Whitney CW, Lind BK, Wahl PW (1998) Quality assurance and quality control in longitudinal studies. Epidemiol Rev 20:71–80

    PubMed  CAS  Google Scholar 

  38. Karasik D, Cupples LA, Hannan MT et al (2003) Age, gender, and body mass effects on quantitative trait loci for bone mineral density: the Framingham Study. Bone 33:308–316

    Article  PubMed  CAS  Google Scholar 

  39. Ralston SH, Galwey N, MacKay I et al (2005) Loci for regulation of bone mineral density in men and women identified by genome wide linkage scan: the FAMOS study. Hum Mol Genet 14:943–951

    Article  PubMed  CAS  Google Scholar 

  40. Ji Y, Rebert NA, Joslin JM et al (2000) Structure of the highly conserved HERC2 gene and of multiple partially duplicated paralogs in human. Genome Res 10:319–329

    Article  PubMed  CAS  Google Scholar 

  41. Nicholls RD, Knepper JL (2001) Genome organization, function, and imprinting in Prader-Willi and Angelman syndromes. Annu Rev Genomics Hum Genet 2:153–175

    Article  PubMed  CAS  Google Scholar 

  42. Hoybye C, Hilding A, Jacobsson H et al (2002) Metabolic profile and body composition in adults with Prader-Willi syndrome and severe obesity. J Clin Endocrinol Metab 87:3590–3597

    Article  PubMed  CAS  Google Scholar 

  43. Vestergaard P, Kristensen K, Bruun JM et al (2004) Reduced bone mineral density and increased bone turnover in Prader-Willi syndrome compared with controls matched for sex and body mass index—a cross-sectional study. J Pediatr 144:614–619

    Article  PubMed  Google Scholar 

  44. Liu YZ, Dvornyk V, Lu Y et al (2005) A novel pathophysiological mechanism for osteoporosis suggested by an in vivo gene expression study of circulating monocytes. J Biol Chem 280:29011–29016

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

Investigators of this work were partially supported by grants from National Institutes of Health (R01 AR050496, K01 AR02170-01, R01 AR45349-01, R01 GM60402-01A1, and R21 AG027110-01A1, P50 AR055081). The study also benefited from the National Natural Science Foundation of China (30570875), Xi’an Jiaotong University, Huo Yingdong Education Foundation, Hunan Province, and the Ministry of Education of China.

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Authors and Affiliations

  1. The Key Laboratory of Biomedical Information Engineering of Ministry of Education and Institute of Molecular Genetics, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, People’s Republic of China

    H. Yan, Q. Zhou & H.-W. Deng

  2. Departments of Basic Medical Sciences and Orthopedic Surgery, University of Missouri-Kansas City, 2411 Holmes Street, Room M3-CO3, Kansas City, MO, 64108-2792, USA

    H. Yan, Y.-J. Liu & H.-W. Deng

  3. Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, NE, 68131, USA

    P. Xiao & R. R. Recker

  4. Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, 410081, People’s Republic of China

    H.-W. Deng

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  1. H. Yan
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  2. Y.-J. Liu
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  3. Q. Zhou
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  4. P. Xiao
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  5. R. R. Recker
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  6. H.-W. Deng
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Correspondence to H.-W. Deng.

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Yan, H., Liu, YJ., Zhou, Q. et al. Comparison of whole genome linkage scans in premenopausal and postmenopausal women: no bone-loss-specific QTLs were implicated. Osteoporos Int 20, 771–777 (2009). https://doi.org/10.1007/s00198-008-0723-y

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  • DOI: https://doi.org/10.1007/s00198-008-0723-y

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