Osteoporosis International

, Volume 19, Issue 3, pp 303–310 | Cite as

A whole genome linkage scan for QTLs underlying peak bone mineral density

  • F. Zhang
  • P. Xiao
  • F. Yang
  • H. Shen
  • D.-H. Xiong
  • H.-Y. Deng
  • C. J. Papasian
  • B. M. Drees
  • J. J. Hamilton
  • R. R. Recker
  • H.-W. Deng
Original Article



We conducted a whole genome linkage scan for quantitative trait loci (QTLs) underlying peak bone mineral density (PBMD). Our efforts identified several potential genomic regions for PBMD and highlighted the importance of epistatic interaction and sex-specific analyses in identifying genetic regions underlying PBMD variation.


Peak bone mineral density (PBMD) is an important clinical risk predictor of osteoporosis and explains a large part of bone mineral density (BMD) variation.


To detect susceptive quantitative trait loci (QTLs) for PBMD variation including consideration of epistatic and sex-specific effects, we conducted a whole genome linkage scan (WGLS) for PBMD using 2,200 Caucasians from 207 pedigrees, aged 20–50 years. All the individuals were genotyped with 410 microsatellite markers. In addition to WGLS in the total combined sample of males and females, we conducted epistatic interaction analyses, and sex-specific subgroup linkage analyses.


We identified several potential genomic regions that met the criteria for suggestive linkage. The most impressing region is 12p12 for hip PBMD (LOD = 2.79) in the total sample. Epistatic interaction analyses found a significant epistatic interaction between 12p12 and 22q13 (p = 0.0021) for hip PBMD. Additionally, we detected suggestive linkage evidence at 15q26 (LOD = 2.93), 2p13 (LOD = 2.64), and Xq27 (LOD = 2.64). Sex-specific analyses suggested the presence of sex-specific QTLs for PBMD variation.


Our efforts identified several potential regions for PBMD and highlighted the importance of epistatic interaction and sex-specific analyses in identifying genetic regions underlying PBMD variation.


Epistatic interaction PBMD QTL Sex-specific Whole genome linkage scan 


  1. 1.
    Consensus Development Conference (1993) Bone mass and fracture risk. Am J Med 95:1S–78SGoogle Scholar
  2. 2.
    America’s Bone Health (2002) The state of osteoporosis and low bone mass in our nation. National Osteoporosis FoundationGoogle Scholar
  3. 3.
    Orsini LS, Rousculp MD, Long SR, Wang S (2005) Health care utilization and expenditures in the United States: a study of osteoporosis-related fractures. Osteoporos Int 16:359–371PubMedCrossRefGoogle Scholar
  4. 4.
    Heaney RP, Abrams S, Dawson-Hughes B (2000) Peak bone mass. Osteoporos Int 11:985–1009PubMedCrossRefGoogle Scholar
  5. 5.
    Hernandez CJ, Beaupre GS, Carter DR (2003) A theoretical analysis of the relative influences of peak BMD, age-related bone loss and menopause on the development of osteoporosis. Osteoporos Int 14:843–847PubMedCrossRefGoogle Scholar
  6. 6.
    Hui SL, Slemenda CW, Johnston CC Jr (1990) The contribution of bone loss to postmenopausal osteoporosis. Osteoporos Int 1:30–34PubMedCrossRefGoogle Scholar
  7. 7.
    Kammerer CM, Schneider JL, Cole SA et al (2003) Quantitative trait loci on chromosomes 2p, 4p, and 13q influence bone mineral density of the forearm and hip in Mexican Americans. J Bone Miner Res 18:2245–2252PubMedCrossRefGoogle Scholar
  8. 8.
    Karasik D, Cupples LA, Hannan MT, Kiel DP (2003) Age, gender, and body mass effects on quantitative trait loci for bone mineral density: the Framingham Study. Bone 33:308–316PubMedCrossRefGoogle Scholar
  9. 9.
    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 14:943–951PubMedCrossRefGoogle Scholar
  10. 10.
    Deng HW, Deng H, Liu YJ et al (2002) A genomewide linkage scan for quantitative-trait loci for obesity phenotypes. Am J Hum Genet 70:1138–1151PubMedCrossRefGoogle Scholar
  11. 11.
    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 87:5151–5159PubMedCrossRefGoogle Scholar
  12. 12.
    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 9:1503–1514PubMedCrossRefGoogle Scholar
  13. 13.
    Recker R, Lappe J, Davies K, Heaney R (2000) Characterization of perimenopausal bone loss: a prospective study. J Bone Miner Res 15:1965–1973PubMedCrossRefGoogle Scholar
  14. 14.
    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 22:12–25PubMedCrossRefGoogle Scholar
  15. 15.
    Huang QY, Xu FH, Shen H et al (2004) Genome scan for QTLs underlying bone size variation at 10 refined skeletal sites: genetic heterogeneity and the significance of phenotype refinement. Physiol Genomics 17:326–331PubMedCrossRefGoogle Scholar
  16. 16.
    O’Connell JR, Weeks DE (1998) PedCheck: a program for identification of genotype incompatibilities in linkage analysis. Am J Hum Genet 63:259–266PubMedCrossRefGoogle Scholar
  17. 17.
    Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin-rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 30:97–101PubMedCrossRefGoogle Scholar
  18. 18.
    Amos CI (1994) Robust variance-components approach for assessing genetic linkage in pedigrees. Am J Hum Genet 54:535–543PubMedGoogle Scholar
  19. 19.
    Amos CI, Zhu DK, Boerwinkle E (1996) Assessing genetic linkage and association with robust components of variance approaches. Ann Hum Genet 60(Pt 2):143–160PubMedCrossRefGoogle Scholar
  20. 20.
    Almasy L, Blangero J (1998) Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 62:1198–1211PubMedCrossRefGoogle Scholar
  21. 21.
    Blangero J, Williams JT, Almasy L (2000) Robust LOD scores for variance component-based linkage analysis. Genet Epidemiol 19 [Suppl 1]:S8–S14PubMedCrossRefGoogle Scholar
  22. 22.
    Hamet P, Merlo E, Seda O et al (2005) Quantitative founder-effect analysis of French Canadian families identifies specific loci contributing to metabolic phenotypes of hypertension. Am J Hum Genet 76:815–832PubMedCrossRefGoogle Scholar
  23. 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 21:1536–1544PubMedCrossRefGoogle Scholar
  24. 24.
    Mukhopadhyay N, Almasy L, Schroeder M, Mulvihill WP, Weeks DE (2005) Mega2: data-handling for facilitating genetic linkage and association analyses. Bioinformatics 21:2556–2557PubMedCrossRefGoogle Scholar
  25. 25.
    Camp NJ, Farnham JM (2001) Correcting for multiple analyses in genomewide linkage studies. Ann Hum Genet 65:577–582PubMedCrossRefGoogle Scholar
  26. 26.
    Mathias RA, Freidhoff LR, Blumenthal MN (2001) Genome-wide linkage analyses of total serum IgE using variance components analysis in asthmatic families. Genet Epidemiol 20:340–355PubMedCrossRefGoogle Scholar
  27. 27.
    Tsukamoto K, Orimo H, Hosoi T et al (2000) Association of bone mineral density with polymorphism of the human matrix Gla protein locus in elderly women. J Bone Miner Metab 18:27–30PubMedCrossRefGoogle Scholar
  28. 28.
    Price PA, Thomas GR, Pardini AW, Figueira WF, Caputo JM, Williamson MK (2002) Discovery of a high molecular weight complex of calcium, phosphate, fetuin, and matrix gamma-carboxyglutamic acid protein in the serum of etidronate-treated rats. J Biol Chem 277:3926–3934PubMedCrossRefGoogle Scholar
  29. 29.
    Bohlooly Y, Mahlapuu M, Andersen H et al (2004) Osteoporosis in MCHR1-deficient mice. Biochem Biophys Res Commun 318:964–969CrossRefGoogle Scholar
  30. 30.
    Shen H, Zhang YY, Long JR et al (2004) A genome-wide linkage scan for bone mineral density in an extended sample: evidence for linkage on 11q23 and Xq27. J Med Genet 41:743–751PubMedCrossRefGoogle Scholar
  31. 31.
    Mochida Y, Parisuthiman D, Yamauchi M (2006) Biglycan is a positive modulator of BMP-2 induced osteoblast differentiation. Adv Exp Med Biol 585:101–113PubMedCrossRefGoogle Scholar
  32. 32.
    Parisuthiman D, Mochida Y, Duarte WR, Yamauchi M (2005) Biglycan modulates osteoblast differentiation and matrix mineralization. J Bone Miner Res 20:1878–1886PubMedCrossRefGoogle Scholar
  33. 33.
    Dlouhy SR, Christian JC, Haines JL, Conneally PM, Hodes ME (1987) Localization of the gene for a syndrome of X-linked skeletal dysplasia and mental retardation to Xq27-qter. Hum Genet 75:136–139PubMedCrossRefGoogle Scholar
  34. 34.
    Zhang W, Amir R, Stockton DW, Van DV I, Bacino CA, Zoghbi HY (2000) Terminal osseous dysplasia with pigmentary defects maps to human chromosome Xq27.3-xqter. Am J Hum Genet 66:1461–1464PubMedCrossRefGoogle Scholar
  35. 35.
    Ogawa S, Hosoi T, Shiraki M et al (2000) Association of estrogen receptor beta gene polymorphism with bone mineral density. Biochem Biophys Res Commun 269:537–541PubMedCrossRefGoogle Scholar
  36. 36.
    Scariano JK, Simplicio SG, Montoya GD, Garry PJ, Baumgartner RN (2004) Estrogen receptor beta dinucleotide (CA) repeat polymorphism is significantly associated with bone mineral density in postmenopausal women. Calcif Tissue Int 74:501–508PubMedCrossRefGoogle Scholar
  37. 37.
    Mayr-Wohlfart U, Kessler S, Knochel W, Puhl W, Gunther KP (2001) BMP-4 of Xenopus laevis stimulates differentiation of human primary osteoblast-like cells. J Bone Joint Surg Br 83:144–147PubMedCrossRefGoogle Scholar
  38. 38.
    Peng H, Wright V, Usas A, Gearhart B, Shen HC, Cummins J, Huard J (2002) Synergistic enhancement of bone formation and healing by stem cell-expressed VEGF and bone morphogenetic protein-4. J Clin Invest 110:751–759PubMedCrossRefGoogle Scholar
  39. 39.
    Bayoumi R, Saar K, Lee YA et al (2001) Localisation of a gene for an autosomal recessive syndrome of macrocephaly, multiple epiphyseal dysplasia, and distinctive facies to chromosome 15q26. J Med Genet 38:369–373PubMedCrossRefGoogle Scholar
  40. 40.
    Eyre S, Roby P, Wolstencroft K et al (2002) Identification of a locus for a form of spondyloepiphyseal dysplasia on chromosome 15q26.1: exclusion of aggrecan as a candidate gene. J Med Genet 39:634–638PubMedCrossRefGoogle Scholar
  41. 41.
    Gleghorn L, Ramesar R, Beighton P, Wallis G (2005) A mutation in the variable repeat region of the aggrecan gene (AGC1) causes a form of spondyloepiphyseal dysplasia associated with severe, premature osteoarthritis. Am J Hum Genet 77:484–490PubMedCrossRefGoogle Scholar
  42. 42.
    Sano M, Inoue S, Hosoi T et al (1995) Association of estrogen receptor dinucleotide repeat polymorphism with osteoporosis. Biochem Biophys Res Commun 217:378–383PubMedCrossRefGoogle Scholar
  43. 43.
    Laflamme N, Giroux S, Loredo-Osti JC et al (2005) A frequent regulatory variant of the estrogen-related receptor alpha gene associated with BMD in French-Canadian premenopausal women. J Bone Miner Res 20:938–944PubMedCrossRefGoogle Scholar
  44. 44.
    Yamada Y, Ando F, Niino N, Shimokata H (2003) Association of polymorphisms of interleukin-6, osteocalcin, and vitamin D receptor genes, alone or in combination, with bone mineral density in community-dwelling Japanese women and men. J Clin Endocrinol Metab 88:3372–3378PubMedCrossRefGoogle Scholar
  45. 45.
    Murray RE, McGuigan F, Grant SF, Reid DM, Ralston SH (1997) Polymorphisms of the interleukin-6 gene are associated with bone mineral density. Bone 21:89–92PubMedCrossRefGoogle Scholar
  46. 46.
    Roschger P, Matsuo K, Misof BM et al (2004) Normal mineralization and nanostructure of sclerotic bone in mice over expressing Fra-1. Bone 34:776–782PubMedCrossRefGoogle Scholar
  47. 47.
    Bollerslev J, Wilson SG, Dick IM et al (2005) LRP5 gene polymorphisms predict bone mass and incident fractures in elderly Australian women. Bone 36:599–606PubMedCrossRefGoogle Scholar
  48. 48.
    Sobacchi C, Vezzoni P, Reid DM et al (2004) Association between a polymorphism affecting an AP1 binding site in the promoter of the TCIRG1 gene and bone mass in women. Calcif Tissue Int 74:35–41PubMedCrossRefGoogle Scholar
  49. 49.
    Karasik D, Myers RH, Cupples LA et al (2002) Genome screen for quantitative trait loci contributing to normal variation in bone mineral density: the Framingham Study. J Bone Miner Res 17:1718–1727PubMedCrossRefGoogle Scholar
  50. 50.
    Ioannidis JP, Ng MY, Sham PC et al (2007) Meta-analysis of genome-wide scans provides evidence for sex- and site-specific regulation of bone mass. J Bone Miner Res 22:173–183PubMedCrossRefGoogle Scholar
  51. 51.
    Lee YH, Rho YH, Choi SJ, Ji JD, Song GG (2006) Meta-analysis of genome-wide linkage studies for bone mineral density. J Hum Genet 51:480–486PubMedCrossRefGoogle Scholar

Copyright information

© International Osteoporosis Foundation and National Osteoporosis Foundation 2007

Authors and Affiliations

  • F. Zhang
    • 1
    • 2
  • P. Xiao
    • 2
  • F. Yang
    • 2
    • 5
  • H. Shen
    • 2
  • D.-H. Xiong
    • 2
  • H.-Y. Deng
    • 3
  • C. J. Papasian
    • 3
  • B. M. Drees
    • 4
  • J. J. Hamilton
    • 3
  • R. R. Recker
    • 2
  • H.-W. Deng
    • 1
    • 2
    • 3
  1. 1.The Key Laboratory of Biomedical Information Engineering of the Ministry of Education and Institute of Molecular Genetics, School of Life Science and TechnologyXi’an Jiaotong UniversityXi’anPeople’s Republic of China
  2. 2.Department of Biomedical Sciences and Osteoporosis Research Center, School of MedicineCreighton UniversityOmahaUSA
  3. 3.Department of Orthopaedic Surgery and Basic Medical Sciences, School of MedicineUniversity of Missouri-Kansas CityKansas CityUSA
  4. 4.Department of Internal Medicine and Basic Medical Sciences, School of MedicineUniversity of Missouri-Kansas CityKansas CityUSA
  5. 5.Laboratory of Molecular and Statistical Genetics, College of Life SciencesHunan Normal UniversityChangshaPeople’s Republic of China

Personalised recommendations