- Research article
- Open Access
- Open Peer Review
Transforming growth factor beta-1 (TGFB1) and peak bone mass: association between intragenic polymorphisms and quantitative ultrasound of the heel
© Tzakas et al; licensee BioMed Central Ltd. 2005
- Received: 15 January 2005
- Accepted: 14 June 2005
- Published: 14 June 2005
Variance of peak bone mass has a substantial genetic component, as has been shown with twin studies examining quantitative measures such as bone mineral density (BMD) and quantitative ultrasound (QUS). Evidence implicating single nucleotide polymorphisms (SNPs) of the transforming growth factor beta-1 (TGFB1) gene is steadily accumulating. However, a comprehensive look at multiple SNPs at this locus for their association with indices of peak bone mass has not been reported.
A cohort of 653 healthy Caucasian females 18 to 35 years old was genotyped for seven TGFB1 SNPs. Polymorphisms were detected by restriction endonuclease digestion of amplified DNA segments.
The frequencies of the least common allele at G-800A, C-509T, codon 10 (L10P), codon 25 (R25P), codon 263 (T263I), C861-20T, and 713-8 delC loci were 0.07, 0.33, 0.41, 0.08, 0.04, 0.25 and 0.01, respectively. A significant association was seen between QUS Stiffness Index (QUS-SI) and the SNP at codon 10 and the linked promoter SNP, C-509T. This association remained significant after multiple regression was used to incorporate important clinical covariates – age, BMI, level of activity, family history, and caffeine intake – into the model.
The association of QUS-SI with -509T is consistent with a gene-dose effect, while only individuals homozygous for the codon 10P allele showed a significant increase. In this cohort of young healthy Caucasian females, the T allele at position -509 is associated with greater bone mass as measured by calcaneal ultrasound.
- Bone Mineral Density
- Lumbar Spine Bone Mineral Density
- Peak Bone Mass
- Clinical Covariates
- Latent Associate Peptide
Osteoporosis is a common disorder of aging characterized by low bone mineral density (BMD), deteriorating bone microarchitecture, and increased fracture rate. Osteoporosis and BMD are both complex traits with a strong genetic component [1, 2]. Among the genes that have been associated with BMD are those encoding the vitamin D receptor [3, 4], the estrogen receptors [5, 6], collagen Iα1 , apolipoprotein E , and TGFB1 .
Abundant in bone matrix , secreted TGFB1 is an important regulator of osteoblast proliferation and differentiation and directly affects bone formation in vivo . Activating mutations in humans are associated with Camurati-Engelmann disease, a disorder of progressive diaphyseal dysplasia characterized by increased BMD [12, 13]. Homozygous knock-out of the TGFB1 gene in mice is associated with an osteopenic phenotype . It is not surprising, therefore, that the TGFB1 locus has emerged as a strong candidate gene in the study of osteoporosis genetics.
The TGF-β1 amino acid sequence is highly conserved across mammalian species, indicating a strong selection against variant forms of the protein . Variable expression or activation of TGF-β1 may therefore be associated with altered bone remodeling and different overall BMD . Thus, elevated serum TGF-β1 levels are associated with osteosclerosis, and conversely, decreased serum TGF-β1 with osteopenia.
A number of studies have examined the association of TGFB1 polymorphisms with TGF-β1 levels. In post-menopausal British women, the -509T allele was associated with higher total serum TGF-β1 , but this association was not confirmed in post-menopausal Chinese  or Japanese cohorts . Similarly, the L allele at codon 10 was found to be associated with higher serum TGF-β1 levels in middle aged European women , but these findings were not confirmed in elderly Australian  or Chinese  women.
Other studies have also examined these allelic variants with respect to effects on bone. In 256 postmenopausal Italian women, Bertoldo et al. found strong evidence of association between the 713-8delC SNP and: (i) femoral neck BMD (FN-BMD), (ii) prevalence of hip fractures, and (iii) high bone turnover . In 123 osteoporotic cases and 131 matched normal controls, Langdahl et al. found that the same 713-8delC deletion was associated with low bone mass and increased bone turnover . In 76 pre-menopausal women, Keen et al. reported that the 861-20C allele was associated with higher BMD at the femoral neck, but not at the lumbar spine or with quantitative ultrasound (QUS) at the heel . In a subsequent publication by Langdahl et al. involving 1168 osteoporotic cases and controls, the T allele at T861-20C was associated with significantly higher LS and FN BMD, while the T allele at C-509T was significantly associated with higher FN BMD, and the Pro allele of L10P was associated with greater FN BMD . A study of the L10P variant in 625 Japanese women showed significant association of the 10P allele with higher lumbar spine (LS) BMD and total BMD . This study also examined the -509 site and concluded that -509 T allele, alone or in combination with 10P, is a genetic determinant for osteoprosis. However, the more common allele at codon 10 (leucine) was found to be associated with higher LS BMD and FN BMD in middle-aged European women  and with higher FN BMD in Chinese elderly . In 1337 elderly Australian women, the 10P allele associated with lower hip BMD and heel QUS . The codon 10 polymorphism was not seen to have any association to BMD in 3382 elderly Caucasian American females . In 356 healthy Japanese adolescents, however, the -509 CC homozygotes were found to have 5 to 6% greater radial BMD, and higher bone mineral content than the corresponding TT group .
In none of these reports were multiple SNP sites examined simultaneously in relation to peak bone mass. We therefore undertook a study of seven TGFB1 polymorphisms in relation to BMD indices as well as clinical covariates in a group of healthy young women with well characterized clinical and laboratory phenotypes to determine their relationship to peak bone mass.
The 653 healthy non-related Caucasian female subjects presented in this report were recruited by advertising for a study of bone and mineral metabolism in the Greater Toronto Area, as described previously [4, 6]. In this study, data on 25 women identified as originating from the Indian sub-continent were excluded.
The study protocol was approved by the Institutional Review Board of the University of Toronto (Toronto, ON) and written consent was obtained from each individual at the onset of the study . Each subject completed a standardized questionnaire about lifestyle factors, menstrual and reproductive history, past history of medical diseases, current and prior medication use, history of fractures, and family history of osteoporosis. Summary clinical characteristics (mean ± SD) include: age, 27.5 ± 4.5 yr (range 18 to 35 yr); weight, 63.3 ± 11.6 kg; height, 1.65 ± 0.06 m; and BMI 23.2 ± 3.9 kg/m2.
Assessment of BMD
BMD was measured at the hip (left femoral neck = FN) and lumbar spine (L2-L4 = LS) by dual-energy X-ray absorptiometry using a DPX-L absorptiometer (Lunar Corp., Madison, WI, U.S.A.). BMD was reported as grams per square centimeter. Quantitative Ultrasound (QUS) measurements were also conducted, consisting of broadband ultrasound attenuation (BUA, dB/MHz), speed of sound (SOS, m/s) and the calculated heel stiffness index (SI, % of age-matched controls), at the right heel (Lunar Achilles; Lunar Corp., Madison WI), as published previously . Summary statistics for our study cohort were: LS-BMD, 1.19 ± 0.13 g/cm2; FN-BMD, 1.00 ± 0.12 g/cm2; and QUS-SI, 97.2 ± 14.1.
DNA isolation and genotyping
Primer sequences used for the amplification of polymorphic TGFB1 sites.
Amplicon Size (bp)
Haplotyping of -800 and -509 SNP loci was possible since both SNPs were amplified in one PCR product, and simultaneous digestion by Eco 181 and Tai I produced a unique pattern of fragments for each possible haplotype [28, 29]. Loci were tested for Hardy-Weinberg (HW) equilibrium of the distribution of the genotypes, and pairwise linkage disequilibrium (LD) coefficients calculated and normalized (Δ'), using methods of Weir et al. , and improved software as we have described . Bivariate correlations between BMD, QUS-SI, and lifestyle factors, menstrual and reproductive factors, and TGFB1 genotypes were assessed using Spearman rank correlation coefficients, as reported previously [4, 6]. Each TGFB1 SNP was added to the model without any clinical covariates and then with covariates used in our established model . All data analyses were performed with SPSS for Windows 10.0.7 (SPSS Inc., Chicago, Illinois, U.S.A.).
TGFB1 genotype and variant allele frequencies, and pair-wise standardized LD coefficients (Δ')
Linkage Disequilibrium Coefficients (Δ')
Variant Allele Frequency
Clinical characteristics by TGFB1 genotype
Clinical variables grouped by -509 and codon10 Genotype.*
27.1 ± 4.3
27.9 ± 4.7
27.5 ± 4.8
27.3 ± 4.2
27.6 ± 4.6
27.7 ± 4.9
63 ± 13
64 ± 11
62 ± 9
63 ± 2
62 ± 9
1.65 ± 0.06
1.65 ± 0.07
1.66 ± 0.07
1.65 ± 0.06
1.65 ± 0.07
1.65 ± 0.07
Calcium intake (mg/day)
590 ± 380
550 ± 340
510 ± 310
580 ± 370
570 ± 370
510 ± 300
Caffeine intake (cups/day)
1.49 ± 1.21
1.62 ± 1.61
1.33 ± 1.18
1.49 ± 1.20
1.65 ± 1.57
1.25 ± 1.21
23 ± 3
23 ± 3
23 ± 4
23 ± 3
23 ± 3
23 ± 3
TGFB1 SNPs and clinical characteristics
Correlation coefficients (Spearman R) and their significance (p) are shown for QUS-SI and BMD in relation to clinical, lifestyle and TGFB1 genotypes.*
Lumbar Spine BMD
Femoral Neck BMD
TGFB1 codon 10
Association of TGFB1 genotypes with BMD and QUS
There was no significant correlation of any TGFB1 SNP with BMD at FN or LS (data not shown). Of the seven loci, only the -509 SNP was significantly correlated with QUS-SI. (r = 0.078, p = 0.038). Since this SNP is in strong linkage disequilibrium with codon 10 (Δ' = 0.88) and 713-8delC (Δ' = -0.77), all three of these SNPs were included in further analysis.
Based on the model previously reported by Rubin et al. , the seven TGFB1 genotypes were each introduced as single additive variables (variant allele counted as 0, 1 or 2) to the original multivariate analysis to test for significance. The LS BMD model included the following clinical variables: weight, physical activity at time of study, and physical activity during adolescence, age, paternal history of osteoporosis, family history of osteoporosis, and past amenorrhea greater than 3 months. None of the TGFB1 SNPs were significant predictors of LS BMD, nor were results significant for femoral neck (data not shown).
Multiple linear regression analysis of genetic and clinical determinants of QUS-SI modelled to determine individual contribution of -509 and codon10.*
Active as adolescent
Active as Adolescent
Relatives with Osteoporosis
Relatives with Osteoporosis
TGF-β1 is a secreted factor that plays an important role in bone remodelling. It is a potent stimulator of osteoblastic bone formation, causing chemotaxis, proliferation and differentiation in committed osteoblasts . Although in vitro experiments have led to conflicting reports about the effects of exogenous TGF-β1 in cultured osteoblast systems [32, 33], secreted TGF-β1 leads to matrix growth and osteoblast stimulation in vivo, while it inhibits mineralization, osteoclast differentiation and the resorptive activity of mature osteoclasts [34, 35]. Mouse knockouts for TGFB1 have skeletal defects, including shortened long bones and decreased tibial BMD. In humans, however, mutations found in the pro-peptide of TGFB1 are associated with Camurati-Engelman Disease (CED), an autosomal dominant disorder manifesting as periosteal and endosteal thickening of the long bone diaphyses [12, 13]. Most of these mutations lie in the Latent Associated Peptide (LAP) that is cleaved from the mature TGF-β1 peptide. LAP subsequently binds to mature TGF-β1 to form an inactivated secretory complex. Presumably, mutations that interfere with binding of LAP to the mature peptide would lead to increased TGF-β1 activation, stimulating bone remodelling, net bone deposition, and resulting in a denser skeleton.
In our cohort, allele frequencies for the -800, -509, codon 10, codon 25 and codon 263 SNPs are in agreement with those published by Cambien et al. , and Syrris et al. , who examined French, Irish and UK populations. Allele frequencies in our cohort for 713-8delC and C861-20T, respectively, are comparable to those in the European Caucasians studied by Langdahl et al. and by Keen et al. [17, 18]. Of the 7 SNPs examined for linkage, 713-8delC was in complete negative LD with codon 25 and codon 263. The 713-8delC SNP was in strong negative LD with -509 (Δ' = -0.77) and codon 10 (Δ' = -0.80), suggesting a single haplotype. Moreover, disequilibrium coefficients in our population were comparable to those reported by Cambien et al .
The two SNPs in the promoter, G-800A and C-509T, may theoretically alter the binding of RNA polymerase or other transcription factors. Luedecking et al. found that the transcriptional activity of the -509T variant allele of the TGFB1 gene was slightly greater than that of the common C allele . Serum TGF-β1 concentrations are increased in a gene dose-dependent fashion, with differences in concentrations in TT homozygotes being twice that of TC individuals, when the CC genotype is taken as the referent . Our results for the -509 polymorphism are consistent with this view that the T allele (high TGF-β1 producer) is associated with increased bone formation in young women, since heel QUS-SI is increased in rough proportion to the number of T alleles present. Langdahl reported a similar finding in a healthy Danish middle aged cohort, in whom higher FN BMD was associated with TT genotype . In the Japanese population, however, the -509 CC genotype has been found associated with higher BMD . This difference may be due to background genetic differences in the populations, ascertainment differences affecting the TGF-β1 genotype distribution in the sample set, or environmental factors. Differences in linkage disequilibrium may also contribute to this discordance, and shed light on parallel differences with codon 10 associations. In some studies, the 10Pro allele is associated with increased BMD [21, 25], but not in others [20, 22, 23].
The TGFB1 codon 10 and 25 polymorphisms are located in the signal sequence, which is cleaved from the TGF-β1 precursor at codon 29 (Gly29-Leu30 peptide bond). In general, signal sequence mutations affect peptide export efficiency . The replacement of leucine by proline at position 10 would be expected to disrupt the alpha-helical domain, while replacement of arginine by proline at position 25 would change the characteristic polarity of the carboxyl domain of the signal sequence. In either case, altered signal peptide regulation leading to differential trafficking or export would be the likely mechanism underlying genotype-dependent differences in TGF-β1 metabolism.
The physiologic evidence for such differential expression is not extensive. Awad et al. reported a significant correlation between codon 25 genotype and amounts of TGF-β1 secreted by cultured lymphocytes stimulated in vitro . Significant association of the codon 10 genotype with plasma TGF-β1 concentrations, BMD at lumbar spine, and vertebral fracture frequency, has been reported in controls and 2 different Japanese populations of osteoporotic patients . In both control and osteoporotic groups, the association with higher plasma TGF-β1 and the 10P allele was roughly additive . In a study of Japanese adolescents, those homozygous for the 10P genotype had significantly higher BMD than those homozygous for the L10 allele . These results suggest that increased skeletal mineralization during puberty may be related to the presence of a 10P allele. Our study of Caucasian pre-menopausal women found no difference in BMD at either FN or LS, but found a positive association between the Leu10 allele and calcaneal QUS-SI.
Of the remaining SNPs, Langdahl et al. reported that the 713-8delC was more frequent in osteoporotic women (6/123), than controls (2/131) but no correlation to bone mass was demonstrated in the controls . It is possible that linkage of this SNP with other functional sites provides an explanation for variable but genuine association with parameters of bone strength and mineral density. Indeed, we observed that the 713-8delC is in negative disequilibrium with codon 10 and -509 (Δ' = -0.77 and -0.80, respectively) in our population. Thus, previous positive results with this genotype alone may represent association with a haplotype extending across all 3 loci.
None of the TGFB1 SNPs in this study was significantly associated with either spine or hip BMD. Although apparently negative in contrast to other studies, our findings may be explained in part by the demographic characteristics of our cohort. Ours was a population of healthy young adults, whereas previous research showing an association with codon 10 and 713-8delC was based on post-menopausal women diagnosed with osteoporosis . It is generally understood that studies of post-menopausal women are predominantly investigations of the rate of bone loss, whereas those in young adults are identifying genetic determinants of peak bone mass accumulation. While BMD is a measure of the density of the mineralized bone, QUS-SI is a measure of bone architecture as well .
The skeletal site examined for bone mass and bone quality is important. Modelling of data in twins has indicated that there are both common and specific genetic factors acting on bone at different skeletal sites and on different aspects on bone quality [42, 43]. Our study suggests that TGFB1 genetic variation does not seem to be a major factor in total bone mineralization per se, at least as measured by BMD at the hip and femur.
Significant linkage disequilibrium exists between -509 and codon10 alleles and the results in our cohort (Δ' = 0.88) are no exception. However, the LD is not complete, and it is therefore no surprise that both -509 and codon 10 show association to QUS-SI, even when entered as independent variables in the multiple regression analysis. When means are compared for each genotype at a single locus, only the -509 genotypes showed a gene dosage effect, much as Yamada et al. described in a cohort of Japanese adolescents . Evidence indicates that the T allele of -509 may be the more important SNP leading to an increase rate of transcription, which in turn affects bone mass. For our cohort, the multiple regression model for QUS-SI, as the dependent variable, adjusted for clinical covariates (age, height, weight, BMI, caffeine and calcium intake) and therefore these factors are likely confounders of the genotype effects seen.
Our findings must be interpreted in the context of several potential limitations. Our Caucasian cohort was recruited from an ethnically diverse urban population and admixture effects cannot be excluded. Only women were recruited, and we cannot say whether a similar association would be observed in men. Recruitment was conducted by public advertisement, and there may be significant bias toward those believing they were at higher risk for a bone related disease, particularly because of family history. However, the parameters for LS and FN BMD and for QUS-SI are comparable to other cohorts of healthy young women , and the associations we describe are independent of family history in our multiple regression model.
Common variations in DNA sequence are often associated with mild phenotypic effects . Thus even a single SNP could account for a significant variation in bone mass so as to potentially influence subsequent fracture risk. However, the contribution of genotypes determined by all intragenic loci within a gene must be evaluated with environmental factors, in order to generate a balanced picture of gene-environment interactions for a complex quantitative trait like peak bone mass.
This work was supported by an IOC Partnership Grant from the National Science and Engineering Research Council and Dairy Farmers of Canada.
- Pocock NA, Eisman JA, Hopper JL, Yeates MG, Sambrook PN, Eberl S: Genetic determinants of bone mass in adults. A twin study. J Clin Invest. 1987, 80: 706-710.View ArticlePubMedPubMed CentralGoogle Scholar
- Patel MS, Rubin LA, Cole DE: Genetic determinants of peak bone mass. The Osteoporosis Primer. Edited by: Henderson JE, Goltzman D. 2000, Cambridge: Cambridge University Press, 131-146.View ArticleGoogle Scholar
- Morrison NA, Qi JC, Tokita A, Kelly PJ, Crofts L, Nguyen TV, Sambrook PN, Eisman JA: Prediction of bone density from vitamin D receptor alleles. Nature. 1994, 367: 284-287. 10.1038/367284a0.View ArticlePubMedGoogle Scholar
- Rubin LA, Hawker GA, Peltekova VD, Fielding LJ, Ridout R, Cole DE: Determinants of peak bone mass: clinical and genetic analyses in a young female Canadian cohort. J Bone Miner Res. 1999, 14: 633-643.View ArticlePubMedGoogle Scholar
- Kobayashi S, Inoue S, Hosoi T, Ouchi Y, Shiraki M, Orimo H: Association of bone mineral density with polymorphism of the estrogen receptor gene. J Bone Miner Res. 1996, 11: 306-311.View ArticlePubMedGoogle Scholar
- Patel MS, Cole DE, Smith JD, Hawker GA, Wong B, Trang H, Vieth R, Meltzer P, Rubin LA: Alleles of the estrogen receptor alpha-gene and an estrogen receptor cotranscriptional activator gene, amplified in breast cancer-1 (AIB1), are associated with quantitative calcaneal ultrasound. J Bone Miner Res. 2000, 15: 2231-2239.View ArticlePubMedGoogle Scholar
- Grant SF, Reid DM, Blake G, Herd R, Fogelman I, Ralston SH: Reduced bone density and osteoporosis associated with a polymorphic Sp1 binding site in the collagen type I alpha 1 gene. Nat Genet. 1996, 14: 203-205. 10.1038/ng1096-203.View ArticlePubMedGoogle Scholar
- Shiraki M, Shiraki Y, Aoki C, Hosoi T, Inoue S, Kaneki M, Ouchi Y: Association of bone mineral density with apolipoprotein E phenotype. J Bone Miner Res. 1997, 12: 1438-1445.View ArticlePubMedGoogle Scholar
- Yamada Y, Miyauchi A, Goto J, Takagi Y, Okuizumi H, Kanematsu M, Hase M, Takai H, Harada A, Ikeda K: Association of a polymorphism of the transforming growth factor-beta1 gene with genetic susceptibility to osteoporosis in postmenopausal Japanese women. J Bone Miner Res. 1998, 13: 1569-1576.View ArticlePubMedGoogle Scholar
- Seyedin SM, Thompson AY, Bentz H, Rosen DM, McPherson JM, Conti A, Siegel NR, Galluppi GR, Piez KA: Cartilage-inducing factor-A. Apparent identity to transforming growth factor-beta. J Biol Chem. 1986, 261: 5693-5695.PubMedGoogle Scholar
- Cohen MM: TGF beta/Smad signaling system and its pathologic correlates. Am J Med Genet A. 2003, 116: 1-10. 10.1002/ajmg.a.10750.View ArticleGoogle Scholar
- Janssens K, Gershoni-Baruch R, Guanabens N, Migone N, Ralston S, Bonduelle M, Lissens W, Van ML, Vanhoenacker F, Verbruggen L: Mutations in the gene encoding the latency-associated peptide of TGF-beta 1 cause Camurati-Engelmann disease. Nat Genet. 2000, 26: 273-275. 10.1038/81563.View ArticlePubMedGoogle Scholar
- Kinoshita A, Fukumaki Y, Shirahama S, Miyahara A, Nishimura G, Haga N, Namba A, Ueda H, Hayashi H, Ikegawa S: TGFB1 mutations in four new families with Camurati-Engelmann disease: confirmation of independently arising LAP-domain-specific mutations. Am J Med Genet A. 2004, 127: 104-107. 10.1002/ajmg.a.20671.View ArticleGoogle Scholar
- Dickson MC, Martin JS, Cousins FM, Kulkarni AB, Karlsson S, Akhurst RJ: Defective hematopoiesis and vasculogenesis in transforming growth-factor-beta-1 knock out mice. Development. 1995, 121: 1845-1854.PubMedGoogle Scholar
- Derynck R, Jarrett JA, Chen EY, Goeddel DV: The murine transforming growth factor-beta precursor. J Biol Chem. 1986, 261: 4377-4379.PubMedGoogle Scholar
- Cambien F, Ricard S, Troesch A, Mallet C, Generenaz L, Evans A, Arveiler D, Luc G, Ruidavets JB, Poirier O: Polymorphisms of the transforming growth factor-beta 1 gene in relation to myocardial infarction and blood pressure. The Etude Cas-Temoin de l'Infarctus du Myocarde (ECTIM) Study. Hypertension. 1996, 28: 881-887.View ArticlePubMedGoogle Scholar
- Langdahl BL, Knudsen JY, Jensen HK, Gregersen N, Eriksen EF: A sequence variation: 713-8delC in the transforming growth factor-beta 1 gene has higher prevalence in osteoporotic women than in normal women and is associated with very low bone mass in osteoporotic women and increased bone turnover in both osteoporotic and normal women. Bone. 1997, 20: 289-294. 10.1016/S8756-3282(96)00363-8.View ArticlePubMedGoogle Scholar
- Keen RW, Snieder H, Molloy H, Daniels J, Chiano M, Gibson F, Fairbairn L, Smith P, MacGregor AJ, Gewert D: Evidence of association and linkage disequilibrium between a novel polymorphism in the transforming growth factor beta 1 gene and hip bone mineral density: a study of female twins. Rheumatology (Oxford). 2001, 40: 48-54. 10.1093/rheumatology/40.1.48.View ArticleGoogle Scholar
- Grainger DJ, Heathcote K, Chiano M, Snieder H, Kemp PR, Metcalfe JC, Carter ND, Spector TD: Genetic control of the circulating concentration of transforming growth factor type beta1. Hum Mol Genet. 1999, 8: 93-97. 10.1093/hmg/8.1.93.View ArticlePubMedGoogle Scholar
- Lau HH, Ho AY, Luk KD, Kung AW: Transforming growth factor-beta1 gene polymorphisms and bone turnover, bone mineral density and fracture risk in southern chinese women. Calcif Tissue Int. 2004, 74: 516-521. 10.1007/s00223-004-0163-4.View ArticlePubMedGoogle Scholar
- Yamada Y, Miyauchi A, Takagi Y, Tanaka M, Mizuno M, Harada A: Association of the C-509-->T polymorphism, alone of in combination with the T869-->C polymorphism, of the transforming growth factor-beta1 gene with bone mineral density and genetic susceptibility to osteoporosis in Japanese women. J Mol Med. 2001, 79: 149-156. 10.1007/s001090100190.View ArticlePubMedGoogle Scholar
- Hinke V, Seck T, Clanget C, Scheidt-Nave C, Ziegler R, Pfeilschifter J: Association of transforming growth factor-beta1 (TGFbeta1) T29 -> C gene polymorphism with bone mineral density (BMD), changes in BMD, and serum concentrations of TGF-beta1 in a population-based sample of postmenopausal german women. Calcif Tissue Int. 2001, 69: 315-320. 10.1007/s002230020024.View ArticlePubMedGoogle Scholar
- Dick IM, Devine A, Li S, Dhaliwal SS, Prince RL: The T869C TGF beta polymorphism is associated with fracture, bone mineral density, and calcaneal quantitative ultrasound in elderly women. Bone. 2003, 33: 335-341. 10.1016/S8756-3282(03)00158-3.View ArticlePubMedGoogle Scholar
- Bertoldo F, D'Agruma L, Furlan F, Colapietro F, Lorenzi MT, Maiorano N, Iolascon A, Zelante L, Locascio V, Gasparini P: Transforming growth factor-beta1 gene polymorphism, bone turnover, and bone mass in Italian postmenopausal women. J Bone Miner Res. 2000, 15: 634-639.View ArticlePubMedGoogle Scholar
- Langdahl BL, Carstens M, Stenkjaer L, Eriksen EF: Polymorphisms in the transforming growth factor beta 1 gene and osteoporosis. Bone. 2003, 32: 297-310. 10.1016/S8756-3282(02)00971-7.View ArticlePubMedGoogle Scholar
- Ziv E, Kahn A, Cauley J, Morin P, Saiz R, Browner W: No association between the TGF-beta 1 Leu10Pro polymorphism and osteoporosis among white women in the United States. Am J Med. 2003, 114: 227-231. 10.1016/S0002-9343(02)01393-1.View ArticlePubMedGoogle Scholar
- Yamada Y, Hosoi T, Makimoto F, Tanaka H, Seino Y, Ikeda K: Transforming growth factor beta-1 gene polymorphism and bone mineral density in Japanese adolescents. Am J Med. 1999, 106: 477-479. 10.1016/S0002-9343(99)00043-1.View ArticlePubMedGoogle Scholar
- Sawitzke AD, Sawitzke AL, Ward RH: HLA-DPB typing using co-digestion of amplified fragments allows efficient identification of heterozygous genotypes. Tissue Antigens. 1992, 40: 175-181.View ArticlePubMedGoogle Scholar
- Peltekova VD, Cole DE, Pavlova A, Rubin LA: Improved method for direct haplotyping at the vitamin D receptor gene locus. Clin Biochem. 1998, 31: 191-194. 10.1016/S0009-9120(98)00005-8.View ArticlePubMedGoogle Scholar
- Weir BS: . Genetic Data Analysis II. 1996, Sunderland, Massachusetts: Sinauer Associates, Inc. PublishersGoogle Scholar
- Hamilton DC, Cole DE: Standardizing a composite measure of linkage disequilibrium. Ann Hum Genet. 2004, 68: 234-239. 10.1046/j.1529-8817.2004.00056.x.View ArticlePubMedGoogle Scholar
- Pfeilschifter J, Seyedin SM, Mundy GR: Transforming growth factor beta inhibits bone resorption in fetal rat long bone cultures. J Clin Invest. 1988, 82: 680-685.View ArticlePubMedPubMed CentralGoogle Scholar
- Fuller K, Lean JM, Bayley KE, Wani MR, Chambers TJ: A role for TGFbeta(1) in osteoclast differentiation and survival. J Cell Sci. 2000, 113 (Pt 13): 2445-2453.PubMedGoogle Scholar
- Antosz ME, Bellows CG, Aubin JE: Effects of transforming growth factor beta and epidermal growth factor on cell proliferation and the formation of bone nodules in isolated fetal rat calvaria cells. J Cell Physiol. 1989, 140: 386-395. 10.1002/jcp.1041400225.View ArticlePubMedGoogle Scholar
- Dieudonne SC, Semeins CM, Goei SW, Vukicevic S, Nulend JK, Sampath TK, Helder M, Burger EH: Opposite effects of osteogenic protein and transforming growth factor beta on chondrogenesis in cultured long bone rudiments. J Bone Miner Res. 1994, 9: 771-780.View ArticlePubMedGoogle Scholar
- Syrris P, Carter ND, Metcalfe JC, Kemp PR, Grainger DJ, Kaski JC, Crossman DC, Francis SE, Gunn J, Jeffery S: Transforming growth factor-beta1 gene polymorphisms and coronary artery disease. Clin Sci. 1998, 95: 659-667. 10.1042/CS19980154.View ArticlePubMedGoogle Scholar
- Luedecking EK, DeKosky ST, Mehdi H, Ganguli M, Kamboh MI: Analysis of genetic polymorphisms in the transforming growth factor-beta1 gene and the risk of Alzheimer's disease. Hum Genet. 2000, 106: 565-569. 10.1007/s004390050026.View ArticlePubMedGoogle Scholar
- Walter P, Johnson AE: Signal sequence recognition and protein targeting to the endoplasmic reticulum membrane. Annu Rev Cell Biol. 1994, 10: 87-119. 10.1146/annurev.cb.10.110194.000511.View ArticlePubMedGoogle Scholar
- Awad MR, El Gamel A, Hasleton P, Turner DM, Sinnott PJ, Hutchinson IV: Genotypic variation in the transforming growth factor-beta1 gene: association with transforming growth factor-beta1 production, fibrotic lung disease, and graft fibrosis after lung transplantation. Transplantation. 1998, 66: 1014-1020. 10.1097/00007890-199810270-00009.View ArticlePubMedGoogle Scholar
- Yamada Y: Association of polymorphisms of the transforming growth factor-beta1 gene with genetic susceptibility to osteoporosis. Pharmacogenetics. 2001, 11: 765-771. 10.1097/00008571-200112000-00004.View ArticlePubMedGoogle Scholar
- Njeh CF, Boivin CM, Langton CM: The role of ultrasound in the assessment of osteoporosis: a review. Osteoporos Int. 1997, 7: 7-22. 10.1007/BF01623454.View ArticlePubMedGoogle Scholar
- Howard GM, Nguyen TV, Harris M, Kelly PJ, Eisman JA: Genetic and environmental contributions to the association between quantitative ultrasound and bone mineral density measurements: a twin study. J Bone Miner Res. 1998, 13: 1318-1327.View ArticlePubMedGoogle Scholar
- Beamer WG, Donahue LR, Rosen CJ, Baylink DJ: Genetic variability in adult bone density among inbred strains of mice. Bone. 1996, 18: 397-403. 10.1016/8756-3282(96)00047-6.View ArticlePubMedGoogle Scholar
- Chakravarti A: Population genetics--making sense out of sequence. Nat Genet. 1999, 21: 56-60. 10.1038/4482.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/6/29/prepub
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