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BioMed Research International
Volume 2014 (2014), Article ID 320828, 5 pages
http://dx.doi.org/10.1155/2014/320828
Research Article

Association Analysis between g.18873C>T and g.27522G>A Genetic Polymorphisms of OPG and Bone Mineral Density in Chinese Postmenopausal Women

1Department of Orthopaedic Surgery, The General Hospital of Beijing Military Area Command, No. 5 Nanmencang Road, Dongcheng District, Beijing 100700, China
2Department of Endocrinology, The General Hospital of Beijing Military Area Command, No. 5 Nanmencang Road, Dongcheng District, Beijing 100700, China

Received 27 May 2014; Accepted 4 August 2014; Published 15 December 2014

Academic Editor: Germán Vicente-Rodriguez

Copyright © 2014 Fei Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Several studies report that the OPG is an important candidate gene in the pathogenesis of osteoporosis. This study aimed to detect the potential association of OPG gene polymorphisms with osteoporosis in postmenopausal women. We recruited 928 subjects containing 463 with primary postmenopausal osteoporosis and 465 healthy volunteers as controls. The BMD of neck hip, lumbar spine (), and total hip were assessed by dual-energy X-ray absorptiometry (DEXA). Through the created restriction site-polymerase chain reaction (CRS-PCR), PCR-restriction fragment length polymorphism (PCR-RFLP), and DNA sequencing methods, the g.18873C>T and g.27522G>A have been investigated. As for g.18873C>T, our data indicated that subjects with CC genotype have significantly higher BMD value than those of CT and TT genotypes (all values < 0.05). As for g.27522G>A, the BMD values of subjects with GG genotype were significantly higher than those of GA and AA genotypes (all values < 0.05). Our findings suggest that the OPG g.18873C>T and g.27522G>A genetic polymorphisms are associated with the decreased risk for osteoporosis in Chinese postmenopausal women.

1. Introduction

Osteoporosis is a multifactorial disease in the postmenopausal women, which is characterized by low bone mineral density (BMD) and deteriorated microarchitecture of bone with the increased susceptibility to fracture [19]. BMD is a complex trait that is determined by multiple interaction of environmental, metabolic, and genetic factors [10]. It is well accepted that the genetic factors play key roles in the etiology of osteoporosis [1116]. Growing evidence indicates that osteoprotegerin gene (OPG) is one of the most important candidate genes for influencing the pathogenesis of osteoporosis [9, 1726]. Some genetic polymorphisms (such as A163G, T245G, T950C, G1181C, g.18861A>G, and g.27406C>T) in OPG gene have been reported to play genetic influence on BMD and osteoporosis [6, 7, 9, 10, 16, 18, 22, 2532]. However, there are no similar related studies which reported the relationship of OPG g.18873C>T and g.27522G>A genetic polymorphisms with BMD and osteoporosis. Therefore, this study aims to detect these two OPG genetic polymorphisms and to assess their potential association with BMD and osteoporosis in postmenopausal women.

2. Subjects and Methods

2.1. Studied Subjects

In total, 928 Chinese postmenopausal women were enrolled in this case-control study, containing 463 with primary postmenopausal osteoporosis (aged 45–88 years) and 465 healthy volunteers as controls (aged 47–90 years). All subjects were recruited from the General Hospital of Beijing Military Area Command between January 2009 and November 2013. All individuals were genetically unrelated Chinese Han population and lived in Beijing, China. Those individuals suffering from present or past history of diseases or taking drugs which could affect bone metabolism were excluded from this study. This study was approved by the Ethics Committee of the General Hospital of Beijing Military Area Command. All participants have provided the informed consent for this study.

2.2. Measurement of BMD

The BMD of neck hip, lumbar spine (), and total hip were assessed through dual-energy X-ray absorptiometry (DEXA) (Norland Coopersurgical Corp., WI, USA) [33]. The value of BMD was automatically calculated from bone area (cm2) and bone mineral content (g) and performed as g/cm2.

2.3. DNA Extraction and Genotyping of OPG Genetic Polymorphisms

The peripheral venous blood was collected from each individual in this case-control study. Genomic DNA were extracted using the DNA isolation kit (Invitrogen, Carlsbad, CA, USA) and stored at −20°C until analyzed. According to the DNA sequences (GenBank ID: NG_012202.1) and mRNA sequences (GenBank ID: NM_002546.3) of the human OPG gene, the specific polymerase chain reaction (PCR) primers were designed by the Primer Premier 5.0 software (Premier Biosoft International, Palo Alto, CA). Table 1 shows the sequences of primers, PCR product regions, annealing temperature, and fragment sizes. The PCR amplifications were performed on a total volume of 20 μL reaction mixture containing 50 ng mixed DNA template, 1x buffer (100 mmol Tris-HCl, pH 8.3; 500 mmol KCl), 0.25 μmol primers, 2.0 mmol MgCl2, 0.25 mmol dNTPs, and 0.5 U Taq DNA polymerase (TaKaRa, Dalian, China). The PCR protocol was carried out in an initial denaturation at 95°C for 5 min, followed by 30 cycles of 94°C for 30 s, annealing at the corresponding temperature (given in Table 1) for 30 s, and 72°C for 30 s, with a final extension at 72°C for 8 min. The genotypes of OPG g.18873C>T genetic polymorphism were investigated by the created restriction site-PCR (CRS-PCR) method with one of the primers containing a nucleotide mismatch, which enables the use of restriction enzymes for discriminating sequence variations [3438]. Through the PCR-restriction fragment length polymorphism (PCR-RFLP) method, we detected the genotypes of OPG g.27522G>A genetic polymorphism. Following the supplier’s manual, the amplified PCR products (5 μL) were digested with 2 U selected restriction enzymes (performed on Table 1, MBI Fermentas, St. Leon-Rot, Germany) at 37°C for 10 h. The digested PCR products were separated by electrophoresis for 1 h at 100 V on 2.5% agarose gel including 0.5 μg/mL ethidium bromide. The different genotypes were observed directly under ultraviolet (UV) light. To confirm the genotyping test results from CRS-PCR and PCR-RFLP methods, we selected random samples (10% of the total samples) to reanalyze through the DNA sequencing method (ABI3730xl DNA Analyzer, Applied Biosystems, Foster City, CA).

Table 1: PCR, CRS-PCR, and PCR-RFLP analysis used for genotyping OPG SNPs.
2.4. Statistical Analyses

The Hardy-Weinberg equilibrium for the genetic variants in the studied subjects was assessed by the chi-squared () test. The distribution of allelic and genotypic frequencies was compared in the studied subjects through the chi-squared () test. The multiple regression analyses were performed to detect the potential relationships between the variables. All data were shown as the deviation (SD) of the mean. The Statistical Package for Social Sciences software (SPSS, version 17.0; SPSS Inc.; Chicago, IL, USA) was utilized to evaluate all statistical analyses. Statistically significance was set at value < 0.05.

3. Results

3.1. Identification and Genotyping of OPG Genetic Polymorphisms

Through the CRS-PCR, PCR-RFLP, and DNA sequencing methods, we have successfully detected and genotyped two OPG genetic polymorphisms (g.18873C>T and g.27522G>A). As for g.18873C>T, our sequence analyses indicate that this genetic polymorphism causes CT mutation, results into a nonsynonymous mutation in exon 2 at 18873 position of OPG gene, and leads to threonine (Thr) to isoleucine (Ile) amino acid replacement (p.Thr20Ile, reference sequences GenBank IDs: NG_012202.1, NM_002546.3, and NP_002537.3). The PCR products of g.18873C>T were digested with AciI restriction enzymes and divided into three genotypes, CC (196 bp and 20 bp), CT (216 bp, 196 bp, and 20 bp), and TT (216 bp, Table 1). As for g.27522G>A, this genetic polymorphism causes GA mutation. It is a synonymous mutation in exon 5 at 27522 position of OPG gene (p. cysteine (Cys) 319Cys, reference sequences GenBank IDs: NG_012202.1, NM_002546.3, and NP_002537.3). The PCR products of 27522G>A were digested with SphI restriction enzymes and divided into three genotypes, GG (173 bp and 80 bp), GA (253 bp, 173 bp, and 80 bp), and AA (253 bp, Table 1).

3.2. Allele and Genotype Frequencies

Table 2 shows the frequencies of allele and genotype for OPG g.18873C>T and g.27522G>A genetic polymorphisms. As for g.18873C>T, the genotypic frequencies in osteoporosis cases (CC, 43.41%; CT, 41.25%; TT, 15.33%) were statistically significantly different from those of healthy controls (CC, 50.97%; CT, 39.78%; TT, 9.25%; , ), and significant differences were found between the allele frequencies of cases (C, 64.04%; T, 35.96%) and those of healthy controls (C, 70.86%; T, 29.14%, , ). As for g.27522G>A, the allele frequencies in osteoporosis cases (G, 66.63%; A, 33.37%) were not consistent with healthy controls (G, 70.97%; A, 29.03%; , ). The genotype frequencies in osteoporosis cases (GG, 46.65%; GA, 39.96%; AA, 13.39%) were significantly different from healthy controls (GG, 48.60%; GA, 44.73%; AA, 6.67%; , ). As shown in Table 2, the distributions of these two genetic variants were fitted with Hardy-Weinberg equilibrium (all values > 0.05).

Table 2: Genotypic and allelic frequencies of OPG genetic polymorphisms in the studied subjects.
3.3. OPG Genetic Polymorphisms Associated with BMD

The values of age, weight, height, body mass index (BMI), adjusted neck hip BMD, adjusted spine BMD, and adjusted total hip BMD in the studied subjects are shown in Table 3. Our data indicated that the OPG g.18873C>T and g.27522G>A genetic polymorphisms were statistically associated with the adjusted neck hip BMD, adjusted spine BMD, and adjusted total hip BMD. As for g.18873C>T, subjects with CC genotype had significantly higher adjusted BMD value than those of CT and TT genotypes (all values < 0.05). As for g.27522G>A, subjects with GG genotype had significantly higher adjusted BMD value than those of GA and AA genotypes (all values < 0.05).

Table 3: Characteristics of OPG genetic polymorphisms in the total group of subjects.

4. Discussion

Osteoporosis remains an important and complex health problem in the postmenopausal women in the world. Previous studies indicated that this disease is caused by the combined effects of genetic and environmental factors [16], but the genetic factors play key roles for the development of osteoporosis [1116]. Evidence from the published reports approved that several OPG genetic polymorphisms have been potentially associated with BMD and osteoporosis [6, 7, 9, 10, 16, 18, 22, 2532]. However, findings from these observations are still inconsistent, and the exact mechanism of osteoporosis etiology is poorly understood. In this case-control study, we firstly evaluated the genetic effects of OPG g.18873C>T and g.27522G>A genetic polymorphisms on BMD and osteoporosis in Chinese postmenopausal women by association analyses method. Results from this study indicated that there were significant differences in the allelic and genotypic frequencies among primary postmenopausal osteoporosis patients and healthy controls (for g.18873C>T, , ; for g.27522G>A, , , Table 2). Subjects with the wild genotypes of OPG g.18873C>T and g.27522G>A genetic polymorphisms have the significantly higher value of adjusted neck hip BMD, adjusted spine BMD, and adjusted total hip BMD than those of mutation genotypes (all values < 0.05, Table 3). The allele-T of g.18873C>T and allele-A of g.27522G>A genetic polymorphisms could contribute to osteoporosis in Chinese postmenopausal women. These preliminary findings provided more evidence that OPG genetic polymorphisms could play genetic effects on BMD and osteoporosis. To the best of our knowledge, this is the first assessment of the influence of OPG g.18873C>T and g.27522G>A genetic polymorphisms with the genetic susceptibility to BMD and osteoporosis. Future replication studies on larger different populations are needed to confirm these findings from this study and to reach more reliable results for assessing the relationship of g.18873C>T and g.27522G>A or other genetic polymorphisms with the etiology of osteoporosis.

Conflict of Interests

The authors have no conflict of interests.

Authors’ Contribution

Fei Wang and Yi Cao have contributed equally to this paper.

References

  1. S. R. Cummings, J. L. Kelsey, M. C. Nevitt, and K. J. O'Dowd, “Epidemiology of osteoporosis and osteoporotic fractures,” Epidemiologic Reviews, vol. 7, pp. 178–208, 1985. View at Scopus
  2. B. L. Riggs and L. J. Melton III, “Involutional osteoporosis,” New England Journal of Medicine, vol. 314, no. 26, pp. 1676–1686, 1986. View at Publisher · View at Google Scholar · View at Scopus
  3. J. A. Kanis, L. J. Melton III, C. Christiansen, C. C. Johnston, and N. Khaltaev, “The diagnosis of osteoporosis,” Journal of Bone and Mineral Research, vol. 9, no. 8, pp. 1137–1141, 1994. View at Scopus
  4. L. Geng, Z. Yao, H. Yang, J. Luo, L. Han, and Q. Lu, “Association of CA repeat polymorphism in estrogen receptor beta gene with postmenopausal osteoporosis in Chinese,” Journal of Genetics and Genomics, vol. 34, no. 10, pp. 868–876, 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. “Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis,” The American Journal of Medicine, vol. 94, pp. 646–650, 1993.
  6. M. T. García-Unzueta, J. A. Riancho, M. T. Zarrabeitia et al., “Association of the 163A/G and 1181G/C osteoprotegerin polymorphism with bone mineral density,” Hormone and Metabolic Research, vol. 40, no. 3, pp. 219–224, 2008. View at Publisher · View at Google Scholar · View at Scopus
  7. Y. H. Lee, J.-H. Woo, S. J. Choi, J. D. Ji, and G. G. Song, “Associations between osteoprotegerin polymorphisms and bone mineral density: a meta-analysis,” Molecular Biology Reports, vol. 37, no. 1, pp. 227–234, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. Y. Li, B. Xi, K. Li, and C. Wang, “Association between vitamin D receptor gene polymorphismsand bone mineral density in Chinese women,” Molecular Biology Reports, vol. 39, no. 5, pp. 5709–5717, 2012. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Jurado, X. Nogués, L. Agueda et al., “Polymorphisms and haplotypes across the osteoprotegerin gene associated with bone mineral density and osteoporotic fractures,” Osteoporosis International, vol. 21, no. 2, pp. 287–296, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. H. Ohmori, Y. Makita, M. Funamizu et al., “Linkage and association analyses of the osteoprotegerin gene locus with human osteoporosis,” Journal of Human Genetics, vol. 47, no. 8, pp. 400–406, 2002. View at Publisher · View at Google Scholar · View at Scopus
  11. O. M. E. Albagha and S. H. Ralston, “Genetics and Osteoporosis,” Rheumatic Disease Clinics of North America, vol. 32, no. 4, pp. 659–680, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. T. Hosoi, “Genetic aspects of osteoporosis,” Journal of Bone and Mineral Metabolism, vol. 28, no. 6, pp. 601–607, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. S. H. Ralston, “Genetics of osteoporosis,” Annals of the New York Academy of Sciences, vol. 1192, pp. 181–189, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. S. Ferrari, “Human genetics of osteoporosis,” Best Practice & Research Clinical Endocrinology & Metabolism, vol. 22, pp. 723–735, 2008.
  15. C.-L. Cheung, S.-M. Xiao, and A. W. C. Kung, “Genetic epidemiology of age-related osteoporosis and its clinical applications,” Nature Reviews Rheumatology, vol. 6, no. 9, pp. 507–517, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. H.-Y. Zhao, J.-M. Liu, G. Ning et al., “The influence of Lys3Asn polymorphism in the osteoprotegerin gene on bone mineral density in Chinese postmenopausal women,” Osteoporosis International, vol. 16, no. 12, pp. 1519–1524, 2005. View at Publisher · View at Google Scholar · View at Scopus
  17. N. A. Pocock, J. A. Eisman, J. L. Hopper, M. G. Yeates, P. N. Sambrook, and S. Eberl, “Genetic determinants of bone mass in adults: a twin study,” The Journal of Clinical Investigation, vol. 80, no. 3, pp. 706–710, 1987. View at Publisher · View at Google Scholar · View at Scopus
  18. B. L. Langdahl, M. Carstens, L. Stenkjaer, and E. F. Eriksen, “Polymorphisms in the osteoprotegerin gene are associated with osteoporotic fractures,” Journal of Bone and Mineral Research, vol. 17, no. 7, pp. 1245–1255, 2002. View at Publisher · View at Google Scholar · View at Scopus
  19. B. Arko, J. Preželj, A. Kocijančič, R. Komel, and J. Marc, “Association of the osteoprotegerin gene polymorphisms with bone mineral density in postmenopausal women,” Maturitas, vol. 51, no. 3, pp. 270–279, 2005. View at Publisher · View at Google Scholar · View at Scopus
  20. Y. Yamada, F. Ando, N. Niino, and H. Shimokata, “Association of polymorphisms of the osteoprotegerin gene with bone mineral density in Japanese women but not men,” Molecular Genetics and Metabolism, vol. 80, no. 3, pp. 344–349, 2003. View at Publisher · View at Google Scholar · View at Scopus
  21. C. Vidal, R. Formosa, and A. Xuereb-Anastasi, “Functional polymorphisms within the TNFRSF11B (osteoprotegerin) gene increase the risk for low bone mineral density,” Journal of Molecular Endocrinology, vol. 47, no. 3, pp. 327–333, 2011. View at Publisher · View at Google Scholar · View at Scopus
  22. B. Arko, J. Preelj, R. Komel, A. Kocijani, P. Hudler, and J. Marc, “Sequence variations in the osteoprotegerin gene promoter in patients with postmenopausal osteoporosis,” Journal of Clinical Endocrinology and Metabolism, vol. 87, no. 9, pp. 4080–4084, 2002. View at Publisher · View at Google Scholar · View at Scopus
  23. L. C. Hofbauer and M. Schoppet, “Osteoprotegerin gene polymorphism and the risk of osteoporosis and vascular disease,” Journal of Clinical Endocrinology and Metabolism, vol. 87, no. 9, pp. 4078–4079, 2002. View at Publisher · View at Google Scholar · View at Scopus
  24. Y. M. Hussien, A. Shehata, R. A. Karam, S. S. Alzahrani, H. Magdy, and A. M. El-Shafey, “Polymorphism in vitamin D receptor and osteoprotegerin genes in Egyptian rheumatoid arthritis patients with and without osteoporosis,” Molecular Biology Reports, vol. 40, no. 5, pp. 3675–3680, 2013. View at Publisher · View at Google Scholar · View at Scopus
  25. L. Paternoster, C. Ohlsson, A. Sayers et al., “OPG and RANK polymorphisms are both associated with cortical bone mineral density: findings from a metaanalysis of the avon longitudinal study of parents and children and Gothenburg osteoporosis and obesity determinants cohorts,” The Journal of Clinical Endocrinology and Metabolism, vol. 95, no. 8, pp. 3940–3948, 2010. View at Publisher · View at Google Scholar · View at Scopus
  26. S. P. Moffett, J. I. Oakley, J. A. Cauley et al., “Osteoprotegerin Lys3Asn polymorphism and the risk of fracture in older women,” Journal of Clinical Endocrinology and Metabolism, vol. 93, no. 5, pp. 2002–2008, 2008. View at Publisher · View at Google Scholar · View at Scopus
  27. J. G. Kim, J. H. Kim, J. Y. Kim et al., “Association between osteoprotegerin (OPG), receptor activator of nuclear factor-κB (RANK), and RANK ligand (RANKL) gene polymorphisms and circulating OPG, soluble RANKL levels, and bone mineral density in Korean postmenopausal women,” Menopause, vol. 14, no. 5, pp. 913–918, 2007. View at Publisher · View at Google Scholar · View at Scopus
  28. T. Ueland, J. Bollerslev, S. G. Wilson et al., “No associations between OPG gene polymorphisms or serum levels and measures of osteoporosis in elderly Australian women,” Bone, vol. 40, no. 1, pp. 175–181, 2007. View at Publisher · View at Google Scholar · View at Scopus
  29. H. L. Jørgensen, P. Kusk, B. Madsen, M. Fenger, and J. B. Lauritzen, “Serum osteoprotegerin (OPG) and the A163G polymorphism in the OPG promoter region are related to peripheral measures of bone mass and fracture odds ratios,” Journal of Bone and Mineral Metabolism, vol. 22, no. 2, pp. 132–138, 2004. View at Publisher · View at Google Scholar · View at Scopus
  30. L. Shen, Y. Qiu, S. Xing et al., “Association between osteoprotegerin genetic variants and bone mineral density in Chinese women,” International Immunopharmacology, vol. 16, no. 2, pp. 275–278, 2013. View at Publisher · View at Google Scholar · View at Scopus
  31. F. Yu, X. Huang, J. Miao, L. Guo, and D. Tao, “Association between osteoprotegerin genetic variants and osteoporosis in Chinese postmenopausal women,” Endocrine Journal, vol. 60, no. 12, pp. 1303–1307, 2013. View at Publisher · View at Google Scholar · View at Scopus
  32. Q. Wang, Z. Chen, Y. Huang et al., “The relationship between osteoprotegerin gene polymorphisms and bone mineral density in Chinese postmenopausal women,” International Immunopharmacology, vol. 17, no. 2, pp. 404–407, 2013. View at Publisher · View at Google Scholar · View at Scopus
  33. P. Tothill, M. A. Laskey, C. I. Orphanidou, and M. van Wijk, “Anomalies in dual energy X-ray absorptiometry measurements of total-body bone mineral during weight change using Lunar, Hologic and Norland instruments,” British Journal of Radiology, vol. 72, pp. 661–669, 1999. View at Publisher · View at Google Scholar · View at Scopus
  34. A. Haliassos, J. C. Chomel, L. Tesson et al., “Modification of enzymatically amplified DNA for the detection of point mutations,” Nucleic Acids Research, vol. 17, no. 9, p. 3606, 1989. View at Publisher · View at Google Scholar · View at Scopus
  35. Z. Yuan, J. Li, X. Gao, and S. Xu, “SNPs identification and its correlation analysis with milk somatic cell score in bovine MBL1 gene,” Molecular Biology Reports, vol. 40, no. 1, pp. 7–12, 2013. View at Publisher · View at Google Scholar · View at Scopus
  36. Z. Yuan, J. Li, L. Zhang, X. Gao, H. J. Gao, and S. Xu, “Investigation on BRCA1 SNPs and its effects on mastitis in Chinese commercial cattle,” Gene, vol. 505, no. 1, pp. 190–194, 2012. View at Publisher · View at Google Scholar · View at Scopus
  37. Z. R. Yuan, J. Y. Li, X. Gao, H. Gao, and S. Z. Xu, “Effects of DGAT1 gene on meat and carcass fatness quality in Chinese commercial cattle,” Molecular Biology Reports, vol. 40, no. 2, pp. 1947–1954, 2013. View at Publisher · View at Google Scholar · View at Scopus
  38. C. J. Zhao, N. Li, and X. M. Deng, “The establishment of method for identifying SNP genotype by CRS-PCR,” Yi Chuan = Hereditas/Zhongguo Yi Chuan Xue Hui Bian Ji, vol. 25, pp. 327–329, 2003.