Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2009 Jun 19.
Published in final edited form as: Calcif Tissue Int. 2008 Sep 12;83(3):155–166. doi: 10.1007/s00223-008-9165-y

Genetic Variation in Candidate Osteoporosis Genes, Bone Mineral Density, and Fracture Risk: The Study of Osteoporotic Fractures

Gregory J Tranah 1,2,✉, Brent C Taylor 3,4, Li-Yung Lui 1, Joseph M Zmuda 5, Jane A Cauley 5, Kristine E Ensrud 3,4,6, Teresa A Hillier 7, Marc C Hochberg 8, Jia Li 9, Brian K Rhees 9, Henry A Erlich 9, Mark D Sternlicht 10, Gary Peltz 11, Steven R Cummings 1,12, For the Study of Osteoporotic Fractures (SOF) Research Group San Francisco, CA, USA
PMCID: PMC2699257  NIHMSID: NIHMS120058  PMID: 18787887

Abstract

Candidate osteoporosis gene variants were examined for associations with fracture risk and bone mineral density (BMD). A total of 9704 white women were recruited at four U.S. clinical centers and enrolled into the Study of Osteoporotic Fractures, a longitudinal cohort study. Genotyping of 31 polymorphisms from 18 candidate osteoporosis genes was performed in 6752 women. Incident radiographic fractures were identified at the third and eighth examinations compared with the baseline examination. BMD was measured at the total hip by dual-energy X-ray absorptiometry. Analyses were adjusted for age, clinic site, and self-reported ethnicity. During a mean follow-up of 14.5 years, a total of 849 hip, 658 vertebral, and 2496 nonhip/nonvertebral fractures occurred in 6752 women. Women carrying the ALOX15_G48924T T/T genotype had a higher rate of hip fracture (hazard ratio [HR] = 1.33;95% confidence interval [95% CI] = 1.00–1.77) compared with the G/G genotype. Compared with those carrying the PRL_T228C T/T genotype, women with either the C/C (HR = 0.80; 95% CI = 0.67–0.95) or C/T (HR = 0.81; 95% CI = 0.68–0.97) genotype had a lower rate of nonvertebral/nonhip fractures. Women carrying theBMP2_A125611G G/G genotype had a higher rate of vertebral fracture (odds ratio [OR] = 1.51; 95% CI = 1.03–2.23) compared with the A/A genotype. Women with the ESR1_C1335G G/G genotype had a higher rate of vertebral fracture (OR = 1.64; 95% CI = 1.07–2.50) compared with the C/C genotype. Compared with those with the MMP2_C595T C/C genotype, women with the C/T (OR = 0.79; 95% CI = 0.65–0.96) or T/T (OR = 0.44; 95% CI = 0.27–0.72) genotype had a lower rate of vertebral fracture. In conclusion, polymorphisms in several candidate genes were associated with hip, vertebral, and nonhip/nonvertebral fractures but not with total hip BMD in this large population based cohort study.

Keywords: Genetics, Polymorphism, Osteoporosis, BMD, Fracture

Osteoporosis is a disorder characterized by low bone mass and increased risk of fracture. Many factors influence the risk of osteoporosis, including diet, physical activity, medication use, coexisting diseases, and a family history of the disorder. Research into the genetic basis of osteoporosis has been motivated by evidence that bone traits tend to be highly heritable. Whereas genetic factors explain 50% to 80% [1–4] of the biological variation in bone density and other bone phenotypes, these factors are not sufficient to explain fracture risk [5]. Deng et al. [5] report that the genetic correlation between bone density and fracture is not significant and that most genes found to be relevant to bone density may not be important for hip fracture.

Osteoporosis, like other genetically complex diseases, is the product of multiple genetic and environmental factors, and their interactions [6, 7]. To date, several approaches have been attempted to identify osteoporosis-related genes, among them linkage analysis in families and candidate gene association analysis in populations and case–control collections. Genes hypothesized to play a role in osteoporosis include those involved in bone formation and remodeling (e.g., LRP5), those involved in hormone signaling (e.g., VDR and ESR1), and those that code for bone-structure proteins (e.g., COL1A1). However, many of the reported allelic associations with osteoporosis have not been replicated when tested in other cohorts. The inconsistent results may be due in part to the lack of statistical power to detect subtle genetic effects and the different approaches for identifying genes and gene variants as well as differences in study design. In addition, the preference for reporting positive associations and for underreporting of negative results may introduce bias in the genetic epidemiology literature [8].

DNA samples from individuals in the Study of Osteoporotic Fractures (SOF) cohort have been used to evaluate the relationship between allelic variants in several candidate genes and osteoporosis risk. SOF is a multicenter cohort study that was initiated in 1986 to determine risk factors for osteoporotic fractures in elderly women [9]. As a source of DNA samples for an osteoporosis genetic marker screen, SOF has many advantages. Of the approximately 7000 prospectively recruited white women who provided samples with adequate consent for participation in genetic studies, over 800 have had incident hip fractures, over 600 have had incident vertebral fractures, and virtually all had bone mineral density (BMD) measurements at the hip. As such, SOF is the largest and best-characterized U.S. cohort available for studying the genetics of osteoporosis in primarily white women of European ancestry. Associations between allelic variants within the VDR [10, 11], IL6 [12], TNFα [13], NOS3 [14], and OPG [15] genes and fracture risk or BMD have been reported in SOF. Here, we present the results of a genetic association study covering 31 polymorphisms in 18 candidate genes that was performed with the SOF cohort to identify genetic risk factors for osteoporosis.

Materials and Methods

Subjects

SOF is a longitudinal epidemiologic study of 9704 women aged 65–99 (mean 71.7, standard deviation 5.3) years recruited from four study centers located in Baltimore, Maryland; Minneapolis, Minnesota; Portland, Oregon; and the Monongahela Valley near Pittsburgh, Pennsylvania. The baseline SOF examinations were conducted from 1986 to 1988 [16]. SOF was originally designed to investigate risk factors for osteoporosis and osteoporotic fractures. Black women were initially excluded from SOF because of their low risk of fractures [17]. Also excluded were women with bilateral hip replacement or those unable to walk without assistance. All participants were community dwellers at baseline. Since then, follow-up examinations have taken place approximately every 2 years. The institutional review boards on human research approved the study at each institution, and all the women provided written informed consent.

Genotyping

Buffy coat or whole blood specimens were collected from a total of 6975 participants at either visit 2 (1989–1990) or visit 6 (1997–1998). In collaboration with Roche Molecular Sciences, the SOF DNA was purified, assayed, stored, and cataloged. The present analysis was completed by using DNA extracted from either buffy coat or whole blood samples. Among the 6975 participants who provided samples, genotyping was performed in 6752 women who provided adequate consent for participation in genetic studies and had sufficient DNA available. Genotyping of the 31 polymorphisms in 18 genes (Table 1) was performed by Roche Molecular Systems (RMS) in Alameda, California, in 2004–2005. Candidate osteoporosis genes were selected at the time on the basis of the hypotheses that they were involved in bone formation and remodeling; that they were involved in hormone signaling; or that they encoded bone-structure proteins. We selected single nucleotide polymorphisms (SNPs) that were available at the time we initiated the project on the basis of potential function or previous publication in association studies of osteoporosis. Not all candidate SNPs were compatible with the genotyping platform, and we report results for those that were successfully genotyped.

Table 1.

Candidate genes and polymorphisms

Gene SNP position RS no. Gene name OMIM accession no.
ALOX15 G48924T rs7220870 ARACHIDONATE 15-LIPOXYGENASE 152392*
G49010C rs2664593
C51425T rs11078528
A57901G rs743646
BMP2 C117863T rs1980499 BONE MORPHOGENETIC PROTEIN 2 112261*
A125611G rs235764
G149529A rs235739
C167584T rs996544
CALCR C1654T rs1801197 CALCITONIN RECEPTOR 114131*
CASR C3403G rs1801726 CALCIUM-SENSING RECEPTOR 601199*
CBFA1 A529 Ga NA CORE BINDING FACTOR 1 600211*
COL1A1 G296T rs1107946 COLLAGEN, TYPE I, ALPHA-1 120150*
G2046T rs1800012
COMT G1947A rs4680 CATECHOL-O-METHYLTRANSFERASE 116790*
CYP1A1 A6570G rs1048943 CYTOCHROME P450, SUBFAMILY I, POLYPEPTIDE 1 108330*
ESR1 T938C rs2234693 ESTROGEN RECEPTOR 1 133430*
A984G rs9340799
C1335G rs1801132
FRZB1 A757G rs9288087 FRIZZLED-RELATED PROTEIN 605083*
G19524A rs2242070
C26794G rs7775
GSTP A2627G rs1695 GLUTATHIONE S-TRANSFERASE, PI 134660*
LRP5 G1980A rs2277268 LOW DENSITY LIPOPROTEIN RECEPTOR-RELATED PROTEIN 5 603506*
MMP1 135792 (–/G) rs1799750 MATRIX METALLOPROTEINASE 1 120353*
MMP2 C595T rs243865 MATRIX METALLOPROTEINASE 2 120360*
A1829G rs2287074
MMP13 A326G rs2252070 MATRIX METALLOPROTEINASE 13 600108*
MTHFR C677T rs1801133 5,10-METHYLENETETRAHYDROFOLATE REDUCTASE 607093*
PPAR C34G rs1801282 PEROXISOME PROLIFERATOR-ACTIVATED RECEPTOR, GAMMA 601487*
PRL T228C rs7739889 PROLACTIN 176760*
G1627T rs1341239
Open in a new tab

NA, not available

a

CBFA1_A529G probes target an A/G variant at base 929 in NM_004348.3

The candidate gene polymorphisms were genotyped in the context of a multiplex polymerase chain reaction (PCR) amplification followed by allele-specific SNP detection with immobilized oligonucleotide probes in linear arrays, as previously described [18]. Primers were modified at the 5′ phosphate by conjugation with biotin. A total of 10 to 50 ng of purified human genomic DNA was amplified in a reaction volume of 50 μL with AmpliTaq Gold DNA polymerase with a GeneAmp PCR System 9600 thermal cycler (PE Biosystems, Foster City, CA) with the following cycling profile: an initial hold at 94°C for 7 minutes, then 33 two-step amplification cycles of 15 seconds at 95°C for denaturation and 60 seconds at 60°C for annealing/extension, and a final 5-minute product extension step at 68°C. Chromogenic detection of allelic variants following stringent hybridization of the biotinylated PCR products to the immobilized sequence-specific probes was performed on a Profiblot II T24 (Tecan, Research Triangle Park, NC). Roche Molecular Sciences in-house software was used to scan the linear arrays on an Epson Perfection 1670 scanner (Epson, Long Beach, CA) and to assign genotypes.

Fracture Ascertainment

Details of the method for identifying fractures have been previously published [19–21]. Briefly, participants were contacted every 4 months by postcard or telephone to ask whether they had experienced a fracture. More than 95% of these contracts were completed. All fractures are adjudicated by radiographic report, and a detailed description of the implementation and accuracy of SOF fracture data has been previously reported [22]. Fractures that occurred because of major trauma such as motor vehicle accidents were excluded. Vertebral fractures were defined by morphometry by lateral spine radiography collected at the first, third, and eighth clinic examinations. Incident radiographic fractures were identified on follow-up radiographs at the third and eighth examinations compared with the baseline examination. Sample sizes for incident vertebral fractures are lower than for other fractures as a result of deaths, terminations, and loss to follow-up between examinations 3 and 8. All nonvertebral and nonhip fractures were analyzed as a group, and hip and vertebral fractures were analyzed separately.

Bone Density Measurements

Hip BMD were measured by dual-energy X-ray absorptiometry (QDR 1000; Hologic, Bedford, MA) at the second visit. Details of these methods and quality control procedures have been reported elsewhere [23–25]. Details of the densitometry and quality control methods utilized in SOF have been outlined elsewhere [24, 26–28].

Statistical Analysis

Hardy-Weinberg equilibrium of the candidate gene polymorphisms was assessed by the χ2 goodness-of-fit statistic. We analyzed BMD by genotype with analysis of variance. To determine the relationship between genotype and the incidence of hip and nonspine, nonhip fractures, we used Cox proportional hazard models to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs). Logistic regression was used to estimate odds ratios (ORs) and 95% CIs to determine the relationship between genotype and risk of vertebral fracture. The wild-type genotype served as the referent group in these analyses. All analyses were adjusted for age, clinic site, and self-reported ethnicity (northern, central, and southern European). The Bonferroni method was used to calculate the corrected P values for multiple testing. Statistical analysis was performed with the statistical software program SAS version 9.1 (SAS Institute, Cary, NC).

Results

HRs and ORs for the polymorphisms within selected candidate genes are listed in Table 2, and all genotypes were in Hardy-Weinberg equilibrium. Five SNPs showed a nominal association with some form of fracture, although no SNPs reached statistical significance after adjusting for multiple testing by the Bonferroni correction with α = 0.0004. The CBFA1_A529G polymorphism was monomorphic for the A/A genotype in this population.

Table 2.

Associations with fractures and total hip bone mineral densitya

Gene/polymorphism Hip fracture HR (95% CI) Nonvertebral, nonhip fracture HR (95% CI) Vertebral fracture OR (95% CI) Total hip BMD (g/cm2) Mean (95% CI)
Total no. 6575 6068 2475 6515
No. of fractures 849 2496 658
ALOX15_G48924T GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
GT 1.03 (0.9–1.19) 1.02 (0.93–1.11) 1.01 (0.83–1.24) 0.76 (0.76–0.77)
TT 1.33 (1.00–1.77) 1.02 (0.84–1.23) 0.78 (0.49–1.25) 0.75 (0.74–0.77)
ALOX15_G49010C GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
GC 1.06 (0.92–1.23) 1.00 (0.92–1.09) 0.91 (0.75–1.12) 0.76 (0.76–0.77)
CC 1.25 (0.93–1.68) 0.98 (0.81–1.19) 0.72 (0.44–1.17) 0.75 (0.74–0.77)
ALOX15_C51425T CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
CT 1.06 (0.92–1.22) 0.94 (0.86–1.02) 0.92 (0.75–1.13) 0.76 (0.76–0.76)
TT 0.92 (0.70–1.19) 1.00 (0.86–1.16) 0.98 (0.69–1.39) 0.76 (0.75–0.77)
ALOX15_A57901G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
AG 1.10 (0.93–1.29) 1.01 (0.91–1.11) 0.93 (0.73–1.17) 0.76 (0.76–0.77)
GG 0.62 (0.29–1.31) 0.93 (0.65–1.34) 0.62 (0.23–1.66) 0.76 (0.74–0.79)
BMP2_C117863T CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.77)
CT 0.84 (0.71–0.98) 0.98 (0.89–1.08) 1.05 (0.83–1.33) 0.76 (0.75–0.76)
TT 0.78 (0.65–0.94) 0.96 (0.86–1.08) 0.91 (0.69–1.20) 0.76 (0.75–0.77)
BMP2_A125611G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.75 (0.74–0.76)
AG 0.78 (0.60–1.00) 0.93 (0.80–1.08) 1.33 (0.90–1.97) 0.76 (0.76–0.77)
GG 0.98 (0.77–1.26) 0.96 (0.83–1.12) 1.51 (1.03–2.23) 0.76 (0.75–0.76)
BMP2_G149529A GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.77)
GA 1.05 (0.84–1.31) 1.01 (0.88–1.15) 0.87 (0.63–1.19) 0.76 (0.75–0.76)
AA 0.93 (0.74–1.17) 0.99 (0.86–1.13) 0.89 (0.65–1.23) 0.76 (0.75–0.76)
BMP2_C167584T CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
CT 0.94 (0.77–1.15) 1.06 (0.94–1.19) 1.03 (0.77–1.37) 0.75 (0.75–0.76)
TT 0.63 (0.20–1.96) 1.15 (0.68–1.95) 2.13 (0.75–6.02) 0.77 (0.73–0.82)
CALCR_C1654T CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.77)
CT 1.05 (0.78–1.42) 1.01 (0.85–1.21) 1.11 (0.73–1.68) 0.76 (0.75–0.76)
TT 1.00 (0.75–1.33) 1.00 (0.84–1.19) 0.93 (0.62–1.40) 0.76 (0.76–0.76)
CASR_C3403G CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
CG 0.85 (0.65–1.10) 0.97 (0.83–1.12) 1.12 (0.79–1.60) 0.76 (0.75–0.77)
GG 0.31 (0.04–2.19) 1.53 (0.87–2.70) 1.38 (0.32–5.91) 0.75 (0.7–0.8)
COL1A1_G296T GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
GT 0.91 (0.77–1.07) 0.98 (0.89–1.07) 1.07 (0.85–1.33) 0.76 (0.75–0.76)
TT 0.98 (0.63–1.53) 0.90 (0.67–1.21) 1.56 (0.82–2.97) 0.76 (0.74–0.78)
COL1A1_G2046T GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
GT 1.07 (0.93–1.24) 1.05 (0.96–1.14) 1.09 (0.89–1.34) 0.76 (0.75–0.76)
TT 1.03 (0.71–1.51) 1.15 (0.93–1.42) 0.94 (0.56–1.58) 0.76 (0.74–0.77)
COMT_G1947A GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.77)
GA 1.26 (1.05–1.51) 1.00 (0.9–1.11) 1.18 (0.92–1.52) 0.76 (0.75–0.76)
AA 1.17 (0.96–1.44) 0.98 (0.87–1.10) 1.09 (0.83–1.44) 0.76 (0.75–0.77)
CYP1A1_A6570G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
AG 0.91 (0.68–1.22) 1.02 (0.87–1.21) 0.97 (0.65–1.44) 0.75 (0.74–0.77)
GG 1.40 (0.58–3.38) 0.76 (0.36–1.59) 1.42 (0.26–7.92) 0.79 (0.75–0.84)
ESR1_T938C TT 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
TC 1.00 (0.85–1.17) 1.01 (0.92–1.11) 1.18 (0.94–1.48) 0.76 (0.76–0.76)
CC 0.96 (0.79–1.17) 0.93 (0.83–1.05) 1.11 (0.84–1.46) 0.76 (0.75–0.77)
ESR1_A984G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
AG 1.14 (0.99–1.32) 0.93 (0.86–1.02) 1.21 (0.99–1.48) 0.76 (0.75–0.76)
GG 1.01 (0.80–1.26) 0.91 (0.79–1.04) 1.10 (0.80–1.51) 0.76 (0.75–0.77)
ESR1_C1335G CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
CG 0.93 (0.81–1.08) 1.00 (0.91–1.09) 1.16 (0.95–1.42) 0.76 (0.75–0.76)
GG 1.23 (0.91–1.64) 1.06 (0.88–1.28) 1.64 (1.07–2.50) 0.77 (0.76–0.79)
FRZB1_A–757G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.77)
AG 0.89 (0.66–1.20) 0.92 (0.77–1.11) 0.74 (0.5–1.09) 0.76 (0.76–0.77)
GG 0.94 (0.71–1.26) 1.01 (0.84–1.20) 0.70 (0.48–1.03) 0.76 (0.75–0.76)
FRZB1_G19524A GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
GA 0.96 (0.83–1.11) 0.95 (0.87–1.03) 1.13 (0.92–1.38) 0.76 (0.76–0.77)
AA 1.01 (0.76–1.35) 0.97 (0.82–1.16) 1.44 (0.99–2.09) 0.76 (0.75–0.77)
FRZB1_C26794G CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
CG 0.95 (0.78–1.15) 0.96 (0.86–1.07) 0.79 (0.60–1.04) 0.76 (0.75–0.77)
GG 1.05 (0.44–2.54) 0.98 (0.56–1.73) 1.78 (0.48–6.52) 0.74 (0.7–0.78)
GSTP_A2627G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
AG 0.92 (0.80–1.07) 0.96 (0.88–1.04) 0.96 (0.78–1.17) 0.76 (0.76–0.76)
GG 0.89 (0.71–1.12) 1.04 (0.91–1.19) 1.05 (0.77–1.43) 0.76 (0.75–0.77)
LRP5_G1980A GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.76)
GA 1.05 (0.86–1.28) 1.07 (0.95–1.21) 1.17 (0.87–1.56) 0.76 (0.75–0.76)
AA 0.69 (0.22–2.14) 0.98 (0.54–1.78) 2.04 (0.53–7.96) 0.76 (0.71–0.8)
MMP1_135792 (–/G) 1G/1G 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
1G/2G 0.94 (0.80–1.10) 0.99 (0.9–1.09) 1.02 (0.82–1.28) 0.76 (0.76–0.77)
2G/2G 1.03 (0.85–1.25) 1.03 (0.92–1.15) 1.25 (0.96–1.64) 0.76 (0.75–0.76)
MMP2_C595T CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
CT 0.98 (0.85–1.14) 1.00 (0.92–1.09) 0.79 (0.65–0.96) 0.76 (0.76–0.77)
TT 1.20 (0.92–1.56) 0.89 (0.74–1.07) 0.44 (0.27–0.72) 0.76 (0.75–0.78)
MMP2_A1829G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.77)
AG 0.92 (0.77–1.10) 1.02 (0.92–1.14) 1.21 (0.94–1.57) 0.76 (0.75–0.76)
GG 0.93 (0.77–1.13) 1.04 (0.93–1.17) 1.24 (0.94–1.64) 0.76 (0.75–0.76)
MMP13_A326G AA 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.77)
AG 1.01 (0.87–1.17) 1.05 (0.96–1.14) 1.16 (0.95–1.41) 0.76 (0.75–0.76)
GG 1.21 (0.97–1.50) 1.07 (0.93–1.22) 0.87 (0.62–1.22) 0.75 (0.74–0.76)
MTHFR_C677T CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.76–0.77)
CT 0.96 (0.83–1.11) 1.00 (0.92–1.09) 0.97 (0.80–1.19) 0.76 (0.75–0.76)
TT 1.09 (0.88–1.36) 1.07 (0.94–1.22) 0.94 (0.68–1.29) 0.75 (0.75–0.76)
PPARc_C34G CC 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
CG 0.80 (0.67–0.95) 1.06 (0.97–1.17) 0.82 (0.66–1.04) 0.76 (0.76–0.77)
GG 1.21 (0.75–1.97) 1.29 (0.97–1.73) 0.92 (0.44–1.92) 0.76 (0.73–0.78)
PRL_T228C TT 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.75 (0.74–0.77)
TC 0.85 (0.63–1.15) 0.81 (0.68–0.97) 0.74 (0.48–1.15) 0.76 (0.76–0.77)
CC 0.87 (0.65–1.16) 0.80 (0.67–0.95) 0.78 (0.51–1.19) 0.76 (0.75–0.76)
PRL_G1627T GG 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 0.76 (0.75–0.76)
GT 0.89 (0.77–1.03) 1.03 (0.94–1.13) 0.84 (0.68–1.03) 0.76 (0.76–0.76)
TT 0.99 (0.81–1.21) 1.10 (0.97–1.24) 1.10 (0.83–1.46) 0.76 (0.75–0.76)
Open in a new tab

BMD, bone mineral density; HR, hazard ratio; 95% CI, 98% confidence interval

a

All analyses adjusted for age, clinic site, and self-reported ethnicity (northern, central, and southern European) Bold values are statistically significant results

Hip Fracture

During a mean follow-up of 14.5 years, a total of 849 hip fractures occurred among the approximately 6600 women with no history of hip fracture. Women with the ALOX15_G48924T T/T genotype had a 33% higher rate of hip fracture, compared with women with the G/G genotype (HR = 1.33; 95% CI = 1.00–1.77).

Nonvertebral and Nonhip Fracture

During the same 14.5-year follow-up, a total of 2496 nonvertebral and nonhip fractures occurred among approximately 6000 women. Compared with women carrying the PRL_T228C T/T genotype, women with either the C/C genotype (HR = 0.80; 95% CI = 0.67–0.95) or the C/T genotype (HR = 0.81; 95% CI = 0.68–0.97) had an approximately 20% lower rate of nonvertebral and nonhip fractures.

Incident Radiographic Vertebral Fracture

A total of 658 incident vertebral fractures occurred among the approximately 2500 women who had undergone assessment at visits 3 or 8. Women with the BMP2_A125611G G/G genotype had a 51% higher rate of vertebral fracture, compared with women with the A/A genotype (OR = 1.51; 95% CI = 1.03–2.23). Women with the ESR1_C1335G G/G genotype had a 64% higher rate of vertebral fracture compared with women with the C/C genotype (OR = 1.64; 95% CI = 1.07–2.50). Women with the MMP2_C595T C/T genotype had a 21% lower rate of vertebral fracture (OR = 0.79; 95% CI = 0.65–0.96) compared with women with the C/C genotype, while women with the T/T genotype had a 56% lower rate of vertebral fracture (OR = 0.44; 95% CI = 0.27–0.72).

From the approximately 6500 participants who had a total hip BMD measurement, there was no significant association between the previously unreported candidate genes and total hip BMD (Table 2). For example, the strongest association with BMD was found for the CYP1A1_A6570G polymorphism (Table 2). The CYP1A1_A6570G A/A and G/G genotypes were associated with mean BMD measures of 0.76 g/cm2 (95% CI = 0.76–0.76 g/cm2) and 0.79 g/cm2 (95% CI = 0.75–0.84 g/cm2), respectively.

Discussion

We analyzed 31 polymorphisms in 18 candidate genes within the SOF cohort to identify genetic risk factors for osteoporosis. It was of particular interest that women with the ALOX15_G48924T T/T genotype had a 33% higher rate of hip fracture in this study. This polymorphism was the only one with an allelic association with hip fracture in this study. ALOX15 and ALOX12 are contiguous genes located within the 17p13 region of the human genome, which contains a quantitative trait locus that affects BMD in the hip, spine [29], and wrist [30]. However, previous studies have found inconsistent associations between SNPs in ALOX15 and BMD or fracture data [31–34]. The ALOX15_G48924T SNP is located within the 5′ flanking region (−272 bp) of ALOX15. This polymorphism is of interest because a C-to-T substitution at ALOX15 position −292 was shown to create a novel transcription factor binding site for SPI1 [35]. SPI1 selectively binds to the −292 T allele, and transcription assays in primary human macrophages showed that −292 C/T heterozygous individuals expressed three times more ALOX15 mRNA than −292 C/C individuals [35]. Higher ALOX15 mRNA levels were also observed in monocytes from heterozygous −292 C/T carriers [36]. The ALOX15_G48924T SNP (G-272T) examined herein may be in linkage disequilibrium with the functional C-292T polymorphism, leading to differential ALOX15 expression and increased risk of fracture for the variant allele. Alternately, G-272T may itself be functional. Consistent with our findings in the female SOF cohort, there were significant associations between SNPs within the 5′ flanking region of ALOX15 and BMD in Japanese women in two different studies [32–34]. By contrast, two studies did not observe associations between 5′-flanking ALOX15 SNPs and BMD in Chinese women [33] or BMD and fracture in postmenopausal white women [31]. Taken together, the results of genetic association studies performed in this and two other female populations indicate that genetic variation within the 5′ promoter region of ALOX15 may contribute to osteoporosis-related traits. Measuring associations between 5′-flanking ALOX15 SNPs and BMD and fracture in emerging genome-wide association study data sets may help confirm these associations.

Prolactin is a peptide hormone that when present at high levels is associated with decreased levels of estrogen and testosterone. Prolactin may also have direct effects on osteoblast function and bone formation [37–39]. In this study, women carrying one or two copies of the PRL_T228C C allele had a ~20% lower rate of nonvertebral and nonhip fractures. The function of the intronic T228C polymorphisms is currently unknown. High prolactin levels have been associated with osteopenia, decreased bone density, and increased osteoporosis risk, possibly as a result of a reduction in estrogen levels [40, 41]. In addition, long-term administration of raloxifene, which has been shown to decrease fracture risk in postmenopausal women with osteoporosis, decreases serum prolactin levels [42].

Bone morphogenetic protein 2 is a growth factor belonging to the transforming growth factor beta super-family that plays a role in osteoblast differentiation. The gene for bone morphogenetic protein 2 (BMP2) was identified as an osteoporosis candidate locus by genome-wide linkage mapping in human populations [43]. To date, two BMP2 SNPs have been associated with fracture [43] and BMD [44]; however, the associations are not consistent [43, 45]. In the present study, women with the intronic BMP2_A125611G G/G genotype had a 51% higher risk of vertebral fracture. The function of the BMP2_A125611G polymorphism is unknown, and it is possible that this SNP is functional or in linkage disequilibrium with a functional variant.

MMP-2 is a determinant of bone remodeling and mineralization and plays a crucial role in forming and maintaining the osteocytic canalicular network [46]. Serum concentrations of MMP-2 have been related to markers of bone turnover including bone alkaline phosphatase, osteocalcin, and cross-linked N-telopeptides of type I collagen [47]. A previous study also found that serumMMP-2 levels may also increase with increasing bone turnover [48]. In the present study, women with one copy of the MMP2_C595T T allele (located in the 5′ promoter at position −1586) had a 21% lower adjusted rate of vertebral fracture, and women with two copies had a 56% lower adjusted rate.

Several studies have investigated the association between estrogen receptor alpha (ESR1) gene variants and osteoporosis [49–51]. In the present study, neither the PvuII (rs2234693) nor the XbaI (rs9340799) polymorphisms were associated with hip or nonvertebral/nonhip fracture risk. Women with the ESR1_C1335G G/G genotype had a 64% higher rate of vertebral fracture, compared with women with the C/C genotype. The ESR1_C1335G variant codes for a synonymous P325P substitution in exon 4. A previous study of late postmenopausal women found that mean femoral neck BMD, but not lumbar spine BMD, was significantly lower in the homozygous G/G women compared with the homozygous C/C women [52]. Another study found that after 6 months of treatment with raloxifene, subjects with C/C or C/G genotype of P325P mutation had significantly lower total cholesterol and low-density lipoprotein cholesterol concentrations, and higher decreases of total cholesterol when compared with those with the G/G genotype [53]. Our results and those of Jurada et al. [52] suggest that the codon 325 G/G genotype is associated with increased risk of vertebral fracture and lower femoral neck BMD.

There were no significant genetic associations with total hip BMD. The strongest association with BMD was found for the CYP1A1_A6570G polymorphism with a 4%increase in BMD for the G/G genotype compared with the A/A genotype. The inconsistency of genetic associations with fracture andBMDand across fracture types is consistent with studies in mice, which indicate that there are skeletal-site-specific genetic loci for bone mass and strength [54–57]. Previous findings have demonstrated that a wide array of skeletal phenotypes were polygenic with complex segregation patterns [57]. Beamer et al. [55] showed that several quantitative trait loci were responsible for both femoral and vertebral measures of BMD, whereas other quantitative trait loci were unique to femurs or vertebrae. Unique genetic factors contributing to trabecular and cortical bone mass have also been identified [54]. Another possibility is that the fracture findings are possibly spurious as a result of the multiple comparisons that were made.

Although this study found several positive genetic associations with osteoporotic outcomes, most of the investigated polymorphisms were not associated with fracture risk or BMD, and none of the previously unreported polymorphisms were consistently significantly associated with multiple fracture types or BMD sites. Previously reported associations between polymorphisms in COL1A1 [58–64], LRP5 [65–71], CASR [72], CALCR [73], and MTHFR [74–81] andBMDor fracture were not replicated in this study. Inconsistencies between this and previous studies may be due in part to differences in study size, specific SNPs assayed, sex-specific effects, ethnic background, and menopausal status, all of which influence genetic associations with BMD and fracture risk. Several previous studies [58–61, 66, 67, 72, 73, 77, 79] had small sample sizes (<300 participants), which may have led to spurious associations. For several genes, we examined different SNPs than those previously reported [63, 65–67, 73]. Two of the previous studies only found associations in men [65, 67] or premenopausal women [72]. Several studies were conducted on nonwhite participants [67, 68, 76, 79].

This study is limited in making conclusions regarding whether the examined genes play an important role in fracture risk or BMD because of the limited number of polymorphisms per gene studied in this population. Even though the selected polymorphisms based on prior investigation seemed to be promising, no single SNP can explain the variation of an entire gene. Although the SOF cohort is a well-characterized and appropriate cohort to use for osteoporosis- related studies, particularly within the population of elderly white women, results from a single population likely cannot be generalized to all possible populations. Finally, interactions between environmental factors and other genes may have obscured important subgroup associations with the candidate gene polymorphisms.

In the past decades, several approaches have been attempted to identify osteoporosis genes; however, the genes contributing to osteoporosis risk remain poorly defined. As with most complex diseases, it is generally assumed that many gene variants are responsible, with each contributing a subtle effect. Inconsistent results may be due to a lack of statistical power to detect the subtle effects of the responsible gene variants, a lack of standardized methods and approaches to identify the variants, or the selection of the wrong candidate genes. Recently the consortium approach to genetic studies, as exemplified for osteoporosis by the “genetic markers for osteoporosis” (GENOMOS) consortium [51, 64, 69, 82, 83], has remedied some of the most important pitfalls of candidate gene studies by standardizing phenotypes and genotypes, increasing sample sizes, improving power, and reducing false discovery rates. In addition, replication has become well established as the gold standard in genetic association studies to overcome problems with multiple testing and false-positive discoveries. The increasing use of genome-wide screening approaches, which exacerbate the discovery of false-positive findings, requires well-conducted replication studies in a variety of populations to confirm true novel genetic associations and increase generalizability of findings to more than one population. Making genotype data available from phenotypically well-characterized individual studies (such as those reported here) not only provides an opportunity for future confirmation of genome-wide association study results for specific genes, but also contributes to future meta-analyses. In addition, disclosure of negative as well as positive associations is essential to minimize the risk of publication bias. Ioannidis [8, 84] argues that the large majority of molecular epidemiology results should be null and that scientific journals should publish all studies with null results, provided study limitations are acknowledged. Rebbeck et al. [85] provide a framework for prioritizing the publication of reports that are likely to provide more meaningful information about disease etiology.

Acknowledgments

Supported by NIH grants AG05407, AR35582, AG05394, AR35584, AR35583, AR46238, AG005407, AG027576-22, AG005394-22A1, and AG027574-22A1. J. A. Cauley receives funding from Merck & Company, Eli Lily & Company, Pfizer Pharmaceuticals, and Novartis Pharmaceuticals. K. E. Ensrud is a federal employee of the Veterans Affairs Medical Center in Minneapolis, Minnesota, and has received research support from California Pacific Medical Center, who receives funding from Roche Molecular Systems. M. C. Hochberg acts as a consultant for Amgen. J. Li, B. Rhees, and H. Erlich are all employees of Roche Molecular Systems, which provided genotyping reagents and services for this study at no cost under a research collaboration. G. Peltz is a former employee of Roche Palo Alto. S. Cummings, L. Lui, and G. Tranah are employees of the California Pacific Medical Center and receive research support from Roche Molecular Systems.

References

  • 1.Flicker L, Hopper JL, Rodgers L, Kaymakci B, Green RM, Wark JD. Bone density determinants in elderly women: a twin study. J Bone Miner Res. 1995;10:1607–1613. doi: 10.1002/jbmr.5650101102. [DOI] [PubMed] [Google Scholar]
  • 2.Christian JC, Yu PL, Slemenda CW, Johnston CC., Jr Heritability of bone mass: a longitudinal study in aging male twins. Am J Hum Genet. 1989;44:429–433. [PMC free article] [PubMed] [Google Scholar]
  • 3.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. doi: 10.1172/JCI113125. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Eisman JA. Genetics of osteoporosis. EndocrRev. 1999;20:788–804. doi: 10.1210/edrv.20.6.0384. [DOI] [PubMed] [Google Scholar]
  • 5.Deng HW, Mahaney MC, Williams JT, Li J, Conway T, Davies KM, Li JL, Deng H, Recker RR. 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. 2002;22:12–25. doi: 10.1002/gepi.1040. [DOI] [PubMed] [Google Scholar]
  • 6.Ralston SH, de Crombrugghe B. Genetic regulation of bone mass and susceptibility to osteoporosis. Genes Dev. 2006;20:2492–2506. doi: 10.1101/gad.1449506. [DOI] [PubMed] [Google Scholar]
  • 7.Stewart TL, Ralston SH. Role of genetic factors in the pathogenesis of osteoporosis. J Endocrinol. 2000;166:235–245. doi: 10.1677/joe.0.1660235. [DOI] [PubMed] [Google Scholar]
  • 8.Ioannidis JP. Journals should publish all “null” results and should sparingly publish “positive” results. Cancer Epidemiol Biomarkers Prev. 2006;15:186. doi: 10.1158/1055-9965.EPI-05-0921. [DOI] [PubMed] [Google Scholar]
  • 9.Nevitt MC, Cummings SR, Lane NE, Hochberg MC, Scott JC, Pressman AR, Genant HK, Cauley JA. Association of estrogen replacement therapy with the risk of osteoarthritis of the hip in elderly white women. Study of Osteoporotic Fractures Research Group. Arch Intern Med. 1996;156:2073–2080. [PubMed] [Google Scholar]
  • 10.Ensrud KE, Stone K, Cauley JA, White C, Zmuda JM, Nguyen TV, Eisman JA, Cummings SR. Vitamin D receptor gene polymorphisms and the risk of fractures in older women. For the Study of Osteoporotic Fractures Research Group. J Bone Miner Res. 1999;14:1637–1645. doi: 10.1359/jbmr.1999.14.10.1637. [DOI] [PubMed] [Google Scholar]
  • 11.Moffett SP, Zmuda JM, Cauley JA, Ensrud KE, Hillier TA, Hochberg MC, Li J, Cayabyab S, Lee JM, Peltz G, Cummings SR. Association of the VDR translation start site polymorphism and fracture risk in older women. J Bone Miner Res. 2007;22:730–736. doi: 10.1359/jbmr.070201. [DOI] [PubMed] [Google Scholar]
  • 12.Moffett SP, Zmuda JM, Cauley JA, Stone KL, Nevitt MC, Ensrud KE, Hillier TA, Hochberg MC, Joslyn G, Morin P, Cummings SR. Association of the G-174C variant in the interleukin-6 promoter region with bone loss and fracture risk in older women. J Bone Miner Res. 2004;19:1612–1618. doi: 10.1359/JBMR.040707. [DOI] [PubMed] [Google Scholar]
  • 13.Moffett SP, Zmuda JM, Oakley JI, Beck TJ, Cauley JA, Stone KL, Lui LY, Ensrud KE, Hillier TA, Hochberg MC, Morin P, Peltz G, Greene D, Cummings SR. Tumor necrosis factor-alpha polymorphism, bone strength phenotypes, and the risk of fracture in older women. J Clin Endocrinol Metab. 2005;90:3491–3497. doi: 10.1210/jc.2004-2235. [DOI] [PubMed] [Google Scholar]
  • 14.Taylor BC, Schreiner PJ, Zmuda JM, Li J, Moffett SP, Beck TJ, Cummings SR, Lee JM, Walker K, Ensrud KE. Association of endothelial nitric oxide synthase genotypes with bone mineral density, bone loss, hip structure, and risk of fracture in older women: the SOF study. Bone. 2006;39:174–180. doi: 10.1016/j.bone.2005.12.080. [DOI] [PubMed] [Google Scholar]
  • 15.Moffett SP, Oakley JI, Cauley JA, Lui LY, Ensrud KE, Taylor BC, Hillier TA, Hochberg MC, Li J, Cayabyab S, Lee JM, Peltz G, Cummings SR, Zmuda JM. Osteoprotegerin Lys3Asn polymorphism and the risk of fracture in older women. J Clin Endocrinol Metab. 2008;93:2002–2008. doi: 10.1210/jc.2007-1019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Cummings SR, Nevitt MC, Browner WS, Stone K, Fox KM, Ensrud KE, Cauley J, Black D, Vogt TM. Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. N Engl J Med. 1995;332:767–773. doi: 10.1056/NEJM199503233321202. [DOI] [PubMed] [Google Scholar]
  • 17.Farmer ME, White LR, Brody JA, Bailey KR. Race and sex differences in hip fracture incidence. Am J Public Health. 1984;74:1374–1380. doi: 10.2105/ajph.74.12.1374. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Cheng S, Grow MA, Pallaud C, Klitz W, Erlich HA, Visvikis S, Chen JJ, Pullinger CR, Malloy MJ, Siest G, Kane JP. A multilocus genotyping assay for candidate markers of cardiovascular disease risk. Genome Res. 1999;9:936–949. doi: 10.1101/gr.9.10.936. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Cummings SR, Nevitt MC, Browner WS, Stone K, Fox KM, Ensrud KE, Cauley J, Black D, Vogt TM. Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. N Engl J Med. 1995;332:767–773. doi: 10.1056/NEJM199503233321202. [DOI] [PubMed] [Google Scholar]
  • 20.Nevitt MC, Cummings SR, Stone KL, Palermo L, Black DM, Bauer DC, Genant HK, Hochberg MC, Ensrud KE, Hillier TA, Cauley JA. Risk factors for a first-incident radiographic vertebral fracture in women > or = 65 years of age: the study of osteoporotic fractures. J Bone Miner Res. 2005;20:131–140. doi: 10.1359/JBMR.041003. [DOI] [PubMed] [Google Scholar]
  • 21.Cauley JA, Hochberg MC, Lui LY, Palermo L, Ensrud KE, Hillier TA, Nevitt MC, Cummings SR. Long-term risk of incident vertebral fractures. JAMA. 2007;298:2761–2767. doi: 10.1001/jama.298.23.2761. [DOI] [PubMed] [Google Scholar]
  • 22.Nevitt MC, Cummings SR, Browner WS, Seeley DG, Cauley JA, Vogt TM, Black DM. The accuracy of self-report of fractures in elderly women: evidence from a prospective study. Am J Epidemiol. 1992;135:490–499. doi: 10.1093/oxfordjournals.aje.a116315. [DOI] [PubMed] [Google Scholar]
  • 23.Ensrud KE, Palermo L, Black DM, Cauley J, Jergas M, Orwoll ES, Nevitt MC, Fox KM, Cummings SR. Hip and calcaneal bone loss increase with advancing age: longitudinal results from the study of osteoporotic fractures. J Bone Miner Res. 1995;10:1778–1787. doi: 10.1002/jbmr.5650101122. [DOI] [PubMed] [Google Scholar]
  • 24.Steiger P, Cummings SR, Black DM, Spencer NE, Genant HK. Age-related decrements in bone mineral density in women over 65. J Bone Miner Res. 1992;7:625–632. doi: 10.1002/jbmr.5650070606. [DOI] [PubMed] [Google Scholar]
  • 25.Orwoll ES, Oviatt SK. Longitudinal precision of dual-energy X-ray absorptiometry in a multicenter study. The Nafarelin/Bone Study Group. J Bone Miner Res. 1991;6:191–197. doi: 10.1002/jbmr.5650060213. [DOI] [PubMed] [Google Scholar]
  • 26.Black DM, Cummings SR, Genant HK, Nevitt MC, Palermo L, Browner W. Axial and appendicular bone density predict fractures in older women. J Bone Miner Res. 1992;7:633–638. doi: 10.1002/jbmr.5650070607. [DOI] [PubMed] [Google Scholar]
  • 27.Cummings SR, Black DM, Nevitt MC, Browner WS, Cauley JA, Genant HK, Mascioli SR, Scott JC, Seeley DG, Steiger P, Vogt TM. Appendicular bone density and age predict hip fracture in women. The Study of Osteoporotic Fractures Research Group. JAMA. 1990;263:665–668. [PubMed] [Google Scholar]
  • 28.Cummings SR, Black DM, Nevitt MC, Browner W, Cauley J, Ensrud K, Genant HK, Palermo L, Scott J, Vogt TM. Bone density at various sites for prediction of hip fractures. The Study of Osteoporotic Fractures Research Group. Lancet. 1993;341:72–75. doi: 10.1016/0140-6736(93)92555-8. [DOI] [PubMed] [Google Scholar]
  • 29.Devoto M, Shimoya K, Caminis J, Ott J, Tenenhouse A, Whyte MP, Sereda L, Hall S, Considine E, Williams CJ, Tromp G, Kuivaniemi H, Ala-Kokko L, Prockop DJ, Spotila LD. First-stage autosomal genome screen in extended pedigrees suggests genes predisposing to low bone mineral density on chromosomes 1p, 2p and 4q. Eur J Hum Genet. 1998;6:151–157. doi: 10.1038/sj.ejhg.5200169. [DOI] [PubMed] [Google Scholar]
  • 30.Deng HW, Xu FH, Huang QY, Shen H, Deng H, Conway T, Liu YJ, Liu YZ, Li JL, Zhang HT, Davies KM, Recker RR. A whole-genome linkage scan suggests several genomic regions potentially containing quantitative trait loci for osteoporosis. J Clin Endocrinol Metab. 2002;87:5151–5159. doi: 10.1210/jc.2002-020474. [DOI] [PubMed] [Google Scholar]
  • 31.Mullin BH, Spector TD, Curtis CC, Ong GN, Hart DJ, Hakim AJ, Worthy T, Wilson SG. Polymorphisms in ALOX12, but not ALOX15, are significantly associated with BMD in post-menopausal women. Calcif Tissue Int. 2007;81:10–17. doi: 10.1007/s00223-007-9023-3. [DOI] [PubMed] [Google Scholar]
  • 32.Ichikawa S, Koller DL, Johnson ML, Lai D, Xuei X, Edenberg HJ, Klein RF, Orwoll ES, Hui SL, Foroud TM, Peacock M, Econs MJ. Human ALOX12, but not ALOX15, is associated with BMD in white men and women. J Bone Miner Res. 2006;21:556–564. doi: 10.1359/jbmr.051212. [DOI] [PubMed] [Google Scholar]
  • 33.Cheung CL, Chan V, Kung AW. A differential association of ALOX15 polymorphisms with bone mineral density in pre-and post-menopausal women. Hum Hered. 2008;65:1–8. doi: 10.1159/000106057. [DOI] [PubMed] [Google Scholar]
  • 34.Urano T, Shiraki M, Fujita M, Hosoi T, Orimo H, Ouchi Y, Inoue S. Association of a single nucleotide polymorphism in the lipoxygenase ALOX15 5′-flanking region (−5229G/A) with bone mineral density. J Bone Miner Metab. 2005;23:226–230. doi: 10.1007/s00774-004-0588-x. [DOI] [PubMed] [Google Scholar]
  • 35.Wittwer J, Marti-Jaun J, Hersberger M. Functional polymorphism in ALOX15 results in increased allele-specific transcription in macrophages through binding of the transcription factor SPI1. Hum Mutat. 2006;27:78–87. doi: 10.1002/humu.20273. [DOI] [PubMed] [Google Scholar]
  • 36.Wittwer J, Bayer M, Mosandl A, Muntwyler J, Hersberger M. The c.−292C>T promoter polymorphism increases reticulocyte- type 15-lipoxygenase-1 activity and could be atheroprotective. Clin Chem Lab Med. 2007;45:487–492. doi: 10.1515/CCLM.2007.103. [DOI] [PubMed] [Google Scholar]
  • 37.Bataille-Simoneau N, Gerland K, Chappard D, Basle MF, Mercier L. Expression of prolactin receptors in human osteosarcoma cells. Biochem Biophys Res Commun. 1996;229:323–328. doi: 10.1006/bbrc.1996.1800. [DOI] [PubMed] [Google Scholar]
  • 38.Clement-Lacroix P, Ormandy C, Lepescheux L, Ammann P, Damotte D, Goffin V, Bouchard B, Amling M, Gaillard-Kelly M, Binart N, Baron R, Kelly PA. Osteoblasts are a new target for prolactin: analysis of bone formation in prolactin receptor knockout mice. Endocrinology. 1999;140:96–105. doi: 10.1210/endo.140.1.6436. [DOI] [PubMed] [Google Scholar]
  • 39.Coss D, Yang L, Kuo CB, Xu X, Luben RA, Walker AM. Effects of prolactin on osteoblast alkaline phosphatase and bone formation in the developing rat. Am J Physiol Endocrinol Metab. 2000;279:E1216–E1225. doi: 10.1152/ajpendo.2000.279.6.E1216. [DOI] [PubMed] [Google Scholar]
  • 40.Sanfilippo JS. Implications of not treating hyperprolactinemia. J Reprod Med. 1999;44:1111–1115. [PubMed] [Google Scholar]
  • 41.Biller BM, Luciano A, Crosignani PG, Molitch M, Olive D, Rebar R, Sanfilippo J, Webster J, Zacur H. Guidelines for the diagnosis and treatment of hyperprolactinemia. J Reprod Med. 1999;44:1075–1084. [PubMed] [Google Scholar]
  • 42.Lasco A, Cannavo S, Gaudio A, Morabito N, Basile G, Nicita-Mauro V, Frisina N. Effects of long-lasting raloxifene treatment on serum prolactin and gonadotropin levels in postmenopausal women. Eur J Endocrinol. 2002;147:461–465. doi: 10.1530/eje.0.1470461. [DOI] [PubMed] [Google Scholar]
  • 43.Styrkarsdottir U, Cazier JB, Kong A, Rolfsson O, Larsen H, Bjarnadottir E, Johannsdottir VD, Sigurdardottir MS, Bagger Y, Christiansen C, Reynisdottir I, Grant SF, Jonasson K, Frigge ML, Gulcher JR, Sigurdsson G, Stefansson K. Linkage of osteoporosis to chromosome 20p12 and association to BMP2. PLoS Biol. 2003;1:E69. doi: 10.1371/journal.pbio.0000069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Reneland RH, Mah S, Kammerer S, Hoyal CR, Marnellos G, Wilson SG, Sambrook PN, Spector TD, Nelson MR, Braun A. Association between a variation in the phosphodiesterase 4D gene and bone mineral density. BMC Med Genet. 2005;6:9. doi: 10.1186/1471-2350-6-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Medici M, van Meurs JB, Rivadeneira F, Zhao H, Arp PP, Hofman A, Pols HA, Uitterlinden AG. BMP-2 gene polymorphisms and osteoporosis: the Rotterdam Study. J Bone Miner Res. 2006;21:845–854. doi: 10.1359/jbmr.060306. [DOI] [PubMed] [Google Scholar]
  • 46.Inoue K, Mikuni-Takagaki Y, Oikawa K, Itoh T, Inada M, Noguchi T, Park JS, Onodera T, Krane SM, Noda M, Itohara S. A crucial role for matrix metalloproteinase 2 in osteocytic canalicular formation and bone metabolism. J Biol Chem. 2006;281:33814–33824. doi: 10.1074/jbc.M607290200. [DOI] [PubMed] [Google Scholar]
  • 47.Guo LJ, Luo XH, Wu XP, Shan PF, Zhang H, Cao XZ, Xie H, Liao EY. Serum concentrations of MMP-1, MMP-2, and TIMP-1 in Chinese women: age-related changes, and the relationships with bone biochemical markers, bone mineral density. Clin Chim Acta. 2006;371:137–142. doi: 10.1016/j.cca.2006.02.036. [DOI] [PubMed] [Google Scholar]
  • 48.Luo XH, Guo LJ, Shan PF, Xie H, Wu XP, Zhang H, Cao XZ, Yuan LQ, Liao EY. Relationship of circulating MMP-2, MMP-1, and TIMP-1 levels with bone biochemical markers and bone mineral density in postmenopausal Chinese women. Osteoporos Int. 2006;17:521–526. doi: 10.1007/s00198-005-0017-6. [DOI] [PubMed] [Google Scholar]
  • 49.Albagha OM, McGuigan FE, Reid DM, Ralston SH. Estrogen receptor alpha gene polymorphisms and bone mineral density: haplotype analysis in women from the United Kingdom. J Bone Miner Res. 2001;16:128–134. doi: 10.1359/jbmr.2001.16.1.128. [DOI] [PubMed] [Google Scholar]
  • 50.Albagha OM, Pettersson U, Stewart A, McGuigan FE, MacDonald HM, Reid DM, Ralston SH. Association of oestrogen receptor alpha gene polymorphisms with postmenopausal bone loss, bone mass, and quantitative ultrasound properties of bone. J Med Genet. 2005;42:240–246. doi: 10.1136/jmg.2004.023895. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Ioannidis JP, Ralston SH, Bennett ST, Brandi ML, Grinberg D, Karassa FB, Langdahl B, van Meurs JB, Mosekilde L, Scollen S, Albagha OM, Bustamante M, Carey AH, Dunning AM, Enjuanes A, van Leeuwen JP, Mavilia C, Masi L, McGuigan FE, Nogues X, Pols HA, Reid DM, Schuit SC, Sherlock RE, Uitterlinden AG. Differential genetic effects of ESR1 gene polymorphisms on osteoporosis outcomes. JAMA. 2004;292:2105–2114. doi: 10.1001/jama.292.17.2105. [DOI] [PubMed] [Google Scholar]
  • 52.Jurada S, Marc J, Prezelj J, Kocijancic A, Komel R. Codon 325 sequence polymorphism of the estrogen receptor alpha gene and bone mineral density in postmenopausal women. J Steroid Biochem Mol Biol. 2001;78:15–20. doi: 10.1016/s0960-0760(01)00069-3. [DOI] [PubMed] [Google Scholar]
  • 53.Zavratnik A, Prezelj J, Kocijancic A, Marc J. Exonic, but not intronic polymorphisms of ESR1 gene might influence the hypolipemic effect of raloxifene. J Steroid Biochem Mol Biol. 2007;104:22–26. doi: 10.1016/j.jsbmb.2006.10.009. [DOI] [PubMed] [Google Scholar]
  • 54.Turner CH, Roeder RK, Wieczorek A, Foroud T, Liu G, Peacock M. Variability in skeletal mass, structure, and biomechanical properties among inbred strains of rats. J Bone Miner Res. 2001;16:1532–1539. doi: 10.1359/jbmr.2001.16.8.1532. [DOI] [PubMed] [Google Scholar]
  • 55.Beamer WG, Shultz KL, Donahue LR, Churchill GA, Sen S, Wergedal JR, Baylink DJ, Rosen CJ. Quantitative trait loci for femoral and lumbar vertebral bone mineral density in C57BL/6J and C3H/HeJ inbred strains of mice. J Bone Miner Res. 2001;16:1195–1206. doi: 10.1359/jbmr.2001.16.7.1195. [DOI] [PubMed] [Google Scholar]
  • 56.Sheng MH, Baylink DJ, Beamer WG, Donahue LR, Lau KH, Wergedal JE. Regulation of bone volume is different in the metaphyses of the femur and vertebra of C3H/HeJ and C57BL/6J mice. Bone. 2002;30:486–491. doi: 10.1016/s8756-3282(01)00693-7. [DOI] [PubMed] [Google Scholar]
  • 57.Beamer WG, Donahue LR, Rosen CJ. Genetics and bone. Using the mouse to understand man. J Musculoskelet Neuronal Interact. 2002;2:225–231. [PubMed] [Google Scholar]
  • 58.Garcia-Giralt N, Nogues X, Enjuanes A, Puig J, Mellibovsky L, Bay-Jensen A, Carreras R, Balcells S, Diez-Perez A, Grinberg D. Two new single-nucleotide polymorphisms in the COL1A1 upstream regulatory region and their relationship to bone mineral density. J Bone Miner Res. 2002;17:384–393. doi: 10.1359/jbmr.2002.17.3.384. [DOI] [PubMed] [Google Scholar]
  • 59.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. doi: 10.1038/ng1096-203. [DOI] [PubMed] [Google Scholar]
  • 60.Mann V, Hobson EE, Li B, Stewart TL, Grant SF, Robins SP, Aspden RM, Ralston SH. A COL1A1 Sp1 binding site polymorphism predisposes to osteoporotic fracture by affecting bone density and quality. J Clin Invest. 2001;107:899–907. doi: 10.1172/JCI10347. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.McGuigan FE, Armbrecht G, Smith R, Felsenberg D, Reid DM, Ralston SH. Prediction of osteoporotic fractures by bone densitometry and COLIA1 genotyping: a prospective, population-based study in men and women. Osteoporos Int. 2001;12:91–96. doi: 10.1007/s001980170139. [DOI] [PubMed] [Google Scholar]
  • 62.Uitterlinden AG, Burger H, Huang Q, Yue F, McGuigan FE, Grant SF, Hofman A, van Leeuwen JP, Pols HA, Ralston SH. Relation of alleles of the collagen type Ialpha1 gene to bone density and the risk of osteoporotic fractures in postmenopausal women. N Engl J Med. 1998;338:1016–1021. doi: 10.1056/NEJM199804093381502. [DOI] [PubMed] [Google Scholar]
  • 63.Stewart TL, Jin H, McGuigan FE, Albagha OM, Garcia-Giralt N, Bassiti A, Grinberg D, Balcells S, Reid DM, Ralston SH. Haplotypes defined by promoter and intron 1 polymorphisms of the COLIA1 gene regulate bone mineral density in women. J Clin Endocrinol Metab. 2006;91:3575–3583. doi: 10.1210/jc.2005-2651. [DOI] [PubMed] [Google Scholar]
  • 64.Ralston SH, Uitterlinden AG, Brandi ML, Balcells S, Langdahl BL, Lips P, Lorenc R, Obermayer-Pietsch B, Scollen S, Bustamante M, Husted LB, Carey AH, Diez-Perez A, Dunning AM, Falchetti A, Karczmarewicz E, Kruk M, van Leeuwen JP, van Meurs JB, Mangion J, McGuigan FE, Mellibovsky L, del Monte F, Pols HA, Reeve J, Reid DM, Renner W, Rivadeneira F, van Schoor NM, Sherlock RE, Ioannidis JP. Large-scale evidence for the effect of the COLIA1 Sp1 polymorphism on osteoporosis outcomes: the GENOMOS study. PLoS Med. 2006;3:e90. doi: 10.1371/journal.pmed.0030090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Ferrari SL, Deutsch S, Choudhury U, Chevalley T, Bonjour JP, Dermitzakis ET, Rizzoli R, Antonarakis SE. Polymorphisms in the low-density lipoprotein receptor–related protein 5 (LRP5) gene are associated with variation in vertebral bone mass, vertebral bone size, and stature in whites. Am J Hum Genet. 2004;74:866–875. doi: 10.1086/420771. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Koay MA, Woon PY, Zhang Y, Miles LJ, Duncan EL, Ralston SH, Compston JE, Cooper C, Keen R, Langdahl BL, MacLelland A, O’Riordan J, Pols HA, Reid DM, Uitterlinden AG, Wass JA, Brown MA. Influence of LRP5 polymorphisms on normal variation in BMD. J Bone Miner Res. 2004;19:1619–1627. doi: 10.1359/JBMR.040704. [DOI] [PubMed] [Google Scholar]
  • 67.Koh JM, Jung MH, Hong JS, Park HJ, Chang JS, Shin HD, Kim SY, Kim GS. Association between bone mineral density and LDL receptor-related protein 5 gene polymorphisms in young Korean men. J Korean Med Sci. 2004;19:407–412. doi: 10.3346/jkms.2004.19.3.407. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Mizuguchi T, Furuta I, Watanabe Y, Tsukamoto K, Tomita H, Tsujihata M, Ohta T, Kishino T, Matsumoto N, Minakami H, Niikawa N, Yoshiura K. LRP5, low-density-lipoprotein-receptor- related protein 5, is a determinant for bone mineral density. J Hum Genet. 2004;49:80–86. doi: 10.1007/s10038-003-0111-6. [DOI] [PubMed] [Google Scholar]
  • 69.van Meurs JB, Trikalinos TA, Ralston SH, Balcells S, Brandi ML, Brixen K, Kiel DP, Langdahl BL, Lips P, Ljunggren O, Lorenc R, Obermayer-Pietsch B, Ohlsson C, Pettersson U, Reid DM, Rousseau F, Scollen S, Van Hul W, Agueda L, Akesson K, Benevolenskaya LI, Ferrari SL, Hallmans G, Hofman A, Husted LB, Kruk M, Kaptoge S, Karasik D, Karlsson MK, Lorentzon M, Masi L, McGuigan FE, Mellstrom D, Mosekilde L, Nogues X, Pols HA, Reeve J, Renner W, Rivadeneira F, van Schoor NM, Weber K, Ioannidis JP, Uitterlinden AG. Large-scale analysis of association between LRP5 and LRP6 variants and osteoporosis. JAMA. 2008;299:1277–1290. doi: 10.1001/jama.299.11.1277. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Richards JB, Rivadeneira F, Inouye M, Pastinen TM, Soranzo N, Wilson SG, Andrew T, Falchi M, Gwilliam R, Ahmadi KR, Valdes AM, Arp P, Whittaker P, Verlaan DJ, Jhamai M, Kumanduri V, Moorhouse M, van Meurs JB, Hofman A, Pols HA, Hart D, Zhai G, Kato BS, Mullin BH, Zhang F, Deloukas P, Uitterlinden AG, Spector TD. Bone mineral density, osteoporosis, and osteoporotic fractures: a genome-wide association study. Lancet. 2008;371:1505–1512. doi: 10.1016/S0140-6736(08)60599-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Giroux S, Elfassihi L, Cole DE, Rousseau F. Replication of associations between LRP5 and ESRRA variants and bone density in premenopausal women. Osteoporos Int. 2008 doi: 10.1007/s00198-008-0617-z. (in press) [DOI] [PubMed] [Google Scholar]
  • 72.Lorentzon M, Lorentzon R, Lerner UH, Nordstrom P. Calcium sensing receptor gene polymorphism, circulating calcium concentrations and bone mineral density in healthy adolescent girls. Eur J Endocrinol. 2001;144:257–261. doi: 10.1530/eje.0.1440257. [DOI] [PubMed] [Google Scholar]
  • 73.Zofkova I, Zajickova K, Hill M, Krepelova A. Does polymorphism C1377T of the calcitonin receptor gene determine bone mineral density in postmenopausal women? Exp Clin Endocrinol Diabetes. 2003;111:447–449. doi: 10.1055/s-2003-44293. [DOI] [PubMed] [Google Scholar]
  • 74.Abrahamsen B, Madsen JS, Tofteng CL, Stilgren L, Bladbjerg EM, Kristensen SR, Brixen K, Mosekilde L. A common methylenetetrahydrofolate reductase (C677T) polymorphism is associated with low bone mineral density and increased fracture incidence after menopause: longitudinal data from the Danish osteoporosis prevention study. J Bone Miner Res. 2003;18:723–729. doi: 10.1359/jbmr.2003.18.4.723. [DOI] [PubMed] [Google Scholar]
  • 75.Bathum L, n Hjelmborg J, Christiansen L, Madsen JS, Skytthe A, Christensen K. Evidence for an association of methylene tetrahydrofolate reductase polymorphism C677T and an increased risk of fractures: results from a population-based Danish twin study. Osteoporos Int. 2004;15:659–664. doi: 10.1007/s00198-003-1584-z. [DOI] [PubMed] [Google Scholar]
  • 76.Hong X, Hsu YH, Terwedow H, Tang G, Liu X, Jiang S, Xu X, Xu X. Association of the methylenetetrahydrofolate reductase C677T polymorphism and fracture risk in Chinese postmenopausal women. Bone. 2007;40:737–742. doi: 10.1016/j.bone.2006.09.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77.Jorgensen HL, Madsen JS, Madsen B, Saleh MM, Abrahamsen B, Fenger M, Lauritzen JB. Association of a common allelic polymorphism (C677T) in the methylene tetrahydrofolate reductase gene with a reduced risk of osteoporotic fractures. A case control study in Danish postmenopausal women. Calcif Tissue Int. 2002;71:386–392. doi: 10.1007/s00223-001-2126-3. [DOI] [PubMed] [Google Scholar]
  • 78.Kiel DP, Demissie S, Dupuis J, Lunetta KL, Murabito JM, Karasik D. Genome-wide association with bone mass and geometry in the Framingham Heart Study. BMC Med Genet. 2007;8(Suppl 1):S14. doi: 10.1186/1471-2350-8-S1-S14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79.Miyao M, Morita H, Hosoi T, Kurihara H, Inoue S, Hoshino S, Shiraki M, Yazaki Y, Ouchi Y. Association of methylenetetrahydrofolate reductase (MTHFR) polymorphism with bone mineral density in postmenopausal Japanese women. Calcif Tissue Int. 2000;66:190–194. doi: 10.1007/s002230010038. [DOI] [PubMed] [Google Scholar]
  • 80.Valero C, Alonso MA, Zarrabeitia MT, Viadero C, Hernandez JL, Riancho JA. MTHFR C677T polymorphism and osteoporotic fractures. Horm Metab Res. 2007;39:543–547. doi: 10.1055/s-2007-985131. [DOI] [PubMed] [Google Scholar]
  • 81.Villadsen MM, Bunger MH, Carstens M, Stenkjaer L, Langdahl BL. Methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism is associated with osteoporotic vertebral fractures, but is a weak predictor of BMD. Osteoporos Int. 2005;16:411–416. doi: 10.1007/s00198-004-1704-4. [DOI] [PubMed] [Google Scholar]
  • 82.Uitterlinden AG, Ralston SH, Brandi ML, Carey AH, Grinberg D, Langdahl BL, Lips P, Lorenc R, Obermayer-Pietsch B, Reeve J, Reid DM, Amedei A, Bassiti A, Bustamante M, Husted LB, Diez-Perez A, Dobnig H, Dunning AM, Enjuanes A, Fahrleitner-Pammer A, Fang Y, Karczmarewicz E, Kruk M, van Leeuwen JP, Mavilia C, van Meurs JB, Mangion J, McGuigan FE, Pols HA, Renner W, Rivadeneira F, van Schoor NM, Scollen S, Sherlock RE, Ioannidis JP. The association between common vitamin D receptor gene variations and osteoporosis: a participantlevel meta-analysis. Ann Intern Med. 2006;145:255–264. doi: 10.7326/0003-4819-145-4-200608150-00005. [DOI] [PubMed] [Google Scholar]
  • 83.Langdahl BL, Uitterlinden AG, Ralston SH, Trikalinos TA, Balcells S, Brandi ML, Scollen S, Lips P, Lorenc R, Obermayer-Pietsch B, Reid DM, Armas JB, Arp PP, Bassiti A, Bustamante M, Husted LB, Carey AH, Perez Cano R, Dobnig H, Dunning AM, Fahrleitner-Pammer A, Falchetti A, Karczmarewicz E, Kruk M, van Leeuwen JP, Masi L, van Meurs JB, Mangion J, McGuigan FE, Mellibovsky L, Mosekilde L, Nogues X, Pols HA, Reeve J, Renner W, Rivadeneira F, van Schoor NM, Ioannidis JP. Large-scale analysis of association between polymorphisms in the transforming growth factor beta 1 gene (TGFB1) and osteoporosis: the GENOMOS study. Bone. 2008;42:969–981. doi: 10.1016/j.bone.2007.11.007. [DOI] [PubMed] [Google Scholar]
  • 84.Ioannidis JP. Why most published research findings are false. PLoS Med. 2005;2:e124. doi: 10.1371/journal.pmed.0020124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85.Rebbeck TR, Martinez ME, Sellers TA, Shields PG, Wild CP, Potter JD. Genetic variation and cancer: improving the environment for publication of association studies. Cancer Epidemiol Biomarkers Prev. 2004;13:1985–1986. [PubMed] [Google Scholar]

RESOURCES