Mapping quantitative trait loci for cross-sectional geometry at the femoral neck

Gender differences in a reference database of age-related femoral neck geometric parameters for Chinese population and their association with femoral neck fractures

Femoral neck geometric parameters (FNGPs) are closely related to the strength of the femoral neck and the risk of fragility fractures. No reference database is available for FNGPs for Chinese population, and gender-related differences in FNGPs as well as their association with the risk of femoral neck fractures are unknown. This investigation aimed to set up reference databases for FNGPs, understand gender-related differences in FNGPs, and examine the association between FNGPs and the risk of osteoporotic fractures of the femoral neck. This study included 5268 females and 2156 males (aged 15-91years) from Chinese population. A total of 384 patients (282 females and 102 males) had sustained femoral neck fractures; 384 age- and sex-matched individuals without any fractures served as controls. Femoral neck DXA images were used to measure bone mineral density (BMD) and eight FNGPs. Our results showed that the age-related trends of FNGPs were fitted with the best goodness-of-fit by applying the cubic regression model. The trends shown by FNGPs were significantly different between male and female subjects, and the fitting curves were significantly higher in male subjects. After adjustments were made for age, height, weight, and body mass index, Cox regression analysis showed that changes in all FNGPs were related to increased hazard ratios (HRs) of femoral neck fractures. After further adjustment was made for BMD of the femoral neck, the HRs related to a cortical thickness (CT) decrease and buckling ratio (BR) increase in females went up by 3.35-folds (95% CI: 2.75-4.07) and 1.86-folds (95% CI: 1.33-2.60), respectively. In males, the HRs related to the decrease in CT and cross-sectional area (CSA) increased by 3.21-folds (95% CI: 2.32-4.45) and 1.88-folds (95% CI: 1.03-3.44), respectively. In conclusions, the reference databases of FNGPs established in this study will assist in the evaluation and prediction of femoral neck fracture risk in the clinic. The decrease in CT and increase in BR of the femoral neck were independent risk factors for osteoporotic fractures of the femoral neck in females from mainland China, while a decrease in CT and CSA were risk factors in male.

Quantification of Alterations in Cortical Bone Geometry Using Site Specificity Software in Mouse models of Aging and the Responses to Ovariectomy and Altered Loading

Investigations into the effect of (re)modeling stimuli on cortical bone in rodents normally rely on analysis of changes in bone mass and architecture at a narrow cross-sectional site. However, it is well established that the effects of axial loading produce site-specific changes throughout bones' structure. Non-mechanical influences (e.g., hormones) can be additional to or oppose locally controlled adaptive responses and may have more generalized effects. Tools currently available to study site-specific cortical bone adaptation are limited. Here, we applied novel site specificity software to measure bone mass and architecture at each 1% site along the length of the mouse tibia from standard micro-computed tomography (μCT) images. Resulting measures are directly comparable to those obtained through μCT analysis (R (2) > 0.96). Site Specificity analysis was used to compare a number of parameters in tibiae from young adult (19-week-old) versus aged (19-month-old) mice; ovariectomized and entire mice; limbs subjected to short periods of axial loading or disuse induced by sciatic neurectomy. Age was associated with uniformly reduced cortical thickness and site-specific decreases in cortical area most apparent in the proximal tibia. Mechanical loading site-specifically increased cortical area and thickness in the proximal tibia. Disuse uniformly decreased cortical thickness and decreased cortical area in the proximal tibia. Ovariectomy uniformly reduced cortical area without altering cortical thickness. Differences in polar moment of inertia between experimental groups were only observed in the proximal tibia. Aging and ovariectomy also altered eccentricity in the distal tibia. In summary, site specificity analysis provides a valuable tool for measuring changes in cortical bone mass and architecture along the entire length of a bone. Changes in the (re)modeling response determined at a single site may not reflect the response at different locations within the same bone.

Bivariate genome-wide association analyses identified genes with pleiotropic effects for femoral neck bone geometry and age at menarche

Femoral neck geometric parameters (FNGPs), which include cortical thickness (CT), periosteal diameter (W), buckling ratio (BR), cross-sectional area (CSA), and section modulus (Z), contribute to bone strength and may predict hip fracture risk. Age at menarche (AAM) is an important risk factor for osteoporosis and bone fractures in women. Some FNGPs are genetically correlated with AAM. In this study, we performed a bivariate genome-wide association study (GWAS) to identify new candidate genes responsible for both FNGPs and AAM. In the discovery stage, we tested 760,794 SNPs in 1,728 unrelated Caucasian subject, followed by replication analyses in independent samples of US Caucasians (with 501 subjects) and Chinese (with 826 subjects). We found six SNPs that were associated with FNGPs and AAM. These SNPs are located in three genes (i.e. NRCAM, IDS and LOC148145), suggesting these three genes may co-regulate FNGPs and AAM. Our findings may help improve the understanding of genetic architecture and pathophysiological mechanisms underlying both osteoporosis and AAM.

The relationships between femoral cortex geometry and tissue mechanical properties

Bone tissue and geometry are constantly modified through modeling and remodeling at the periosteal, endosteal and intracortical envelopes. Results from several studies indicate that femoral bone geometry is a predictor of whole bone strength (e.g. femoral neck strength), however, it is not known whether there is a relationship between bone structural and material properties. Bone geometry can be determined from parameters based on plane X-ray radiogrammetry which are used to evaluate femoral bone quality for implant success. If there is a relationship between these parameters and tissue mechanical properties, this would have implications in the interpretation of such parameters for assessment of fracture risk and in further understanding of bone biology. Following measurement of radiogrammetric parameters from antero-posterior and medio-lateral X-rays (cortical thickness, bone diameter, bone area, moment of inertia, cortical index, Singh index), human femurs were machined into standard test specimens for assessment of tensile fracture toughness (GIc) of the tissue. Results indicated that tensile fracture toughness generally increased with increasing bone size. We also found that fracture toughness of the tissue was significantly related to radiogrammetric indices and that some of these indices explained a greater variability in toughness than porosity, age or gender.

Refined QTLs of osteoporosis-related traits by linkage analysis with genome-wide SNPs: Framingham SHARe

Genome-wide association studies (GWAS) using high-density array of single-nucleotide polymorphisms (SNPs) offer an unbiased strategy to identify new candidate genes for osteoporosis. We used a subset of autosomal SNPs from the Affymetrix 500K+50K SNP GeneChip marker set to examine genetic linkage with multiple highly heritable osteoporosis-related traits, including BMD of the hip and spine, heel ultrasound (attenuation and speed of sound), and geometric indices of the hip, in two generations from the Framingham Osteoporosis Study. Variance component linkage analysis was performed using normalized residuals (adjusted for age, height, BMI, and estrogen status in women). Multipoint linkage analyses produced LOD scores > or =3.0 for BMD on chromosomes (chr.) 9 and 11 and for ultrasound speed of sound on chr. 5. Hip geometric traits were linked with higher LOD scores, such as with shaft width on chr. 4 (LOD=3.9) and chr. 16 (LOD=3.8) and with shaft section modulus on chr. 22 (LOD=4.0). LOD score > or =5.0 was obtained for femoral neck width on chr. 7. In conclusion, with an SNP-based linkage approach, we identified several novel potential QTLs and confirmed previously identified chromosomal regions linked to bone mass and geometry. Subsequent focus on the spectrum of genetic polymorphisms in these refined regions may contribute to finding variants predisposing to osteoporosis.

Genome-wide copy number variation association study suggested VPS13B gene for osteoporosis in Caucasians

Osteoporotic fracture (OF) is a serious outcome of osteoporosis. Important risk factors for OF include reduced bone mineral density and unstable bone structure. This genome-wide copy number variation association study suggested VPS13B gene for osteoporosis in Caucasians.

INTRODUCTION

Bone mineral density (BMD) and femoral neck cross-sectional geometric parameters (FNCSGPs) are under strong genetic control. DNA copy number variation (CNV) is an important source of genetic diversity for human diseases. This study aims to identify CNVs associated with BMD and FNCSGPs.

METHODS

Genome-wide CNV association analyses were conducted in 1,000 unrelated Caucasian subjects for BMD at the spine, hip, femoral neck, and for three FNCSGPs -cortical thickness (CT), cross-section area (CSA), and buckling ratio (BR). BMD was measured by dual energy X-ray absorptiometry (DEXA). CT, CSA, and BR were estimated using DEXA measurements. Affymetrix 500K arrays and copy number analysis tool was used to identify CNVs.

RESULTS

A CNV in VPS13B gene was significantly associated with spine, hip and FN BMDs, and CT, CSA, and BR (p < 0.05). Compared to subjects with two copies of the CNV, carriers of one copy had an average of 14.6%, 12.4%, and 13.6% higher spine, hip, and FN BMD, 20.0% thicker CT, 10.6% larger CSA, and 12.4% lower BR. Thus, a decrease of the CNV consistently produced stronger bone, thereby reducing osteoporotic fracture risk.

CONCLUSIONS

VPS13B gene, via affecting BMD and FNCSGPs, is a novel osteoporosis risk gene.

Genome-wide association study for femoral neck bone geometry

Poor femoral neck bone geometry at the femur is an important risk factor for hip fracture. We conducted a genome-wide association study (GWAS) of femoral neck bone geometry, examining approximately 379,000 eligible single-nucleotide polymorphisms (SNPs) in 1000 Caucasians. A common genetic variant, rs7430431 in the receptor transporting protein 3 (RTP3) gene, was identified in strong association with the buckling ratio (BR, P = 1.6 x 10(-7)), an index of bone structural instability, and with femoral cortical thickness (CT, P = 1.9 x 10(-6)). The RTP3 gene is located in 3p21.31, a region that we found to be linked with CT (LOD = 2.19, P = 6.0 x 10(-4)) in 3998 individuals from 434 pedigrees. The replication analyses in 1488 independent Caucasians and 2118 Chinese confirmed the association of rs7430431 to BR and CT (combined P = 7.0 x 10(-3) for BR and P = 1.4 x 10(-2) for CT). In addition, 350 hip fracture patients and 350 healthy control individuals were genotyped to assess the association of the RTP3 gene with the risk of hip fracture. Significant association between a nearby common SNP, rs10514713 of the RTP3 gene, and hip fracture (P = 1.0 x 10(-3)) was found. Our observations suggest that RTP3 may be a novel candidate gene for femoral neck bone geometry.

Pathway-based genome-wide association analysis identified the importance of EphrinA-EphR pathway for femoral neck bone geometry

Femoral neck (FN) bone geometry is an important predictor of bone strength with high heritability. Previous studies have revealed certain candidate genes for FN bone geometry. However, the majority of the underlying genetic factors remain to be discovered. In this study, pathway-based genome-wide association analysis was performed to explore the joint effects of genes within biological pathways on FN bone geometry variations in a cohort of 1000 unrelated US whites. Nominal significant associations (nominal p value<0.05) were observed between 76 pathways and a key FN bone geometry variable-section modulus (Z), biomechanically indicative of bone strength subject to bending. Among them, EphrinA-EphR pathway was most significantly associated with FN Z even after multiple testing adjustments (p(FWER) value=0.035). The association of EphrinA-EphR pathway with FN Z was also observed in an independent sample from Framingham Osteoporosis Study. Overall, these results suggest the significant genetic contribution of EphrinA-EphR pathway to femoral neck bone geometry.

The contributions of lean tissue mass and fat mass to bone geometric adaptation at the femoral neck in Chinese overweight adults

BACKGROUND

Overweight or obese populations may have lower risk of osteoporotic fractures and higher bone mineral density (BMD), while bone strength is determined not only by bone material but also by bone structural parameters. Thus, the influence of body weight on bone geometry was examined in Chinese overweight adults.

AIM

The purpose of this study was to explore how total body lean mass (TBLM) and total body fat mass (TBFM) contribute to the variation of bone geometry at the femoral neck in Chinese overweight adults.

SUBJECTS AND METHODS

Bone geometric parameters including section modulus (Z), cross-sectional area (CSA), subperiosteal width (W), cortical thickness (CT) and buckling ratio (BR) were compared in 100 overweight (body mass index, BMI >/= 23) vs. 100 underweight subjects (BMI </= 18.5) in Chinese female and male adults aged 20-44 years by multiple regression analyses.

RESULTS

Multiple regression analysis revealed that both TBLM and TBFM were significantly higher in overweight subjects than in underweight subjects. Meanwhile, significant differences in bone geometric parameters (except W) were also detected between the overweight and underweight groups after adjustment for age and height in both sexes (p </= 0.001). Bone bending strength Z and axial strength CSA were 14% and 13% higher in females, as well as 18% and 20% higher in males in the overweight group than in the underweight group, respectively. The significant differences mentioned above were not observed when adjusted for TBLM, age, and height. TBLM seemed to be the strongest significant positive predictor of bone geometric parameters (p < 0.001), with the exception of W in both sexes and BR in females, while TBFM did not contribute significantly to the bone geometric parameters (p > 0.055 for both sexes).

CONCLUSION

Bone geometry may adapt primarily to mechanical load as represented by TBLM, but TBFM seemed to have no independent effect on bone geometry in Chinese overweight subjects.

Bivariate whole-genome linkage scan for bone geometry and total body fat mass

To quantify the genetic correlations between total body fat mass (TBFM) and femoral neck geometric parameters (FNGPs) and, if possible, to detect the specific genomic regions shared by them, bivariate genetic analysis and bivariate whole-genome linkage scan were carried out in a large Caucasian population. All the phenotypes studied were significantly controlled by genetic factors (P < 0.001) with the heritabilities ranging from 0.45 to 0.68. Significantly genetic correlations were found between TBFM and CSA (cross-section area), W (sub-periosteal diameter), Z (section modulus) and CT (cortical thickness) except between TBFM and BR (buckling ratio). The peak bivariate LOD scores were 3.23 (20q12), 2.47 (20p11), 3.19 (6q27), 1.68 (20p12), and 2.47 (7q11) for the five pairs of TBFM and BR, CSA, CT, W, and Z in the entire sample, respectively. Gender-specific bivariate linkage evidences were also found for the five pairs. 6p25 had complete pleiotropic effects on the variations of TBFM & Z in the female sub-population, and 6q27 and 17q11 had coincident linkages for TBFM & CSA and TBFM & Z in the entire population. We identified moderate genetic correlations and several shared genomic regions between TBFM and FNGPs in a large Caucasian population.

A bivariate whole genome linkage study identified genomic regions influencing both BMD and bone structure

Areal BMD (aBMD) and areal bone size (ABS) are biologically correlated traits and are each important determinants of bone strength and risk of fractures. Studies showed that aBMD and ABS are genetically correlated, indicating that they may share some common genetic factors, which, however, are largely unknown. To study the genetic factors influencing both aBMD and ABS, bivariate whole genome linkage analyses were conducted for aBMD-ABS at the femoral neck (FN), lumbar spine (LS), and ultradistal (UD)-forearm in a large sample of 451 white pedigrees made up of 4498 individuals. We detected significant linkage on chromosome Xq27 (LOD = 4.89) for LS aBMD-ABS. In addition, we detected suggestive linkages at 20q11 (LOD = 3.65) and Xp11 (LOD = 2.96) for FN aBMD-ABS; at 12p11 (LOD = 3.39) and 17q21 (LOD = 2.94) for LS aBMD-ABS; and at 5q23 (LOD = 3.54), 7p15 (LOD = 3.45), Xq27 (LOD = 2.93), and 12p11 (LOD = 2.92) for UD-forearm aBMD-ABS. Subsequent discrimination analyses indicated that quantitative trait loci (QTLs) at 12p11 and 17q21 may have pleiotropic effects on aBMD and ABS. This study identified several genomic regions that may contain QTLs important for both aBMD and ABS. Further endeavors are necessary to follow these regions to eventually pinpoint the genetic variants affecting bone strength and risk of fractures.

Post-fracture management of patients with hip fracture: a perspective

BACKGROUND

Hip fracture creates a worldwide morbidity, mortality and economic burden. After surgery, many patients experience long-term disability or die as a consequence of the fracture. A fracture is a major risk factor for a subsequent fracture, which may occur within a short interval.

METHODS

A literature search on post-fracture management of patients with hip fracture was performed on the Medline database. Key experts convened to develop a consensus document.

FINDINGS

Management of hip-fracture patients to optimize outcome after hospital discharge requires several stages of care co-ordinated by a multidisciplinary team from before admission through to discharge. Further studies that specifically assess prevention and post-fracture management of hip fracture are needed, as only one study to date has assessed an osteoporosis medication in patients with a recent hip fracture. Proper nutrition is vital to assist bone repair and prevent further falls, particularly in malnourished patients. Vitamin D, calcium and protein supplementation is associated with an increase in hip BMD and reduction in falls. Rehabilitation is essential to improve functional disabilities and survival rates. Fall prevention and functional recovery strategies should include patient education and training to improve balance and increase muscle strength and mobility. Appropriate management can prevent further fractures and it is critical that high-risk patients are identified and treated. To foster this process, clinical pathways have been established to support orthopaedic surgeons.

CONCLUSION

Although hip fracture is generally associated with poor outcomes, appropriate management can ensure optimal recovery and survival, and should be prioritized after a hip fracture to avoid deterioration of health and prevent subsequent fracture.

Autosome-wide linkage analysis of hip structural phenotypes in the Old Order Amish

INTRODUCTION

Fracture risk is associated with bone mineral density (BMD) and with other indices of bone strength, including hip geometry. While the heritability and associated fracture risk of BMD are well described, less is known about genetic influences of bone geometry. We derived hip structural phenotypes using the Hip Structural Analysis program (HSA) and performed autosome-wide linkage analysis of hip geometric structural phenotypes.

MATERIALS AND METHODS

The Amish Family Osteoporosis Study was designed to identify genes affecting bone health. BMD was measured at the hip using dual X-ray absorptiometry (DXA) in 879 participants (mean age+/-SD=49.8+/-16.1 years, range 18-91 years) from large multigenerational families. From DXA scans, we computed structural measures of hip geometry at the femoral neck (NN) and shaft (S) by HSA, including cross-sectional area (CSA), endocortical or inner diameter (ID), outer diameter (OD) buckling ratio (BR) and section modulus (Z). Genotyping of 731 highly polymorphic microsatellite markers (average spacing of 5.4 cM) and autosome-wide multipoint linkage analysis was performed.

RESULTS

The heritability of HSA-derived hip phenotypes ranged from 40 to 84%. In the group as a whole, autosome-wide linkage analysis suggested evidence of linkage for QTLs related to NN_Z on chromosome 1p36 (LOD=2.36). In subgroup analysis, ten additional suggestive regions of linkage were found on chromosomes 1, 2, 5, 6, 11, 12, 14, 15 and 17, all with LOD>2.3 except for our linkage at 17q11.2-13 for men and women age 50 and under for NN_CSA, which had a lower LOD of 2.16, but confirmed a previous linkage report.

CONCLUSIONS

We found HSA-derived measures of hip structure to be highly heritable independent of BMD. No strong evidence of linkage was found for any phenotype. Confirmatory evidence of linkage was found on chromosome 17q11.2-12 for NN_CSA. Modest evidence was found for genes affecting hip structural phenotypes at ten other chromosomal locations.

Genetics of the musculoskeletal system: a pleiotropic approach

The risk of osteoporotic fracture can be viewed as a function of loading conditions and the ability of the bone to withstand the load. Skeletal loads are dominated by muscle action. Recently, it has become clear that bone and muscle share genetic determinants. Involution of the musculoskeletal system manifests as bone loss (osteoporosis) and muscle wasting (sarcopenia). Therefore, the consideration of pleiotropy is an important aspect in the study of the genetics of osteoporosis and sarcopenia. This Perspective will provide the evidence for a shared genetic influence on bone and muscle. We will start with an overview of accumulating evidence that physical exercise produces effects on the adult skeleton, seeking to unravel some of the contradictory findings published thus far. We will provide indications that there are pleiotropic relationships between bone structure/mass and muscle mass/function. Finally, we will offer some insights and practical recommendations as to the value of studying shared genetic factors and will explore possible directions for future research. We consider several related questions that together comprise the general paradigm of bone responses to mechanical loading and the relationship between muscle strength and bone parameters, including the genetic factors that modulate these responses. We believe that further progress in understanding the common genetic etiology of osteoporosis and sarcopenia will provide valuable insight into important biological underpinnings for both conditions and may translate into new approaches to reduce the burdens of both conditions through improved diagnosis, prevention, and early targeted treatment.

Contribution of gender-specific genetic factors to osteoporosis risk

Common diseases result from the complex relationship between genetic and environmental factors. The aim of this review is to provide perspective for a conceptual framework aimed at studying the interplay of gender-specific genetic and environmental factors in the etiology of complex disease, using osteoporosis as an example. In recent years, gender differences in the heritability of the osteoporosis-related phenotypes have been reported and sex-specific quantitative-trait loci were discovered by linkage studies in humans and mice. Results of numerous allelic association studies also differed by gender. In most cases, it was not clear whether or not this phenomenon should be attributed to the effect of sex-chromosomes, sex hormones, or other intrinsic or extrinsic differences between the genders, such as the level of bioavailable estrogen and of physical activity. We conclude that there is need to consider gender-specific genetic and environmental factors in the planning of future association studies on the etiology of osteoporosis and other complex diseases prevalent in the general population.

Genome-wide association with bone mass and geometry in the Framingham Heart Study

BACKGROUND

Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms.

METHODS

We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study (FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density (BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation (GEE) and family-based association tests (FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates > or =80%, HWE p > or = 0.001, and MAF > or =10% in up to 1141 phenotyped individuals (495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers.

RESULTS

Heritability estimates for all bone phenotypes were 30-66%. LOD scores > or =3.0 were found on chromosomes 15 (1.5 LOD confidence interval: 51,336,679-58,934,236 bp) and 22 (35,890,398-48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 x 10(-6) and 2.5 x 10(-5), respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits (including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association (FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR; rs1884052 and rs3778099 in ESR1; rs4988300 in LRP5; rs2189480 in VDR; rs2075555 in COLIA1; rs10519297 and rs2008691 in CYP19, as well as SNPs in PPARG (rs10510418 and rs2938392) and ANKH (rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.

CONCLUSION

The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.

Bivariate linkage study of proximal hip geometry and body size indices: the Framingham study

Femoral geometry and body size are both characterized by substantial heritability. The purpose of this study was to discern whether hip geometry and body size (height and body mass index, BMI) share quantitative trait loci (QTL). Dual-energy X-ray absorptiometric scans of the proximal femur from 1,473 members in 323 pedigrees (ages 31-96 years) from the Framingham Osteoporosis Study were studied. We measured femoral neck length, neck-shaft angle, subperiosteal width (outer diameter), cross-sectional bone area, and section modulus, at the narrowest section of the femoral neck (NN), intertrochanteric (IT), and femoral shaft (S) regions. In variance component analyses, genetic correlations (rho ( G )) between hip geometry traits and height ranged 0.30-0.59 and between hip geometry and BMI ranged 0.11-0.47. In a genomewide linkage scan with 636 markers, we obtained nominally suggestive linkages (bivariate LOD scores > or =1.9) for geometric traits and either height or BMI at several chromosomes (4, 6, 9, 15, and 21). Two loci, on chr. 2 (80 cM, BMI/shaft section modulus) and chr. X (height/shaft outer diameter), yielded bivariate LOD scores > or =3.0; although these loci were linked in univariate analyses with a geometric trait, neither was linked with either height or BMI. In conclusion, substantial genetic correlations were found between the femoral geometric traits, height and BMI. Linkage signals from bivariate linkage analyses of bone geometric indices and body size were similar to those obtained in univariate linkage analyses of femoral geometric traits, suggesting that most of the detected QTL primarily influence geometry of the hip.

Bivariate whole genome linkage analysis for femoral neck geometric parameters and total body lean mass

A genome-wide bivariate analysis was conducted for femoral neck GPs and TBLM in a large white sample. We found QTLs shared by GPs and TBLM in the total sample and the sex-specific samples. QTLs with potential pleiotropy were also disclosed.

INTRODUCTION

Previous studies have suggested that femoral neck cross-section geometric parameters (FNCS-GPs), including periosteal diameter (W), cross-sectional area (CSA), cortical thickness (CT), buckling ratio (BR), and section modulus (Z), are genetically correlated with total body lean mass (TBLM). However, the shared genetic factors between them are unknown.

MATERIALS AND METHODS

To identify the specific QTLs shared by FNCS-GPs and TBLM, we performed bivariate whole genome linkage analysis (WGLA) in a large sample of 451 white families made up of 4498 subjects.

RESULTS

Multipoint bivariate linkage analyses for 22 autosomes showed evidence of suggestive or significant linkages (thresholds of LOD = 2.3 and 3.7, respectively) to chromosomes 3q12 and 20q13 in the entire sample, 6p25 and 10q24 in women, and 4p15, 5q34-35 and 7q21 in men. Two-point linkage analyses for chromosome X showed strong linkage to Xp22.13, Xp11.4, Xq22.3, Xq23-24, and Xq25. Complete pleiotropy was identified on 10q24 and 5q35 for TBLM and BR in women and for TBLM and CT in men, respectively. Furthermore, chromosomes 5q34-35, 7q21, 10q24, 20q13, Xp22.13, Xp11.4, and Xq25 are also of importance because of their linkage to multiple trait pairs. For example, linkage to chromosome 10q24 was found for TBLM x W (LOD = 2.31), TBLM x CT (LOD = 2.51), TBLM x CSA (LOD = 2.51), TBLM x BR (LOD = 2.64), and TBLM x Z (LOD = 2.55) in women.

CONCLUSIONS

In this study, we identified several genomic regions (e.g., 3q12 and 20q13) that seem to be linked to both FNCS-GPs and TBLM. These regions are of interesting because they may harbor genes that may contribute to variation in both FNCS-GPs and TBLM.

Proximal hip geometry is linked to several chromosomal regions: genome-wide linkage results from the Framingham Osteoporosis Study

INTRODUCTION

Femoral geometry contributes to bone strength and predicts hip fracture risk. The purpose of this study was to evaluate heritability (h(2)) of geometric indices of the proximal hip and to perform whole-genome linkage analyses of these traits, adjusted for body size.

METHODS

DXA scans of the proximal femur from 1473 members of 323 pedigrees (age range 31-96 years) from the population-based Framingham Osteoporosis Study were obtained. Using the hip structural analysis program, we measured femoral neck length (FNL, cm) and neck-shaft angle (NSA); subperiosteal width (WID, cm), cross-sectional area (CSA, cm(2)); and section modulus (Z, cm(3)) at the narrowest section of the neck (NN), intertrochanteric (IT) and femoral shaft (S) regions. Linkage analyses were performed for the above indices with a set of 636 markers using variance components maximum likelihood method.

RESULTS

Substantial genetic influences were found for all geometric phenotypes, with h(2) values between 0.28 (NSA) and 0.70 (IT_WID). Adjustment for height and BMI did not alter h(2) of NSA and FNL but decreased h(2) of the cross-sectional indices. We obtained substantial linkage (multipoint LOD >3.0) for S_Z at 2p21 and 21q11 and S_WID at Xq25-q26. Inclusion of height and BMI as covariates resulted in much lower LOD scores for S_Z, whereas linkage signals for S_Z at 4q25, S_CSA at 4q32 and S_CSA and S_Z at 15q21 increased after the adjustment. Linkage of FNL at 1q and 13q, NSA at 2q and NN_WID at 16q did not change after the adjustment.

CONCLUSION

Suggestive linkages of bone geometric indices were found at 1q, 2p, 4q, 13q, 15q and Xq. The identification of significant linkage regions after adjustment for BMI and height may point to QTLs influencing femoral bone geometry independent of body size.

Genetic and environmental correlations between bone geometric parameters and body compositions

The purpose of this study was to determine the genetic and environmental correlations between weight, lean mass and bone geometric parameters (sub-periosteal diameter, W; cross-sectional area, CSA; cortical thickness, CT; section modulus, Z; and buckling ratio, BR) of femoral neck. The sample was composed of 512 Caucasian pedigrees, including 2667 females and 1822 males. Bivariate quantitative genetic analyses were performed to evaluate the genetic (rho(G)), environmental (rho(E)) and phenotypic (rho(P)) correlations between the study traits. Univariate genetic analyses showed that the heritabilities (h(2)) for bone geometric parameters were significant (P < 0.001) ranging from 0.50 to 0.60. The significant common household effects indicated the common environment shared by household members for W, CSA, CT, Z and BR (P < 0.05), but the magnitude was small compared with heritabilities. rho(E), rho(G) and rho(P) between bone geometric parameters and weight, lean mass were generally significant. Interestingly, lean mass showed both stronger genetic and environmental correlations with the bone geometric parameters than weight. In addition, according to the magnitude of correlation coefficients, the rho(G) between body compositions and bone geometric parameters were generally stronger than rho(E) (except for that between BR and body compositions). These data suggested that the geometric parameters of femoral neck are under strong genetic control. Furthermore, some common genetic and environmental factors are shared by bone geometric parameters and weight, lean mass. The results may help understand the intertwined relationships between bone metabolisms, mechanical loading and body compositions.

Genome-wide scan identified QTLs underlying femoral neck cross-sectional geometry that are novel studied risk factors of osteoporosis

A genome-wide screen was conducted using a large white sample to identify QTLs for FNCS geometry. We found significant linkage of FNCS parameters to 20q12 and Xq25, plus significant epistatic interactions and sex-specific QTLs influencing FNCS geometry variation.

INTRODUCTION

Bone geometry, a highly heritable trait, is a critical component of bone strength that significantly determines osteoporotic fracture risk. Specifically, femoral neck cross-sectional (FNCS) geometry is significantly associated with hip fracture risk as well as genetic factors. However, genetic research in this respect is still in its infancy.

MATERIALS AND METHODS

To identify the underlying genomic regions influencing FNCS variables, we performed a remarkably large-scale whole genome linkage scan involving 3998 individuals from 434 pedigrees for four FNCS geometry parameters, namely buckling ratio (BR), cross-sectional area (CSA), cortical thickness (CT), and section modulus (Z). The major statistical approach adopted is the variance component method implemented in SOLAR.

RESULTS

Significant linkage evidence (threshold LOD = 3.72 after correction for tests of multiple phenotypes) was found in the regions of 20q12 and Xq25 for CT (LOD = 4.28 and 3.90, respectively). We also identified eight suggestive linkage signals (threshold LOD = 2.31 after correction for multiple tests) for the respective geometry traits. The above findings were supported by principal component linkage analysis. Of them, 20q12 was of particular interest because it was linked to multiple FNCS geometry traits and significantly interacted with five other genomic loci to influence CSA variation. The effects of 20q12 on FNCS geometry were present in both male and female subgroups. Subgroup analysis also revealed the presence of sex-specific quantitative trait loci (QTLs) for FNCS traits in the regions such as 2p14, 3q26, 7q21 and 15q21.

CONCLUSIONS

Our findings laid a foundation for further replication and fine-mapping studies as well as for positional and functional candidate gene studies, aiming at eventually finding the causal genetic variants and hidden mechanisms concerning FNCS geometry variation and the associated hip fractures.

Genetic determination and correlation of body weight and body mass index (BMI) and cross-sectional geometric parameters of the femoral neck

INTRODUCTION

This study aimed to examine the genetic determination of body weight, body mass index (BMI) and cross-sectional geometric parameters of the femoral neck including cross-sectional area (CSA), cortical thickness (CT), sectional modulus (Z), and buckling ratio (BR), and to test the genetic correlation between body weight/BMI and the femoral neck geometric parameters.

METHODS

A total of 929 healthy subjects from 292 Chinese nuclear families was included. Femoral neck geometric parameters were estimated from bone mineral density (BMD) and bone area which were measured by dual energy X-ray absorptiometry (DXA).

RESULTS

The heritability (h(2)) estimate values were 0.643, 0.626, 0.626, 0.674, 0.405, and 0.615 for body weight, BMI, CSA, CT, Z, and BR, respectively. Body weight was significantly correlated with bone geometric parameters (p</=0.001) with genetic correlation (rho(G)) values of 0.551, 0.457, 0.571, and -0.385, and bivariate heritability (rho2G) values of 0.304, 0.209, 0.326, and 0.148 for CSA, CT, Z, and BR, respectively. Similar correlations (p</=0.001) were observed between BMI and bone geometric parameters, with rho(G) values of 0.446, 0.432, 0.334, and -0.362, and (rho2G) values of 0.199, 0.187, 0.112, and 0.131 for CSA, CT, Z, and BR, respectively.

CONCLUSION

In summary, our study suggested that body weight, BMI, and femoral neck geometry were under strong genetic determination. The strong genetic correlations suggested that the genetic factors of bone geometry may be overlapped with those of body weight and BMI.