Quantitative trait loci analysis of structural and material skeletal phenotypes in C57BL/6J and DBA/2 second-generation and recombinant inbred mice

Cortical bone relationships are maintained regardless of sex and diet in a large population of LGXSM advanced intercross mice

Introduction

Knowledge of bone structure-function relationships in mice has been based on relatively small sample sets that limit generalizability. We sought to investigate structure-function relationships of long bones from a large population of genetically diverse mice. Therefore, we analyzed previously published data from the femur and radius of male and female mice from the F34 generation of the Large-by-Small advanced intercross line (LGXSM AI), which have over a two-fold continuous spread of bone and body sizes (Silva et al. 2019 JBMR).

Methods

Morphological traits, mechanical properties, and estimated material properties were collected from the femur and radius from 1113 LGXSM AI adult mice (avg. age 25 wks). Males and females fed a low-fat or high-fat diet were evaluated to increase population variation. The data were analyzed using principal component analysis (PCA), Pearson's correlation, and multivariate linear regression.

Results

Using PCA groupings and hierarchical clustering, we identified a reduced set of traits that span the population variation and are relatively independent of each other. These include three morphometry parameters (cortical area, medullary area, and length), two mechanical properties (ultimate force and post-yield displacement), and one material property (ultimate stress). When comparing traits of the femur to the radius, morphological traits are moderately well correlated (r²: 0.18-0.44) and independent of sex and diet. However, mechanical and material properties are weakly correlated or uncorrelated between the long bones. Ultimate force can be predicted from morphology with moderate accuracy for both long bones independent of variations due to genetics, sex, or diet; however, predictions miss up to 50 % of the variation in the population. Estimated material properties in the femur are moderately to strongly correlated with bone size parameters, while these correlations are very weak in the radius.

Discussion

Our results indicate that variation in cortical bone phenotype in the F34 LGXSM AI mouse population can be adequately described by a reduced set of bone traits. These traits include cortical area, medullary area, bone length, ultimate force, post-yield displacement, and ultimate stress. The weak correlation of mechanical and material properties between the femur and radius indicates that the results from routine three-point bending tests of one long bone (e.g., femur) may not be generalizable to another long bone (e.g., radius). Additionally, these properties could not be fully predicted from bone morphology alone, confirming the importance of mechanical testing. Finally, material properties of the femur estimated based on beam theory equations showed a strong dependence on geometry that was not seen in the radius, suggesting that differences in femur size within a study may confound interpretation of estimated material properties.

Genetics of Skeletal Evolution in Unusually Large Mice from Gough Island

Organisms on islands often undergo rapid morphological evolution, providing a platform for understanding mechanisms of phenotypic change. Many examples of evolution on islands involve the vertebrate skeleton. Although the genetic basis of skeletal variation has been studied in laboratory strains, especially in the house mouse Mus musculus domesticus, the genetic determinants of skeletal evolution in natural populations remain poorly understood. We used house mice living on the remote Gough Island-the largest wild house mice on record-to understand the genetics of rapid skeletal evolution in nature. Compared to a mainland reference strain from the same subspecies (WSB/EiJ), the skeleton of Gough Island mice is considerably larger, with notable expansions of the pelvis and limbs. The Gough Island mouse skeleton also displays changes in shape, including elongations of the skull and the proximal vs. distal elements in the limbs. Quantitative trait locus (QTL) mapping in a large F₂ intercross between Gough Island mice and WSB/EiJ reveals hundreds of QTL that control skeletal dimensions measured at 5, 10, and/or 16 weeks of age. QTL exhibit modest, mostly additive effects, and Gough Island alleles are associated with larger skeletal size at most QTL. The QTL with the largest effects are found on a few chromosomes and affect suites of skeletal traits. Many of these loci also colocalize with QTL for body weight. The high degree of QTL colocalization is consistent with an important contribution of pleiotropy to skeletal evolution. Our results provide a rare portrait of the genetic basis of skeletal evolution in an island population and position the Gough Island mouse as a model system for understanding mechanisms of rapid evolution in nature.

Genetic perturbations that impair functional trait interactions lead to reduced bone strength and increased fragility in mice

Functional adaptation may complicate the choice of phenotype used in genetic studies that seek to identify genes contributing to fracture susceptibility. Often, genetic variants affecting one trait are compensated by coordinated changes in other traits. Bone fracture is a prototypic example because mechanical function of long bones (stiffness and strength) depends on how the system coordinately adjusts the amount (cortical area) and quality (tissue-mineral density, TMD) of bone tissue to mechanically offset the natural variation in bone robustness (total area/length). We propose that efforts aimed at identifying genes regulating fracture resistance will benefit from better understanding how functional adaptation contributes to the genotype-phenotype relationship. We analyzed the femurs of C57BL/6J-Chr(A/J)/NaJ Chromosome Substitution Strains (CSSs) to systemically interrogate the mouse genome for chromosomes harboring genes that regulate mechanical function. These CSSs (CSS-i, i=the substituted chromosome) showed changes in mechanical function on the order of -26.6 to +11.5% relative to the B6 reference strain after adjusting for body size. Seven substitutions showed altered robustness, cortical area, or TMD, but no effect on mechanical function (CSS-4, 5, 8, 9, 17, 18, 19); six substitutions showed altered robustness, cortical area, or TMD, and reduced mechanical function (CSS-1, 2, 6, 10, 12, 15); and one substitution also showed reduced mechanical function but exhibited no significant changes in the three physical traits analyzed in this study (CSS-3). A key feature that distinguished CSSs that maintained function from those with reduced function was whether the system adjusted cortical area and TMD to the levels needed to compensate for the natural variation in bone robustness. These results provide a novel biomechanical mechanism linking genotype with phenotype, indicating that genes control function not only by regulating individual traits, but also by regulating how the system coordinately adjusts multiple traits to establish function.

Impact of the environment on the skeleton: is it modulated by genetic factors?

The etiology of skeletal disease is driven by genetic and environmental factors. Genome-wide association studies (GWAS) of osteoporotic phenotypes have identified novel candidate genes, but have only uncovered a small proportion of the trait variance explained. This "missing heritability" is caused by several factors, including the failure to consider gene-by-environmental (G*E) interactions. Some G*E interactions have been investigated, but new approaches to integrate environmental data into genomic studies are needed. Advances in genotyping and meta-analysis techniques now allow combining genotype data from multiple studies, but the measurement of key environmental factors in large human cohorts still lags behind, as do the statistical tools needed to incorporate these measures in genome-wide association meta-studies. This review focuses on discussing ways to enhance G*E interaction studies in humans and how the use of rodent models can inform genetic studies. Understanding G*E interactions will provide opportunities to effectively target intervention strategies for individualized therapy.

Rare coding variants in ALPL are associated with low serum alkaline phosphatase and low bone mineral density

Alkaline phosphatase (ALP) plays an essential role in the regulation of tissue mineralization, and its activity is highly heritable. Guided by genetic associations discovered in a murine model, we hypothesized a role for rare coding variants in determining serum ALP level and bone mineral density (BMD) in humans. We sequenced the coding regions of the ALP gene (ALPL) in men with low and normal serum ALP activity levels. Single-nucleotide ALPL variants, including 19 rare nonsynonymous variants (minor allele frequency <1%), were much more frequent among the low ALP group (33.8%) than the normal group (1.4%, p = 1 × 10(-11)). Within the low ALP group, men with a rare, nonsynonymous variant had 11.2% lower mean serum ALP (p = 3.9 × 10(-4)), 6.7% lower BMD (p = 0.03), and 11.1% higher serum phosphate (p = 0.002) than those without. In contrast, common nonsynonymous variants had no association with serum ALP, phosphate, or BMD. Multiple rare ALPL coding variants are present in the general population, and nonsynonymous coding variants may be responsible for heritable differences in mineralization and thus BMD.

Whole bone mechanics and bone quality

BACKGROUND

The skeleton plays a critical structural role in bearing functional loads, and failure to do so results in fracture. As we evaluate new therapeutics and consider treatments to prevent skeletal fractures, understanding the basic mechanics underlying whole bone testing and the key principles and characteristics contributing to the structural strength of a bone is critical.

QUESTIONS/PURPOSES

We therefore asked: (1) How are whole bone mechanical tests performed and what are the key outcomes measured? (2) How do the intrinsic characteristics of bone tissue contribute to the mechanical properties of a whole bone? (3) What are the effects of extrinsic characteristics on whole bone mechanical behavior? (4) Do environmental factors affect whole bone mechanical properties?

METHODS

We conducted a PubMed search using specific search terms and limiting our included articles to those related to in vitro testing of whole bones. Basic solid mechanics concepts are summarized in the context of whole bone testing and the determinants of whole bone behavior.

RESULTS

Whole bone mechanical tests measure structural stiffness and strength from load-deformation data. Whole bone stiffness and strength are a function of total bone mass and the tissue geometric distribution and material properties. Age, sex, genetics, diet, and activity contribute to bone structural performance and affect the incidence of skeletal fractures.

CONCLUSIONS

Understanding and preventing skeletal fractures is clinically important. Laboratory tests of whole bone strength are currently the only measures for in vivo fracture prediction. In the future, combined imaging and engineering models may be able to predict whole bone strength noninvasively.

Linkage mapping of principal components for femoral biomechanical performance in a reciprocal HCB-8 × HCB-23 intercross

Studies of bone genetics have addressed an array of related phenotypes, including various measures of biomechanical performance, bone size, bone, shape, and bone mineral density. These phenotypes are not independent, resulting in redundancy of the information they provide. Principal component (PC) analysis transforms multiple phenotype data to a new set of orthogonal "synthetic" phenotypes. We performed PC analysis on 17 femoral biomechanical, anatomic, and body size phenotypes in a reciprocal intercross of HcB-8 and HcB-23, accounting for 80% of the variance in 4 PCs. Three of the 4 PCs were mapped in the cross. The linkage analysis revealed a quantitative trait locus (QTL) with LOD = 4.7 for PC2 at 16 cM on chromosome 19 that was not detected using the directly measured phenotypes. The chromosome 19 QTL falls within a ~10 megabase interval, with Osf1 as a positional candidate gene. PC QTLs were also found on chromosomes 1, 2, 4, 6, and 10 that coincided with those identified for directly measured or calculated material property phenotypes. The novel chromosome 19 QTL illustrates the power advantage that attends use of PC phenotypes for linkage mapping. Constraint of the chromosome 19 candidate interval illustrates an important advantage of experimental crosses between recombinant congenic mouse strains.

Genetically determined phenotype covariation networks control bone strength

To identify genes affecting bone strength, we studied how genetic variants regulate components of a phenotypic covariation network that was previously shown to accurately characterize the compensatory trait interactions involved in functional adaptation during growth. Quantitative trait loci (QTLs) regulating femoral robustness, morphologic compensation, and mineralization (tissue quality) were mapped at three ages during growth using AXB/BXA Recombinant Inbred (RI) mouse strains and adult B6-i(A) Chromosome Substitution Strains (CSS). QTLs for robustness were identified on chromosomes 8, 12, 18, and 19 and confirmed at all three ages, indicating that genetic variants established robustness postnatally without further modification. A QTL for morphologic compensation, which was measured as the relationship between cortical area and body weight, was identified on chromosome 8. This QTL limited the amount of bone formed during growth and thus acted as a setpoint for diaphyseal bone mass. Additional QTLs were identified from the CSS analysis. QTLs for robustness and morphologic compensation regulated bone structure independently (ie, in a nonpleiotropic manner), indicating that each trait may be targeted separately to individualize treatments aiming to improve strength. Multiple regression analyses showed that variation in morphologic compensation and tissue quality, not bone size, determined femoral strength relative to body weight. Thus an individual inheriting slender bones will not necessarily inherit weak bones unless the individual also inherits a gene that impairs compensation. This systems genetic analysis showed that genetically determined phenotype covariation networks control bone strength, suggesting that incorporating functional adaptation into genetic analyses will advance our understanding of the genetic basis of bone strength.

Linkage mapping of femoral material properties in a reciprocal intercross of HcB-8 and HcB-23 recombinant mouse strains

Skeletal fragility is an important health problem with a large genetic component. We performed a 603 animal F2 reciprocal intercross of the recombinant congenic strains HcB-8 and HcB-23 to genetically map quantitative trait loci (QTLs) for tissue-level femoral biomechanical performance. These included elastic and post-yield strain, Young's modulus, elastic and maximum stress, and toughness and were calculated from 3-point bend testing of femora by the application of standard beam equations. We mapped these with R/qtl and QTL Cartographer and established significance levels empirically by permutation testing. Significant QTLs for at least one trait are present on chromosomes 1, 6, and 10 in the full F2 population, with additional QTLs evident in subpopulations defined by sex and cross direction. On chromosome 10, we find a QTL for post-yield strain and toughness, phenotypes that have not been mapped previously. Notably, the HcB-8 allele at this QTL increases post-yield strain and toughness, but decreases bone mineral density (BMD), while the material property QTLs on chromosomes 1, 6, and at a second chromosome 10 QTL are independent of BMD. We find significant sex x QTL and cross direction x QTL interactions. A robust, pleiotropic chromosome 4 QTL that we previously reported at the whole-bone level showed no evidence of linkage at the tissue-level, supporting our interpretation that modeling capacity is its primary phenotype. Our data demonstrate an inverse relationship between femoral perimeter and Young's modulus, with R(2)=0.27, supporting the view that geometric and material bone properties are subject to an integrated set of regulatory mechanisms. Mapping QTLs for tissue-level biomechanical performance advances understanding of the genetic basis of bone quality.

Variation in within-bone stiffness measured by nanoindentation in mice bred for high levels of voluntary wheel running

The hierarchical structure of bone, involving micro-scale organization and interaction of material components, is a critical determinant of macro-scale mechanics. Changes in whole-bone morphology in response to the actions of individual genes, physiological loading during life, or evolutionary processes, may be accompanied by alterations in underlying mineralization or architecture. Here, we used nanoindentation to precisely measure compressive stiffness in the femoral mid-diaphysis of mice that had experienced 37 generations of selective breeding for high levels of voluntary wheel running (HR). Mice (n = 48 total), half from HR lines and half from non-selected control (C) lines, were divided into two experimental groups, one with 13-14 weeks of access to a running wheel and one housed without wheels (n = 12 in each group). At the end of the experiment, gross and micro-computed tomography (microCT)-based morphometric traits were measured, and reduced elastic modulus (E(r)) was estimated separately for four anatomical quadrants of the femoral cortex: anterior, posterior, lateral, and medial. Two-way, mixed-model analysis of covariance (ancova) showed that body mass was a highly significant predictor of all morphometric traits and that structural change is more apparent at the microCT level than in conventional morphometrics of whole bones. Both line type (HR vs. C) and presence of the mini-muscle phenotype (caused by a Mendelian recessive allele and characterized by a approximately 50% reduction in mass of the gastrocnemius muscle complex) were significant predictors of femoral cortical cross-sectional anatomy. Measurement of reduced modulus obtained by nanoindentation was repeatable within a single quadrant and sensitive enough to detect inter-individual differences. Although we found no significant effects of line type (HR vs. C) or physical activity (wheel vs. no wheel) on mean stiffness, anterior and posterior quadrants were significantly stiffer (P < 0.0001) than medial and lateral quadrants (32.67 and 33.09 GPa vs. 29.78 and 30.46 GPa, respectively). Our findings of no significant difference in compressive stiffness in the anterior and posterior quadrants agree with previous results for mice, but differ from those for large mammals. Integrating these results with others from ongoing research on these mice, we hypothesize that the skeletons of female HR mice may be less sensitive to the effects of chronic exercise, due to decreased circulating leptin levels and potentially altered endocannabinoid signaling.

Bone, muscle, and physical activity: structural equation modeling of relationships and genetic influence with age

Correlations among bone strength, muscle mass, and physical activity suggest that these traits may be modulated by each other and/or by common genetic and/or environmental mechanisms. This study used structural equation modeling (SEM) to explore the extent to which select genetic loci manifest their pleiotropic effects through functional adaptations commonly referred to as Wolff's law. Quantitative trait locus (QTL) analysis was used to identify regions of chromosomes that simultaneously influenced skeletal mechanics, muscle mass, and/or activity-related behaviors in young and aged B6xD2 second-generation (F(2)) mice of both sexes. SEM was used to further study relationships among select QTLs, bone mechanics, muscle mass, and measures of activity. The SEM approach provided the means to numerically decouple the musculoskeletal effects of mechanical loading from the effects of other physiological processes involved in locomotion and physical activity. It was found that muscle mass was a better predictor of bone mechanics in young females, whereas mechanical loading was a better predictor of bone mechanics in older females. An activity-induced loading factor positively predicted the mechanical behavior of hindlimb bones in older males; contrarily, load-free locomotion (i.e., the remaining effects after removing the effects of loading) negatively predicted bone performance. QTLs on chromosomes 4, 7, and 9 seem to exert some of their influence on bone through actions consistent with Wolff's Law. Further exploration of these and other mechanisms through which genes function will aid in development of individualized interventions able to exploit the numerous complex pathways contributing to skeletal health.

Systems analysis of bone

The genetic variants contributing to variability in skeletal traits has been well studied, and several hundred QTLs have been mapped and several genes contributing to trait variation have been identified. However, many questions remain unanswered. In particular, it is unclear whether variation in a single gene leads to alterations in function. Bone is a highly adaptive system and genetic variants affecting one trait are often accompanied by compensatory changes in other traits. The functional interactions among traits, which is known as phenotypic integration, has been observed in many biological systems, including bone. Phenotypic integration is a property of bone that is critically important for establishing a mechanically functional structure that is capable of supporting the forces imparted during daily activities. In this paper, bone is reviewed as a system and primarily in the context of functionality. A better understanding of the system properties of bone will lead to novel targets for future genetic analyses and the identification of genes that are directly responsible for regulating bone strength. This systems analysis has the added benefit of leaving a trail of valuable information about how the skeletal system works. This information will provide novel approaches to assessing skeletal health during growth and aging and for developing novel treatment strategies to reduce the morbidity and mortality associated with fragility fractures.

Phenotypic integration among trabecular and cortical bone traits establishes mechanical functionality of inbred mouse vertebrae

Conventional approaches to identifying quantitative trait loci (QTLs) regulating bone mass and fragility are limited because they examine cortical and trabecular traits independently. Prior work examining long bones from young adult mice and humans indicated that skeletal traits are functionally related and that compensatory interactions among morphological and compositional traits are critical for establishing mechanical function. However, it is not known whether trait covariation (i.e., phenotypic integration) also is important for establishing mechanical function in more complex, corticocancellous structures. Covariation among trabecular, cortical, and compositional bone traits was examined in the context of mechanical functionality for L(4) vertebral bodies across a panel of 16-wk-old female AXB/BXA recombinant inbred (RI) mouse strains. The unique pattern of randomization of the A/J and C57BL/6J (B6) genome among the RI panel provides a powerful tool that can be used to measure the tendency for different traits to covary and to study the biology of complex traits. We tested the hypothesis that genetic variants affecting vertebral size and mass are buffered by changes in the relative amounts of cortical and trabecular bone and overall mineralization. Despite inheriting random sets of A/J and B6 genomes, the RI strains inherited nonrandom sets of cortical and trabecular bone traits. Path analysis, which is a multivariate analysis that shows how multiple traits covary simultaneously when confounding variables like body size are taken into consideration, showed that RI strains that tended to have smaller vertebrae relative to body size achieved mechanical functionality by increasing mineralization and the relative amounts of cortical and trabecular bone. The interdependence among corticocancellous traits in the vertebral body indicated that variation in trabecular bone traits among inbred mouse strains, which is often thought to arise from genetic factors, is also determined in part by the adaptive response to variation in traits describing the cortical shell. The covariation among corticocancellous traits has important implications for genetic analyses and for interpreting the response of bone to genetic and environmental perturbations.

Replication of long-bone length QTL in the F9-F10 LG,SM advanced intercross

Quantitative trait locus (QTL) mapping techniques are frequently used to identify genomic regions associated with variation in phenotypes of interest. However, the F(2) intercross and congenic strain populations usually employed have limited genetic resolution resulting in relatively large confidence intervals that greatly inhibit functional confirmation of statistical results. Here we use the increased resolution of the combined F(9) and F(10) generations (n = 1455) of the LG,SM advanced intercross to fine-map previously identified QTL associated with the lengths of the humerus, ulna, femur, and tibia. We detected 81 QTL affecting long-bone lengths. Of these, 49 were previously identified in the combined F(2)-F(3) population of this intercross, while 32 represent novel contributors to trait variance. Pleiotropy analysis suggests that most QTL affect three to four long bones or serially homologous limb segments. We also identified 72 epistatic interactions involving 38 QTL and 88 novel regions. This analysis shows that using later generations of an advanced intercross greatly facilitates fine-mapping of confidence intervals, resolving three F(2)-F(3) QTL into multiple linked loci and narrowing confidence intervals of other loci, as well as allowing identification of additional QTL. Further characterization of the biological bases of these QTL will help provide a better understanding of the genetics of small variations in long-bone length.

Pleiotropic patterns of quantitative trait loci for 70 murine skeletal traits

Quantitative trait locus (QTL) studies of a skeletal trait or a few related skeletal components are becoming commonplace, but as yet there has been no investigation of pleiotropic patterns throughout the skeleton. We present a comprehensive survey of pleiotropic patterns affecting mouse skeletal morphology in an intercross of LG/J and SM/J inbred strains (N = 1040), using QTL analysis on 70 skeletal traits. We identify 798 single-trait QTL, coalescing to 105 loci that affect on average 7-8 traits each. The number of traits affected per locus ranges from only 1 trait to 30 traits. Individual traits average 11 QTL each, ranging from 4 to 20. Skeletal traits are affected by many, small-effect loci. Significant additive genotypic values average 0.23 standard deviation (SD) units. Fifty percent of loci show codominance with heterozygotes having intermediate phenotypic values. When dominance does occur, the LG/J allele tends to be dominant to the SM/J allele (30% vs. 8%). Over- and underdominance are relatively rare (12%). Approximately one-fifth of QTL are sex specific, including many for pelvic traits. Evaluating the pleiotropic relationships of skeletal traits is important in understanding the role of genetic variation in the growth and development of the skeleton.

Identification of quantitative trait loci affecting murine long bone length in a two-generation intercross of LG/J and SM/J Mice

INTRODUCTION

Study of mutations with large phenotypic effects has allowed the identification of key players in skeletal development. However, the molecular nature of variation in large, phenotypically normal populations tends to be characterized by smaller phenotypic effects that remain undefined.

MATERIALS AND METHODS

We use interval mapping and quantitative trait locus (QTL) mapping techniques in the combined F2-F3 populations (n = 2111) of an LG/J x SM/J mouse intercross to detect QTLs associated with the lengths of the humerus, ulna, femur, and tibia.

RESULTS

Seventy individual trait QTLs affecting long bone lengths were detected, with several chromosomes harboring multiple QTLs. The genetic architecture suggests mainly small, additive effects on long bone length, with roughly one third of the QTLs displaying dominance. Sex interactions were common, and four sex-specific QTLs were observed. Pleiotropy could not be rejected for most of the QTLs identified. Thirty-one epistatic interactions were detected, almost all affecting regions including or immediately adjacent to QTLs.

CONCLUSIONS

A complex regulatory network with many gene interactions modulates bone growth, possibly with integrated skeletal modules that allow fine-tuning of developmental processes present. Candidate genes in the QTL CIs include many genes known to affect endochondral bone growth and genes that have not yet been associated with bone growth or body size but have a strong potential to influence these traits.

Genetic analysis of craniofacial traits in the medaka

Family and twin studies suggest that a substantial genetic component underlies individual differences in craniofacial morphology. In the current study, we quantified 444 craniofacial traits in 100 individuals from two inbred medaka (Oryzias latipes) strains, HNI and Hd-rR. Relative distances between defined landmarks were measured in digital images of the medaka head region. A total of 379 traits differed significantly between the two strains, indicating that many craniofacial traits are controlled by genetic factors. Of these, 89 traits were analyzed via interval mapping of 184 F(2) progeny from an intercross between HNI and Hd-rR. We identified quantitative trait loci for 66 craniofacial traits. The highest logarithm of the odds score was 6.2 for linkage group (LG) 9 and 11. Trait L33, which corresponds to the ratio of head length to head height at eye level, mapped to LG9; trait V15, which corresponds to the ratio of snout length to head width measured behind the eyes, mapped to LG11. Our initial results confirm the potential of the medaka as a model system for the genetic analysis of complex traits such as craniofacial morphology.

Bone microstructure and its associated genetic variability in 12 inbred mouse strains: microCT study and in silico genome scan

MicroCT analysis of 12 inbred strains of mice identified 5 novel chromosomal regions influencing skeletal phenotype. Bone morphology varied in a compartment- and site-specific fashion across strains and genetic influences contributed to the morphometric similarities observed in femoral and vertebral bone within the trabecular bone compartment.

INTRODUCTION

Skeletal development is known to be regulated by both heritable and environmental factors, but whether genetic influence on peak bone mass is site- or compartment-specific is unknown. This study examined the genetic variation of cortical and trabecular bone microarchitecture across 12 strains of mice.

MATERIALS AND METHODS

MicroCT scanning was used to measure trabecular and cortical bone morphometry in the femur and vertebra of 12 strains of 4-month-old inbred male mice. A computational genome mapping technique was used to identify chromosomal intervals associated with skeletal traits.

RESULTS

Skeletal microarchitecture varied in a compartment- and site-specific fashion across strains. Genome mapping identified 13 chromosomal intervals associated with skeletal traits and 5 of these intervals were novel. Trabecular microarchitecture in different bone sites correlated across strains and most of the chromosomal intervals associated with these trabecular traits were shared between skeletal sites. Conversely, no chromosomal intervals were shared between the trabecular and cortical bone compartments in the femur, even though there was a strong correlation for these different bone compartments across strains, suggesting site-specific regulation by environmental or intrinsic factors.

CONCLUSION

In summary, these data confirm that there are distinct genetic determinants that define the skeletal phenotype at the time when peak bone mass is being acquired, and that genomic regulation of bone morphology is specific for skeletal compartment.

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.

Fine mapping dissects pleiotropic growth quantitative trait locus into linked loci

A recurring issue in studies of quantitative trait loci (QTLs) is whether QTLs that appear to have pleiotropic effects are indeed caused by pleiotropy at single loci or by linked QTLs. Previous work identified a QTL that affected tail length in mice and the lengths of various bones, including the humerus, ulna, femur, tibia, and mandible. The effect of this QTL on tail length has since been found to be due to multiple linked QTLs and so its apparently pleiotropic effects may have been due to linked QTLs with distinct effects. In the present study we examined a line of mice segregating only for a 0.94-Mb chromosomal region known to contain a subset of the QTLs influencing tail length. We measured a number of skeletal dimensions, including the lengths of the skull, mandible, humerus, ulna, femur, tibia, calcaneus, metatarsus, and a tail bone. The QTL region was found to have effects on the size of the mandible and length of the tail bone, with little or no effect on the other traits. Using a randomization approach, we rejected the null hypothesis that the QTL affected all traits equally, thereby demonstrating that the pleiotropic effects reported earlier were due to linked loci with distinct effects. This result underlines the possibility that seemingly pleiotropic effects of QTLs may frequently be due to linked loci and that high-resolution mapping will often be required to distinguish between pleiotropy and linkage.

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.

Identification of quantitative trait loci affecting body composition in a mouse intercross

Gravimetric analysis and dual energy x-ray absorptiometry densitometry were used to determine lean, fat, and bone tissue traits in a F(2) mouse population from a C57BL/6J and CASA/Rk intercross (B6CASAF2). These traits were used in a linkage analysis to identify quantitative trait loci that affect body composition. Linkage mapping showed that body weight (BW) loci on proximal chromosome 2 occurred in the same region as body length, lean tissue mass, and bone mineral content and on chromosome 13 in the same region as lean tissue mass, bone mineral density, and bone mineral content. Fat-related loci occurring on mid-chromosome 2 near 60 cM, proximal chromosome 6, and mid-chromosome 10 were distinct from BW, lean tissue, and bone tissue loci. In B6CASAF2 females, heterozygotes and CASA/Rk homozygotes at the chromosome 6 locus marker had higher body fat percentages, and this locus was responsible for 11% of the variance for body fat percentage. Female heterozygotes and C57BL/6J homozygotes at the chromosome 15 locus marker had higher bone mineral densities, and this locus could explain 8% of that trait's variance. A survey of the literature did not reveal any previous reports of fat-specific loci in the chromosomal 10 region near 42 cM reported in this study. The results of this study indicate that BW and BMI have limited usefulness as phenotypes in linkage or association studies when used as obesity phenotypes.

A locus on mouse Chromosome 9 (Adip5) affects the relative weight of the gonadal but not retroperitoneal adipose depot

To identify the gene or genes on mouse Chromosome 9 that contribute to strain differences in fatness, we conducted an expanded mapping analysis to better define the region where suggestive linkage was found, using the F(2 )generation of an intercross between the C57BL/6ByJ and 129P3/J mouse strains. Six traits were studied: the summed weight of two adipose depots, the weight of each depot, analyzed individually (the gonadal and retroperitoneal depot), and the weight of each depot (summed and individual) relative to body size. We found significant linkage (LOD = 4.6) that accounted for the relative weight of the summed adipose depots, and another for the relative weight of the gonadal (LOD = 5.3) but not retroperitoneal (LOD = 0.9) adipose depot. This linkage is near marker rs30280752 (61.1 Mb, Build 34) and probably is equivalent to the quantitative trait locus (QTL) Adip5. Because the causal gene is unknown, we identified and evaluated several candidates within the confidence interval with functional significance to the body fatness phenotype (Il18, Acat1, Cyp19a1, Crabp1, Man2c1, Neil1, Mpi1, Csk, Lsm16, Adpgk, Bbs4, Hexa, Thsd4, Dpp8, Anxa2, and Lipc). We conclude that the Adip5 locus is specific to the gonadal adipose depot and that a gene or genes near the linkage peak may account for this QTL.

Quantitative trait loci for individual adipose depot weights in C57BL/6ByJ x 129P3/J F2 mice

To understand how genotype influences fat patterning and obesity, we conducted an autosomal genome scan using male and female F(2) hybrids between the C57BL/6ByJ and 129P3/J parental mouse strains. Mice were studied in middle-adulthood and were fed a low-energy, low-fat diet during their lifetime. We measured the weight of the retroperitoneal adipose depot (near the kidney) and the gonadal adipose depot (near the epididymis in males and ovaries in females). An important feature of the analysis was the comparison of linkage results for absolute adipose depot weight and depot weight adjusted for body size, i.e., relative weight. We detected 67 suggestive linkages for six phenotypes, which fell into one of three categories: those specific to absolute but not relative depot weight (Chr 5, 11, and 14), those specific to relative but not absolute depot weight (Chr 9, 15, and 16), and those involving both (Chr 2 and 7). Some quantitative trait loci (QTLs) affected one adipose depot more than another: Retroperitoneal depot weight was linked to Chr 8, 11, 12, and 17, but the linkage effects for the gonadal depot were stronger for Chr 5, 7, and 9. Several linkages were specific to sex; for instance, the absolute weight of gonadal fat was linked to Chromosome 7 in male (LOD = 3.4) but not female mice (LOD = 0.2). Refining obesity as a phenotype may uncover clues about gene function that will assist in positional cloning efforts.

Femur mechanical properties in the F2 progeny of an NZB/B1NJ x RF/J cross are regulated predominantly by genetic loci that regulate bone geometry

Genetic analysis of an NZB/B1NJ x RF/J cross has identified QTLs for femur mechanical, geometric, and densitometric phenotypes. Most mechanical QTLs were associated with geometric QTLs, strongly suggesting common genetic regulation.

INTRODUCTION

Previous studies have shown that bone architecture and BMD are important factors affecting bone strength, and both are genetically regulated. We conducted genetic analyses for loci regulating femur mechanical properties, geometric properties, and BMD in a cohort of F2 mice derived from intercross matings of (NZB/B1NJ x RF/J)F1 parents.

MATERIALS AND METHODS

Femurs were isolated from 662 10-week-old females. Mechanical properties were determined for a femur from each animal by three-point bending. Geometric properties and volumetric BMD (vBMD) were determined by pQCT. Genotype data were obtained by PCR assays for polymorphic markers carried in the genomic DNA of each mouse. Genome-wide scans were carried out for co-segregation of genetic marker data with values from 23 different phenotypes. Quantitative trait loci (QTLs) were identified for mechanical, geometric, and mineral density phenotypes.

RESULTS

QTLs for many phenotypes were significantly refined by covariate analyses using body weight and femur length. Major QTLs for mechanical and geometric phenotypes were found on chromosomes 5, 7, 9, 11, and 12. Nine chromosomal locations were identified with mechanical QTLs and 17 locations with one or more geometric QTLs. The significance of five mechanical and nine geometric QTLs was affected by the inclusion of covariates. These changes included both decreases and increases in significance. The QTLs on chromosomes 5 and 12 were decreased by inclusion of the covariates in the analysis, but QTLs on 7 and 11 were unaffected. Mechanical QTLs were almost always associated with geometric QTLs and less commonly (two of six) with vBMD QTLs.

CONCLUSIONS

Genetic regulation of mechanical properties in the F(2) mice of this NZB/B1NJ x RF/J cross seems to be caused by genes regulating femur geometry.

Genetics of canid skeletal variation: size and shape of the pelvis

The mammalian skeleton presents an ideal system in which to study the genetic architecture of a set of related polygenic traits and the skeleton of the domestic dog (Canis familiaris) is arguably the best system in which to address the relationship between genes and anatomy. We have analyzed the genetic basis for skeletal variation in a population of >450 Portuguese Water Dogs. At this stage of this ongoing project, we have identified >40 putative quantitative trait loci (QTLs) for heritable skeletal phenotypes located on 22 different chromosomes, including the "X." A striking aspect of these is the regulation of suites of traits representing bones located in different parts of the skeleton but related by function. Here we illustrate this by describing genetic variation in postcranial morphology. Two suites of traits are involved. One regulates the size of the pelvis relative to dimensions of the limb bones. The other regulates the shape of the pelvis. Both are examples of trade-offs that may be prototypical of different breeds. For the size of the pelvis relative to limb bones, we describe four QTLs located on autosome CFA 12, 30, 31, and X. For pelvic shape we describe QTLs on autosome CFA 2, 3, 22, and 36. The relation of these polygenic systems to musculoskeletal function is discussed.

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.

Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression.

INTRODUCTION

Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass.

MATERIALS AND METHODS

Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F(2)) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined.

RESULTS AND CONCLUSIONS

The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted phenotypes. Identifying QTLs that exert their effects on skeletal phenotypes through body size-related pathways as well as those having a more direct and independent influence on bone are equally important in deciphering the complex physiologic pathways responsible for the maintenance of bone health.