A genome wide linkage scan of metacarpal size and geometry in the Framingham Study

Novel candidate genes putatively involved in stress fracture predisposition detected by whole-exome sequencing

While genetic factors in all likelihood contribute to stress fracture (SF) pathogenesis, a few studies focusing on candidate genes have previously been reported. The objective of this study is to gain better understanding on the genetic basis of SF in a gene-naive manner. Exome sequence capture followed by massive parallel sequencing of two pooled DNA samples from Israeli combat soldiers was employed: cases with high grade SF and ethnically matched healthy controls. The resulting sequence variants were individually verified using the Sequenom™ platform and the contribution of the genetic alterations was validated in a second cohort of cases and controls. In the discovery set that included DNA pool of cases (n = 34) and controls (n = 60), a total of 1174 variants with >600 reads/variant/DNA pool were identified, and 146 (in 127 genes) of these exhibited statistically significant (P < 0·05) different rates between SF cases and controls after multiple comparisons correction. Subsequent validation of these 146 sequence variants individually in a total of 136 SF cases and 127 controls using the Sequenom™ platform validated 20/146 variants. Of these, three missense mutations (rs7426114, rs4073918, rs3752135 in the NEB, SLC6A18 and SIGLEC12 genes, respectively) and three synonymous mutations (rs2071856, rs2515941, rs716745 in the ELFN2, GRK4, LRRC55 genes) displayed significant different rates in SF cases compared with controls. Exome sequencing seemingly unravelled novel candidate genes as involved in SF pathogenesis and predisposition.

The influence of age at menarche on cross-sectional geometry of bone in young adulthood

Elucidating the somatic and maturational influences on the biomechanical properties of bone in children is crucial for a proper understanding of bone strength and quality in childhood and later life, and has significant potential for predicting adult fracture and osteoporosis risks. The ability of a long bone to resist bending and torsion is primarily a function of its cross-sectional geometric properties, and is negatively impacted by smaller external bone diameter. In pubescent girls, elevated levels of estrogen impede subperiosteal bone growth and increase endosteal bone deposition, resulting in bones averaging a smaller external and internal diameter relative to boys. In addition, given a well-documented secular trend for an earlier menarche, the age at which the rate of subperiosteal bone deposition decreases may also be younger in more recent cohorts of girls. In this study we examined the relationship between pubertal timing and subsequent bone strength in girls. Specifically, we investigated the effects of age at menarche on bone strength indicators (polar moment of inertia and section modulus) determined from cross-sectional geometry of the second metacarpal (MC2) using data derived from serial hand-wrist radiographs of female participants (N=223) in the Fels Longitudinal Study, with repeated measures of MC2 between the ages of 7 and 35 years. Using multivariate regression models, we evaluated the effects of age at menarche on associations between measures of bone strength in early adulthood and the same measures at a prepubertal age. Results indicate that later age at menarche is associated with stronger adult bone (in torsion and bending) when controlling for prepubertal bone strength (R(2) ranged between 0.54 and 0.70, p<0.001). Since cross-sectional properties of bone in childhood may have long lasting implications, they should be considered along with pubertal timing in assessing risk for future fracture and in clinical recommendations.

Genetic variation in TRPS1 may regulate hip geometry as well as bone mineral density

Trps1 has been proposed as a candidate gene for a mouse bone mineral density (BMD) QTL on Chromosome (Chr) 15, but it remained unclear if this gene was associated with BMD in humans. We used newly available data and advanced bioinformatics techniques to confirm that Trps1 is the most likely candidate gene for the mouse QTL. In short, by combining the raw genetic mapping data from two F2 generation crosses of inbred strains of mice, we narrowed the 95% confidence interval of this QTL down to the Chr 15 region spanning from 6 to 24cM. This region contains 131 annotated genes. Using block haplotyping, all other genes except Trps1 were eliminated as candidates for this QTL. We then examined associations of 208 SNPs within 10kb of TRPS1 with BMD and hip geometry, using human genome-wide association study (GWAS) data from the GEFOS consortium. After correction for multiple testing, six TRPS1 SNPs were significantly associated with femoral neck BMD (P=0.0015-0.0019; adjusted P=0.038-0.048). We also found that three SNPs were highly associated with femoral neck width in women (rs10505257, P=8.6×10(-5), adjusted P=2.15×10(-3); rs7002384, P=5.5×10(-4), adjusted P=01.38×10(-2)). In conclusion, we demonstrated that combining association studies in humans with murine models provides an efficient strategy to identify new candidate genes for bone phenotypes.

A Polymorphism in a gene encoding Perilipin 4 is associated with height but not with bone measures in individuals from the Framingham Osteoporosis Study

There is increasing interest in identifying new pathways and candidate genes that confer susceptibility to osteoporosis. There is evidence that adipogenesis and osteogenesis may be related, including a common bone marrow progenitor cell for both adipocytes and osteoblasts. Perilipin 1 (PLIN1) and Perilipin 4 (PLIN4) are members of the PATS family of genes and are involved in lipolysis of intracellular lipid deposits. A previous study reported gender-specific associations between one polymorphism of PLIN1 and bone mineral density (BMD) in a Japanese population. We hypothesized that polymorphisms in PLIN1 and PLIN4 would be associated with bone measures in adult Caucasian participants of the Framingham Osteoporosis Study (FOS). We genotyped 1,206 male and 1,445 female participants of the FOS for four single-nucleotide polymorphism (SNPs) in PLIN1 and seven SNPs in PLIN4 and tested for associations with measures of BMD, bone ultrasound, hip geometry, and height. We found several gender-specific significant associations with the measured traits. The association of PLIN4 SNP rs8887, G>A with height in females trended toward significance after simulation testing (adjusted P = 0.07) and remained significant after simulation testing in the combined-sex model (adjusted P = 0.033). In a large study sample of men and women, we found a significant association between one SNP in PLIN4 and height but not with bone traits, suggesting that PATS family genes are not important in the regulation of bone. Identification of genes that influence human height may lead to a better understanding of the processes involved in growth and development.

Genome-wide association of an integrated osteoporosis-related phenotype: is there evidence for pleiotropic genes?

Multiple musculoskeletal traits assessed by various methods at different skeletal sites serve as surrogates for osteoporosis risk. However, it is a challenge to select the most relevant phenotypes for genetic study of fractures. Principal component analyses (PCA) were conducted in participants of the Framingham Osteoporosis Study on 17 measures including bond mineral density (BMD) (hip and spine), heel ultrasound, leg lean mass (LLM), and hip geometric indices, adjusting for covariates (age, height, body mass index [BMI]), in a combined sample of 1180 men and 1758 women, as well as in each sex. Four principal components (PCs) jointly explained ~69% of the total variability of musculoskeletal traits. PC1, explaining ~33% of the total variance, was referred to as the component of "Bone strength," because it included the hip and spine BMD as well as several hip cross-sectional properties. PC2 (20.5% variance) was labeled as "Femoral cross-sectional geometry;" PC3 (~8% variance) captured only ultrasound measures; PC4, explaining ~7% variance, was correlated with LLM and hip geometry. We then evaluated ~2.5 mil SNPs for association with PCs 1, 2, and 4. There were genome-wide significant associations (p < 5 × 10⁻⁸) between PC2 and HTR1E (that codes for one of the serotonin receptors) and PC4 with COL4A2 in women. In the sexes-combined sample, AKAP6 was associated with PC2 (p = 1.40 × 10⁻⁷). A single nucleotide polymorphism (SNP) in HTR1E was also associated with the risk of nonvertebral fractures in women (p = 0.005). Functions of top associated genes were enriched for the skeletal and muscular system development (p < 0.05). In conclusion, multivariate combination provides genetic associations not identified in the analysis of primary phenotypes. Genome-wide screening for the linear combinations of multiple osteoporosis-related phenotypes suggests that there are variants with potentially pleiotropic effects in established and novel pathways to be followed up to provide further evidence of their functions.

Variation in childhood skeletal robustness is an important determinant of cortical area in young adults

A better understanding of bone growth will benefit efforts to reduce fracture incidence, because variation in elderly bone traits is determined primarily by adulthood. The natural variation in robustness was used as a model to understand how variable growth patterns define adult bone morphology. Longitudinally acquired hand radiographs of 29 boys and 30 girls were obtained from the Bolton-Brush study for 6 time points spanning 8 to 18 years of age. Segregating individuals into tertiles based on robustness revealed that the biological activity underlying bone growth varied significantly with the natural variation in robustness. For boys, slender metacarpals used an osteoblast-dependent growth pattern to establish function, whereas robust metacarpals used an osteoclast-dependent growth pattern. In contrast, differences in biological activity between girls with slender and robust metacarpals were largely based on the age at which the marrow surface changed from expansion to infilling. Importantly, cortical area for slender metacarpals was as much as 19.7% and 32.2% lower than robust metacarpals for boys and girls, respectively, indicating that robustness was a major determinant of adult cortical area. Finally, after accounting for robustness and body weight effects, we found that the inter-individual variation in cortical area was established as early as 8 years of age. While variation in the amount of bone acquired during growth has primarily been attributed to factors like nutrition, exercise, and genetic background, we showed that the natural variation in robustness was also a major determinant of cortical area, which is an important determinant of bone mass. This predictable relationship between robustness and cortical area should be incorporated into clinical diagnostic measures and experimental studies.

Identification of homogeneous genetic architecture of multiple genetically correlated traits by block clustering of genome-wide associations

Genome-wide association studies (GWAS) using high-density genotyping platforms offer an unbiased strategy to identify new candidate genes for osteoporosis. It is imperative to be able to clearly distinguish signal from noise by focusing on the best phenotype in a genetic study. We performed GWAS of multiple phenotypes associated with fractures [bone mineral density (BMD), bone quantitative ultrasound (QUS), bone geometry, and muscle mass] with approximately 433,000 single-nucleotide polymorphisms (SNPs) and created a database of resulting associations. We performed analysis of GWAS data from 23 phenotypes by a novel modification of a block clustering algorithm followed by gene-set enrichment analysis. A data matrix of standardized regression coefficients was partitioned along both axes--SNPs and phenotypes. Each partition represents a distinct cluster of SNPs that have similar effects over a particular set of phenotypes. Application of this method to our data shows several SNP-phenotype connections. We found a strong cluster of association coefficients of high magnitude for 10 traits (BMD at several skeletal sites, ultrasound measures, cross-sectional bone area, and section modulus of femoral neck and shaft). These clustered traits were highly genetically correlated. Gene-set enrichment analyses indicated the augmentation of genes that cluster with the 10 osteoporosis-related traits in pathways such as aldosterone signaling in epithelial cells, role of osteoblasts, osteoclasts, and chondrocytes in rheumatoid arthritis, and Parkinson signaling. In addition to several known candidate genes, we also identified PRKCH and SCNN1B as potential candidate genes for multiple bone traits. In conclusion, our mining of GWAS results revealed the similarity of association results between bone strength phenotypes that may be attributed to pleiotropic effects of genes. This knowledge may prove helpful in identifying novel genes and pathways that underlie several correlated phenotypes, as well as in deciphering genetic and phenotypic modularity underlying osteoporosis risk.

Genome-wide pleiotropy of osteoporosis-related phenotypes: the Framingham Study

Genome-wide association studies offer an unbiased approach to identify new candidate genes for osteoporosis. We examined the Affymetrix 500K + 50K SNP GeneChip marker sets for associations with multiple osteoporosis-related traits at various skeletal sites, including bone mineral density (BMD, hip and spine), heel ultrasound, and hip geometric indices in the Framingham Osteoporosis Study. We evaluated 433,510 single-nucleotide polymorphisms (SNPs) in 2073 women (mean age 65 years), members of two-generational families. Variance components analysis was performed to estimate phenotypic, genetic, and environmental correlations (rho(P), rho(G), and rho(E)) among bone traits. Linear mixed-effects models were used to test associations between SNPs and multivariable-adjusted trait values. We evaluated the proportion of SNPs associated with pairs of the traits at a nominal significance threshold alpha = 0.01. We found substantial correlation between the proportion of associated SNPs and the rho(P) and rho(G) (r = 0.91 and 0.84, respectively) but much lower with rho(E) (r = 0.38). Thus, for example, hip and spine BMD had 6.8% associated SNPs in common, corresponding to rho(P) = 0.55 and rho(G) = 0.66 between them. Fewer SNPs were associated with both BMD and any of the hip geometric traits (eg, femoral neck and shaft width, section moduli, neck shaft angle, and neck length); rho(G) between BMD and geometric traits ranged from -0.24 to +0.40. In conclusion, we examined relationships between osteoporosis-related traits based on genome-wide associations. Most of the similarity between the quantitative bone phenotypes may be attributed to pleiotropic effects of genes. This knowledge may prove helpful in defining the best phenotypes to be used in genetic studies of osteoporosis.

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.

Differentially expressed genes strongly correlated with femur strength in rats

The region of chromosome 1q33-q54 harbors quantitative trait loci (QTL) for femur strength in COPxDA and F344xLEW F2 rats. The purpose of this study is to identify the genes within this QTL region that contribute to the variation in femur strength. Microarray analysis was performed using RNA extracted from femurs of COP, DA, F344 and LEW rats. Genes differentially expressed in the 1q33-q54 region among these rat strains were then ranked based on the strength of correlation with femur strength in F2 animals derived from these rats. A total of 214 genes in this QTL region were differentially expressed among all rat strains, and 81 genes were found to be strongly correlated (r(2)>0.50) with femur strength. Of these, 12 candidate genes were prioritized for further validation, and 8 of these genes (Ifit3, Ppp2r5b, Irf7, Mpeg1, Bloc1s2, Pycard, Sec23ip, and Hps6) were confirmed by quantitative PCR (qPCR). Ingenuity Pathway Analysis suggested that these genes were involved in interferon alpha, nuclear factor-kappa B (NFkB), extracellular signal-related kinase (ERK), hepatocyte nuclear factor 4 alpha (HNF4A) and tumor necrosis factor (TNF) pathways.