Project description:Patient bone mineral density (BMD) predicts the likelihood of osteoporotic fracture. While substantial progress has been made toward elucidating the genetic determinants of BMD, our understanding of the factors involved remains incomplete. Here, using a systems genetics approach in the mouse, we predicted that bicaudal C homolog 1 (Bicc1), which encodes an RNA-binding protein, is responsible for a BMD quantitative trait locus (QTL) located on murine chromosome 10. Consistent with this prediction, mice heterozygous for a null allele of Bicc1 had low BMD. We used a coexpression network-based approach to determine how Bicc1 influences BMD. Based on this analysis, we inferred that Bicc1 was involved in osteoblast differentiation and that polycystic kidney disease 2 (Pkd2) was a downstream target of Bicc1. Knock down of Bicc1 and Pkd2 impaired osteoblastogenesis, and Bicc1 deficiency-dependent osteoblast defects were rescued by Pkd2 overexpression. Last, in 2 human BMD genome-wide association (GWAS) meta-analyses, we identified SNPs in BICC1 and PKD2 that were associated with BMD. These results, in both mice and humans, identify Bicc1 as a genetic determinant of osteoblastogenesis and BMD and suggest that it does so by regulating Pkd2 transcript levels.
Project description:Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR)?=?58, P?=?1 × 10-75) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P?<?0.0001). In-depth analysis of one gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This genetic atlas provides evidence linking associated SNPs to causal genes, offers new insight into osteoporosis pathophysiology, and highlights opportunities for drug development.
Project description:BACKGROUND:Most reported genome-wide association studies (GWAS) seeking to identify the loci of osteoporosis-related traits have involved Caucasian populations. We aimed to identify the single nucleotide polymorphisms (SNPs) of osteoporosis-related traits among East Asian populations from the bone mineral density (BMD)-related loci of an earlier GWAS meta-analysis. METHODS:A total of 95 SNPs, identified at the discovery stage of the largest GWAS meta-analysis of BMD, were tested to determine associations with osteoporosis-related traits (BMD, osteoporosis, or fracture) in Korean subjects (n=1,269). The identified SNPs of osteoporosis-related traits in Korean subjects were included in the replication analysis using Chinese (n=2,327) and Japanese (n=768) cohorts. RESULTS:A total of 17 SNPs were associated with low BMD in Korean subjects. Specifically, 9, 6, 9, and 5 SNPs were associated with the presence of osteoporosis, non-vertebral fractures, vertebral fractures, and any fracture, respectively. Collectively, 35 of the 95 SNPs (36.8%) were associated with one or more osteoporosis-related trait in Korean subjects. Of the 35 SNPs, 19 SNPs (54.3%) were also associated with one or more osteoporosis-related traits in East Asian populations. Twelve SNPs were associated with low BMD in the Chinese and Japanese cohorts. Specifically, 3, 4, and 2 SNPs were associated with the presence of hip fractures, vertebral fractures, and any fracture, respectively. CONCLUSIONS:Our results identified the common SNPs of osteoporosis-related traits in both Caucasian and East Asian populations. These SNPs should be further investigated to assess whether they are true genetic markers of osteoporosis.
Project description:Osteoporosis is a serious public health issue, which is mostly characterized by low bone mineral density (BMD). To search for additional genetic susceptibility loci underlying BMD variation, an effective strategy is to focus on testing of specific variants with high potential of functional effects. Single nucleotide polymorphisms (SNPs) that introduce or disrupt CpG dinucleotides (CpG-SNPs) may alter DNA methylation levels and thus represent strong candidate functional variants. Here, we performed a targeted GWAS for 63,627 potential functional CpG-SNPs that may affect DNA methylation in bone-related cells, in five independent cohorts (n = 5905). By meta-analysis, 9 CpG-SNPs achieved a genome-wide significance level (p < 7.86 × 10-7) for association with lumbar spine BMD and additional 15 CpG-SNPs showed suggestive significant (p < 5.00 × 10-5) association, of which 2 novel SNPs rs7231498 (NFATC1) and rs7455028 (ESR1) also reached a genome-wide significance level in the joint analysis. Several identified CpG-SNPs were mapped to genes that have not been reported for association with BMD in previous GWAS, such as NEK3 and NFATC1 genes, highlighting the enhanced power of targeted association analysis for identification of novel associations that were missed by traditional GWAS. Interestingly, several genomic regions, such as NEK3 and LRP5 regions, contained multiple significant/suggestive CpG-SNPs for lumbar spine BMD, suggesting that multiple neighboring CpG-SNPs may synergistically mediate the DNA methylation level and gene expression pattern of target genes. Furthermore, functional annotation analyses suggested a strong regulatory potential of the identified BMD-associated CpG-SNPs and a significant enrichment in biological processes associated with protein localization and protein signal transduction. Our results provided novel insights into the genetic basis of BMD variation and highlighted the close connections between genetic and epigenetic mechanisms of complex disease.
Project description:Osteoporosis is a skeletal disorder characterized by a systemic impairment of bone mineral density (BMD). Genome-wide association studies (GWAS) have identified hundreds of susceptibility loci for osteoporosis and BMD. However, the vast majority of susceptibility loci are located in non-coding regions of the genome and provide limited information about the genetic mechanisms of osteoporosis. Herein we performed a comprehensive functional analysis to investigate the genetic and epigenetic mechanisms of osteoporosis and BMD. BMD and osteoporosis are found to share many common susceptibility loci, and the corresponding susceptibility genes are significantly enriched in bone-related biological pathways. The regulatory element enrichment analysis indicated that BMD and osteoporosis susceptibility loci are significantly enriched in 5'UTR and DNase I hypersensitive sites (DHSs) of peripheral blood immune cells. By integrating GWAS and expression Quantitative Trait Locus (eQTL) data, we found that 15 protein-coding genes are regulated by the osteoporosis and BMD susceptibility loci. Our analysis provides new clues for a better understanding of the pathogenic mechanisms and offers potential therapeutic targets for osteoporosis.
Project description:Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically.To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning approximately 380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82x10(-7) and 1.47x10(-6), respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the approximately 380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat.Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis.
Project description: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.
Project description:Although GWAS have been successful in identifying some osteoporosis associated loci, the findings explain only a small fraction of the total genetic variance. In this study we use a recently developed novel pleiotropic conditional false discovery rate (cFDR) method to identify novel genetic loci associated with two risk traits for osteoporotic fracture (the clinical outcome and end result of osteoporosis), Height (HT) and Femoral Neck (FNK) BMD. The cFDR method allows us to improve the detection of associated variants by incorporating any potentially shared genetic mechanisms between the two associated traits. We analyzed the summary statistics from two GWAS meta-analyses for single nucleotide polymorphisms (SNPs) that are associated with HT and FNK BMD. Using the cFDR method, we show enrichment in the identification of SNPs associated with each trait conditioned on their strength of association with the second trait. The findings revealed 18 SNPs that are associated with both HT and FNK BMD, 4 of which had not previously been reported to play a role in bone health. The novel SNPs located at KIF1B and the intergenic region between FERD3L and TWISTNB are noteworthy as these genes may be associated with processes that are functionally important in bone metabolism. By leveraging GWAS results from related phenotypes we identified several novel loci that may contribute to the proportion of variability explained for each trait, although we cannot speculate about these potential contributions to heritability based on this analysis alone.
Project description:<h4>Objective</h4> The current study was conducted to determine whether peak bone mineral density (BMD) and obesity phenotypes are associated with certain LGR4 gene polymorphisms found in Chinese nuclear families with female children. <h4>Methods</h4> A total of 22 single nucleotide polymorphisms (SNPs) located in and around the LGR4 gene were identified in 1,300 subjects who were members of 390 Chinese nuclear families with female children. Then, BMD readings of the femoral neck, total hip, and lumbar spine as well as measurements of the total lean mass (TLM), total fat mass (TFM), and trunk fat mass were obtained via dual-energy X-ray absorptiometry. The quantitative transmission disequilibrium test was used to analyze the associations between specific SNPs and LGR4 haplotypes and peak BMD as well as between LGR4 haplotypes and TLM, percent lean mass, TFM, percent fat mass, trunk fat mass, and body mass index (BMI). <h4>Results</h4> Here, rs7936621 was significantly associated with the BMD values for the total hip and lumbar spine, while rs10835171 and rs6484295 were associated with the trunk fat mass and BMI, respectively. Regarding the haplotypes, we found significant associations between GAA in block 2 and trunk fat mass and BMI, between AGCGT in block 3 and total hip BMD, between TGCTCC in block 5 and femoral neck BMD, and between TACTTC in block 5 and both lumbar spine and femoral neck BMD (all P-values < 0.05). <h4>Conclusion</h4> Genetic variations of the LGR4 gene are related to peak BMD, BMI, and trunk fat mass.
Project description:Osteoporosis is a common human complex disease. It is mainly characterized by low bone mineral density (BMD) and low-trauma osteoporotic fractures (OF). Until now, a large proportion of heritability has yet to be explained. The existing large-scale genome-wide association studies (GWAS) provide strong support for the investigation of osteoporosis mechanisms using pathway analysis. Recent findings showed that different risk pathways may be involved in BMD in different tissues. Here, we conducted multiple pathway analyses of a large-scale lumbar spine BMD GWAS dataset (2,468,080 SNPs and 31,800 samples) using two published gene-based analysis software including ProxyGeneLD and the PLINK. Using BMD genes from ProxyGeneLD, we identified 51 significant KEGG pathways with adjusted P<0.01. Using BMD genes from PLINK, we identified 38 significant KEGG pathways with adjusted P<0.01. Interestingly, 33 pathways are shared in both methods. In summary, we not only identified the known risk pathway such as Wnt signaling, in which the top GWAS variants are significantly enriched, but also highlight some new risk pathways. Interestingly, evidence from further supports the involvement of these pathways in MBD.