Identification of PLCL1 gene for hip bone size variation in females in a genome-wide association study

A systematic review and cross-database analysis of single nucleotide polymorphisms underlying hip morphology and osteoarthritis reveals shared mechanisms

OBJECTIVE

Understanding the mechanisms of hip disease, such as osteoarthritis (OA), is crucial to advance their treatment. Such hip diseases often involve specific morphological changes. Genetic variations, called single nucleotide polymorphisms (SNPs), influence various hip morphological parameters. This study investigated the biological relevance of SNPs correlated to hip morphology in genome-wide association studies (GWAS). The SNP-associated genes were compared to genes associated with OA in other joints, aiming to see if the same genes play a role in both hip development and the risk of OA in other lower limb joints.

METHODOLOGY

A systematic literature review was conducted to identify SNPs correlated with hip morphology, based on the Population, Intervention, Comparison, Outcome, and Study (PICOS) framework. Afterwards, Gene Ontology (GO) analysis was performed, using EnrichR, on the SNP-associated genes and compared with non-hip OA-associated genes, across different databases.

RESULTS

Reviewing 49 GWAS identified 436 SNPs associated with hip joint morphology, encompassing variance in bone size, structure and shape. Among the SNP-associated genes, SOX9 plays a pivotal role in size, GDF5 impacts bone structure, and BMP7 affects shape. Overall, skeletal system development, regulation of cell differentiation, and chondrocyte differentiation emerged as crucial processes influencing hip morphology. Eighteen percent of GWAS-identified genes related to hip morphology were also associated with non-hip OA.

CONCLUSION

Our findings indicate the existence of multiple shared genetic mechanisms across hip morphology and OA, highlighting the necessity for more extensive research in this area, as in contrast to the hip, the genetic background on knee or foot morphology remains largely understudied.

Genome-wide association study identifies multiple loci influencing duck serum biochemical indicators in the laying period

1. Laying performance is an important economic trait in poultry. The blood is essential in transporting nutrients to the yolk and albumen and is necessary for egg formation.2. This study calculated the phenotypic relationships of duck egg quality, egg production efficiency and 22 serum parameters in the egg-laying stage. Using a variety of methodologies, a genome-wide association study (GWAS) was carried out to uncover the genetic foundations of the 22 serum biochemical markers of laying ducks.3. Spearman correlation coefficients between the egg production (226-329 per day) and the serum parameters were all weak, being less than 0.3. This analysis was done on 22 serum parameters, with total protein (TP), total triglycerides (TG), calcium (Ca) and phosphorous (P) having the highest correlation coefficients (r = 0.56-0.88). The coefficients for blood markers, such as total cholesterol (CHOL), total bilirubin (TBIL), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) varied from 0.70-0.94.4. Based on single-marker single-trait genome-wide analyses by a mixed linear model program of EMMAX, nine candidate genes were associated with enzyme traits (AST/ALT aspartate transaminase/glutamic-pyruvic transaminase, creatine kinase) and 19 candidate genes were associated with metabolism and protein-related serum parameters (glucose, total bile acid, uric acid (UA), albumin (ALB).5. The mvLMM (multivariate linear mixed model) of GEMMA software was used to carry out multiple trait integrated GWAS. Two candidate genes were found in the TP-TG-CA-P analysis and seven candidate genes in the CHOL_LDL-C_HDL-C_TBIL study. There was a high genetic correlation between the two groups.

PLCL1 suppresses tumour progression by regulating AMPK/mTOR-mediated autophagy in renal cell carcinoma

Autophagy has been increasingly recognized as a critical regulatory mechanism in the maintenance of cellular homeostasis. A previous study showed that phospholipase C-like protein 1 (PLCL1) is associated with lipid metabolism in renal cell carcinoma (RCC). However, it is unclear whether PLCL1 regulates autophagy, thereby influencing the progression of RCC. Bioinformatics analysis of five microarray datasets revealed that expression of PLCL1 is decreased in tumours and is positively correlated with prognosis in RCC patients. Three independent public datasets, clinical RCC tissues and RCC cell lines, were validated using real-time qPCR, western blotting and immunohistochemistry. Using wound healing and transwell assays, we observed that elevated PLCL1 levels decreased the migratory distance and the invasive number of 786-O and ACHN cells, but PLCL1 knockdown reversed these changes in 769P cell lines compared to those in controls. The results of flow cytometry analysis indicated that PLCL1 promotes apoptosis. Moreover, transcriptional analysis based on stable overexpression of PLCL1 in 786-O cells revealed that PLCL1 is related to autophagy, and western blotting and autophagic experimental results further verified these findings. Mechanistic investigations confirmed that PLCL1 activates the AMPK/mTOR pathway and interacts with decidual protein induced by progesterone (DEPP). Collectively, our data suggest that PLCL1 functions as a suppressor of RCC progression by activating the AMPK/mTOR pathway, interacting with DEPP, initiating autophagy and inducing apoptosis. PLCL1 may be a promising therapeutic target for the diagnosis and treatment of ccRCC patients.

PLCL1 regulates fibroblast-like synoviocytes inflammation via NLRP3 inflammasomes in rheumatoid arthritis

Background

Phospholipase C-like 1 (PLCL1), a protein that lacks catalytic activity, has similar structures to the PLC family. The aim of this research was to find the function and underlying mechanisms of PLCL1 in fibroblast-like synoviocyte (FLS) of rheumatoid arthritis (RA).

Methods

In this study, we first analyzed the expression of PLCL1 in the synovial tissue of RA patients and K/BxN mice by immunohistochemical staining. Then silencing or overexpressing PLCL1 in FLS before stimulating by TNF-α. The levels of IL-6, IL-1β and CXCL8 in FLS and supernatants were detected by Western Blot (WB), Real-Time Quantitative PCR and Enzyme Linked Immunosorbent Assay. We used INF39 to specifically inhibit the activation of NLRP3 inflammasomes, and detected the expression of NLRP3, Cleaved Caspase-1, IL-6 and IL-1β in FLS by WB.

Result

When PLCL1 was silenced, the level of IL-6, IL-1β and CXCL8 were down-regulated. When PLCL1 was overexpressed, the level of IL-6, IL-1β and CXCL8 were unregulated. The previous results demonstrated that the mechanism of PLCL1 regulating inflammation in FLS was related to NLRP3 inflammasomes. INF39 could counteract the release of inflammatory cytokines caused by overexpression of PLCL1.

Conclusion

Result showed that the function of PLCL1 in RA FLS might be related to the NLRP3 inflammasomes. We finally confirmed our hypothesis with the NLRP3 inhibitor INF39. Our results suggested that PLCL1 might promote the inflammatory response of RA FLS by regulating the NLRP3 inflammasomes.

Identification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.

Identification of novel pleiotropic gene for bone mineral density and lean mass using the cFDR method

Bone mineral density (BMD) and whole-body lean mass (WBLM) are two important phenotypes of osteoporosis and sarcopenia. Previous studies have shown that BMD and lean mass were phenotypically and genetically correlated. To identify the novel common genetic factors shared between BMD and WBLM, we performed the conditional false discovery rate (cFDR) analysis using summary data of the genome-wide association study of femoral neck BMD (n = 53,236) and WBLM (n = 38,292) from the Genetic Factors for Osteoporosis Consortium (GEFOS). We identified eight pleiotropic Single Nucleotide Polymorphism (SNPs) (PLCL1 rs11684176 and rs2880389, JAZF1 rs198, ADAMTSL3 rs10906982, RFTN2/MARS2 rs7340470, SH3GL3 rs1896797, ST7L rs10776755, ANKRD44/SF3B1 rs11888760) significantly associated with femoral neck BMD and WBLM (ccFDR < 0.05). Bayesian fine-mapping analysis showed that rs11888760, rs198, and rs1896797 were the possible functional variants in the ANKRD44/SF3B1, JAZF1i, and SH3GL3 loci, respectively. Functional annotation suggested that rs11888760 was likely to comprise a DNA regulatory element and linked to the expression of RFTN2 and PLCL1. PLCL1 showed differential expression in laryngeal posterior cricoarytenoid muscle between rats of 6 months and 30 months of age. Our findings, together with PLCL1's potential functional relevance to bone and skeletal muscle function, suggested that rs11888760 was the possible pleiotropic functional variants appearing to coregulate both bone and muscle metabolism through regulating the expression of PLCL1. The findings enhanced our knowledge of genetic associations between BMD and lean mass and provide a rationale for subsequent functional studies of the implicated genes in the pathophysiology of diseases, such as osteoporosis and sarcopenia.

Twelve years of GWAS discoveries for osteoporosis and related traits: advances, challenges and applications

Osteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting diseases and genetic factors. In this review, we first summarize the discovery from genome-wide association studies (GWASs) in the bone field in the last 12 years. To date, GWASs and meta-analyses have discovered hundreds of loci that are associated with bone mineral density (BMD), osteoporosis, and osteoporotic fractures. However, the GWAS approach has sometimes been criticized because of the small effect size of the discovered variants and the mystery of missing heritability, these two questions could be partially explained by the newly raised conceptual models, such as omnigenic model and natural selection. Finally, we introduce the clinical use of GWAS findings in the bone field, such as the identification of causal clinical risk factors, the development of drug targets and disease prediction. Despite the fruitful GWAS discoveries in the bone field, most of these GWAS participants were of European descent, and more genetic studies should be carried out in other ethnic populations to benefit disease prediction in the corresponding population.

Uterine transcriptome analysis reveals mRNA expression changes associated with the ultrastructure differences of eggshell in young and aged laying hens

Background

Lower eggshell quality in the late laying period leads to economic loss. It is a major threat to the quality and safety of egg products. Age-related variations in ultrastructure were thought to induce this deterioration. Eggshell formation is a highly complex process under precise regulation of genes and biological pathways in uterus of laying hens. Herein, we evaluated the physical, mechanical and ultrastructure properties of eggshell and conducted RNA sequencing to learn the transcriptomic differences in uterus between laying hens in the peak (young hens) and late phase (aged hens) of production.

Results

The declined breaking strength and fracture toughness of eggshell were observed in aged hen group compared to those in young hen group, accompanied with ultrastructure variations including the increased thickness of mammillary layer and the decreased incidence of early fusion. During the initial stage of eggshell formation, a total of 183 differentially expressed genes (DEGs; 125 upregulated and 58 downregulated) were identified in uterus of laying hens in the late phase in relative to those at peak production. The DEGs annotated to Gene Ontology terms related to antigen processing and presentation were downregulated in aged hens compared to young hens. The contents of proinflammatory cytokine IL-1β in uterus were higher in aged hens relative to those in young hens. Besides, the genes of some matrix proteins potentially involved in eggshell mineralization, such as ovalbumin, versican and glypican 3, were also differentially expressed between two groups.

Conclusions

Altered gene expression of matrix proteins along with the compromised immune function in uterus of laying hens in the late phase of production may conduce to age-related impairments of eggshell ultrastructure and mechanical properties. The current study enhances our understanding of the age-related deteriorations in eggshell ultrastructure and provides potential targets for improvement of eggshell quality in the late laying period.

Supplementary Information

Supplementary information accompanies this paper at 10.1186/s12864-020-07177-7.

Comprehensive Genetic Analysis of 128 Candidate Genes in a Cohort With Idiopathic, Severe, or Familial Osteoporosis

Context

The genetic bases of osteoporosis (OP), a disorder with high heritability, are poorly understood at an individual level. Cases of idiopathic or familial OP have long puzzled clinicians as to whether an actionable genetic cause could be identified.

Objective

We performed a genetic analysis of 28 cases of idiopathic, severe, or familial osteoporosis using targeted massively parallel sequencing.

Design

Targeted sequencing of 128 candidate genes was performed using Illumina NextSeq. Variants of interest were confirmed by Sanger sequencing or SNP array.

Patients and Setting

Thirty-seven patients in an academic tertiary hospital participated (54% male; median age, 44 years; 86% with fractures), corresponding to 28 sporadic or familial cases.

Main Outcome Measure

The identification of rare stop-gain, indel, splice site, copy-number, or nonsynonymous variants altering protein function.

Results

Altogether, we identified 28 variants of interest, but only 3 were classified as pathogenic or likely pathogenic variants: COL1A2 p.(Arg708Gln), WNT1 p.(Gly169Asp), and IDUA p.(His82Gln). An association of variants in different genes was found in 21% of cases, including a young woman with severe OP bearing WNT1, PLS3, and NOTCH2 variants. Among genes of uncertain significance analyzed, a potential additional line of evidence has arisen for GWAS candidates GPR68 and NBR1, warranting further studies.

Conclusions

While we hope that continuing efforts to identify genetic predisposition to OP will lead to improved and personalized care in the future, the likelihood of identifying actionable pathogenic variants in intriguing cases of idiopathic or familial osteoporosis is seemingly low.

Pleiotropic loci underlying bone mineral density and bone size identified by a bivariate genome-wide association analysis

Aiming to identify pleiotropic genomic loci for bone mineral density and bone size, we performed a bivariate GWAS in five discovery samples and replicated in two large-scale samples. We identified 2 novel loci at 2q37.1 and 6q26. Our findings provide insight into common genetic architecture underlying both traits.

INTRODUCTION

Bone mineral density (BMD) and bone size (BS) are two important factors that contribute to the development of osteoporosis and osteoporotic fracture. Both BMD and BS are highly heritable and they are genetically correlated. In this study, we aim to identify pleiotropic loci associated with BMD and BS.

METHODS

We conducted a bivariate genome-wide association (GWA) analysis of hip BMD and hip BS in 6180 participants from 5 samples, followed by in silico replication in the UK Biobank study of BMD (N = 426,824) and the deCODE study of BS (N = 28,954), respectively.

RESULTS

SNPs from 2 genomic loci were significant at the genome-wide significance (GWS) level (p lt; 5 × 10-8) in the discovery samples and were successfully replicated in the replication samples (2q37.1, lead SNP rs7575512, discovery p = 1.49 × 10-10, replication p = 0.05; 6q26, lead SNP rs1040724, discovery p = 1.95 × 10-8, replication p = 0.03). Functional annotations suggested functional relevance of the identified variants to bone development.

CONCLUSION

Our findings provide insight into the common genetic architecture underlying BMD and BS, and enhance our understanding of the potential mechanism of osteoporosis fracture.

ATRAID regulates the action of nitrogen-containing bisphosphonates on bone

Nitrogen-containing bisphosphonates (N-BPs), such as alendronate, are the most widely prescribed medications for diseases involving bone, with nearly 200 million prescriptions written annually. Recently, widespread use of N-BPs has been challenged due to the risk of rare but traumatic side effects such as atypical femoral fracture (AFF) and osteonecrosis of the jaw (ONJ). N-BPs bind to and inhibit farnesyl diphosphate synthase, resulting in defects in protein prenylation. Yet, it remains poorly understood what other cellular factors might allow N-BPs to exert their pharmacological effects. Here, we performed genome-wide studies in cells and patients to identify the poorly characterized gene, ATRAID Loss of ATRAID function results in selective resistance to N-BP-mediated loss of cell viability and the prevention of alendronate-mediated inhibition of prenylation. ATRAID is required for alendronate inhibition of osteoclast function, and ATRAID-deficient mice have impaired therapeutic responses to alendronate in both postmenopausal and senile (old age) osteoporosis models. Last, we performed exome sequencing on patients taking N-BPs that suffered ONJ or an AFF. ATRAID is one of three genes that contain rare nonsynonymous coding variants in patients with ONJ or an AFF that is also differentially expressed in poor outcome groups of patients treated with N-BPs. We functionally validated this patient variation in ATRAID as conferring cellular hypersensitivity to N-BPs. Our work adds key insight into the mechanistic action of N-BPs and the processes that might underlie differential responsiveness to N-BPs in people.

GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures

Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 - 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P = 2.3 × 10-42, β = -0.090) and confers risk of hip fracture (P = 1.0 × 10-8, OR = 1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density.

Studying the effects of haplotype partitioning methods on the RA-associated genomic results from the North American Rheumatoid Arthritis Consortium (NARAC) dataset

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Haplotype blocks methods plays a complementary role to the single-SNP approaches.

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CIT, FGT, SSLD, and single-SNP methods should be applied to discover the markers.

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Selection of the method used for the association has an impact on the biomarkers.

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SSLD method detected more significant SNPs than CIT, FGT, and single-SNP methods.

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The 383 SNPs discovered by all methods are significantly associated with RA.

The human genome, which includes thousands of genes, represents a big data challenge. Rheumatoid arthritis (RA) is a complex autoimmune disease with a genetic basis. Many single-nucleotide polymorphism (SNP) association methods partition a genome into haplotype blocks. The aim of this genome wide association study (GWAS) was to select the most appropriate haplotype block partitioning method for the North American Rheumatoid Arthritis Consortium (NARAC) dataset. The methods used for the NARAC dataset were the individual SNP approach and the following haplotype block methods: the four-gamete test (FGT), confidence interval test (CIT), and solid spine of linkage disequilibrium (SSLD). The measured parameters that reflect the strength of the association between the biomarker and RA were the P-value after Bonferroni correction and other parameters used to compare the output of each haplotype block method. This work presents a comparison among the individual SNP approach and the three haplotype block methods to select the method that can detect all the significant SNPs when applied alone. The GWAS results from the NARAC dataset obtained with the different methods are presented. The individual SNP, CIT, FGT, and SSLD methods detected 541, 1516, 1551, and 1831 RA-associated SNPs respectively, and the individual SNP, FGT, CIT, and SSLD methods detected 65, 156, 159, and 450 significant SNPs respectively, that were not detected by the other methods. Three hundred eighty-three SNPs were discovered by the haplotype block methods and the individual SNP approach, while 1021 SNPs were discovered by all three haplotype block methods. The 383 SNPs detected by all the methods are promising candidates for studying RA susceptibility. A hybrid technique involving all four methods should be applied to detect the significant SNPs associated with RA in the NARAC dataset, but the SSLD method may be preferred because of its advantages when only one method was used.

Identification of novel genetic loci for osteoporosis and/or rheumatoid arthritis using cFDR approach

There are co-morbidity between osteoporosis (OP) and rheumatoid arthritis (RA). Some genetic risk factors have been identified for these two phenotypes respectively in previous research; however, they accounted for only a small portion of the underlying total genetic variances. Here, we sought to identify additional common genetic loci associated with OP and/or RA. The conditional false discovery rate (cFDR) approach allows detection of additional genetic factors (those respective ones as well as common pleiotropic ones) for the two associated phenotypes. We collected and analyzed summary statistics provided by large, multi-center GWAS studies of FNK (femoral neck) BMD (a major risk factor for osteoporosis) (n = 53,236) and RA (n = 80,799). The conditional quantile-quantile (Q-Q) plots can assess the enrichment of SNPs related to FNK BMD and RA, respectively. Furthermore, we identified shared loci between FNK BMD and RA using conjunction cFDR (ccFDR). We found strong enrichment of p-values in FNK BMD when conditional Q-Q was done on RA and vice versa. We identified 30 novel OP-RA associated pleiotropic loci that have not been reported in previous OP or RA GWAS, 18 of which located in the MHC (major histocompatibility complex) region previously reported to play an important role in immune system and bone health. We identified some specific novel polygenic factors for OP and RA respectively, and identified 30 novel OP-RA associated pleiotropic loci. These discovery findings may offer novel pathobiological insights, and suggest new targets and pathways for drug development in OP and RA patients.

Genome-wide association study of 8 carcass traits in Jinghai Yellow chickens using specific-locus amplified fragment sequencing technology

Carcass traits are important to the commercial chicken industry, and understanding the genetics of these traits will be useful in the development of commercially viable varieties of chickens. We conducted a genome-wide association study based on 8 carcass trait phenotypes in a population of 400 43-week-old Jinghai Yellow chickens. Specific-locus amplified fragment sequencing technology was used to identify 90,961 single nucleotide polymorphisms (SNP) distributed among 29 chromosomes and the mitochondrial genome. SNP that were significantly associated with phenotypic traits were identified by a simple general linear model. Fifteen SNP attained genome-wide significance (P < 1.87E−6) and were associated with 5 of the 8 carcass traits; only one SNP was significantly associated with 2 traits (foot weight and wing weight). Twelve genes were associated with these 15 SNP. A region of chromosome 4 between 75.5 and 76.1 Mb was associated with carcass weight, foot weight, and wing weight. An 84-kb region on chromosome 3 (51.2 Mb) was associated with eviscerated weight and semi-eviscerated weight.

A genome-wide association study reveals susceptibility loci for myocardial infarction/coronary artery disease in Saudi Arabs

BACKGROUND

Multiple loci have been identified for coronary artery disease (CAD) by genome-wide association studies (GWAS), but no such studies on CAD incidence has been reported yet for any Middle Eastern population.

METHODS

In this study, we performed a GWAS for CAD and myocardial infarction (MI) incidence in 5668 Saudis of Arab descent using the Affymetrix Axiom Genotyping platform.

RESULTS

We describe SNPs at 16 loci that showed significant (P < 5 × 10(-8)) or suggestive GWAS association (P < 1 × 10(-5)) with CAD or MI, in the ethnic Saudi Arab population. Among the four variants reaching GWAS significance in the present study, the rs10738607_G [0.78(0.71-0.85); p = 2.17E-08] in CDNK2A/B gene was associated with CAD. Two other SNPs on the same gene, rs10757274_G [0.79(0.73-0.86); p = 2.98E-08] and rs1333045_C [0.79(0.73-0.86); p = 1.15E-08] as well as the rs9982601_T [1.38(1.23-1.55); p = 3.49E-08] on KCNE2 were associated with MI. These variants have been previously described in other populations. Several SNPs, including the rs7421388 (PLCL1) and rs12541758 (TRPA1) displaying a suggestive GWAS association (P < 1 × 10(-5)) with CAD as well as rs41411047 (RNF13), rs32793 (PDZD2) and rs4739066 (YTHDF3), similarly showing weak association with MI, were confirmed in an independent dataset. Furthermore, our estimation of heritability of CAD and MI based on observed genome-wide sharing in unrelated Saudi Arabs was approximately 33% and 44%, respectively.

CONCLUSIONS

Our study has identified susceptibility variants for CAD/MI in ethnic Arabs. These findings provide further insights into pathways contributing to the susceptibility for CAD and will enable more comprehensive genetic studies of these diseases in Middle East populations.

Association Study between the FTCDNL1 (FONG) and Susceptibility to Osteoporosis

Osteoporosis is a systemic skeletal disease characterized by a decreased bone mineral density that results in an increased risk of fragility fractures. Previous studies indicated that genetic factors are involved in the pathogenesis of osteoporosis. Polymorphisms of the FONG (FTCDNL1) gene (rs7605378) were reported to be associated with the risk of osteoporosis in a Japanese population. To assess whether polymorphisms of the FTCDNL1 gene contribute to the susceptibility and severity of osteoporosis in a Taiwanese population, 326 osteoporosis patients and 595 controls of a Taiwanese population were included in this study. Our results indicated that rs10203122 was significantly associated with osteoporosis susceptibility among female. Our findings provide evidence that rs10203122 in FTCDNL1 is associated with a susceptibility to osteoporosis.

Polymorphisms Associated With Low Bone Mass and High Risk of Atraumatic Fracture

Osteoporosis is a serious disease characterized by high morbidity and mortality due to atraumatic fractures. In the pathogenesis of osteoporosis, except environment and internal factors, such as hormonal imbalance and genetic background, are also in play. In this study candidate genes for osteoporosis were classified according to metabolic or hormonal pathways, which regulate bone mineral density and bone quality (estrogen, RANKL/RANK/OPG axis, mevalonate, the canonical circuit and genes regulating the vitamin D system). COL1A1 and/or COL1A2 genes, which encode formation of the procollagen 1 molecule, were also studied. Mutations in these genes are well-known causes of the inborn disease ‘osteogenesis imperfecta’. In addition to this, polymorphisms in COL1A1 and/or COL1A2 have been found to be associated with parameters of bone quality in adult subjects. The authors discuss the perspectives for the practical utilization of pharmacogenetics (identification of single candidate genes using PCR) and pharmacogenomics (using genome wide association studies (GWAS) to choose optimal treatment for osteoporosis). Potential predictors of antiresorptive therapy efficacy include the following well established genes: ER, FDPS, Cyp19A1, VDR, Col1A1, and Col1A2, as well as the gene for the canonical (Wnt) pathway. Unfortunately, the positive outcomes seen in most association studies have not been confirmed by other researchers. The controversial results could be explained by the use of different methodological approaches in individual studies (different sample size, homogeneity of investigated groups, ethnic differences, or linkage disequilibrium between genes). The key pitfall of association studies is the low variability (7-10 %) of bone phenotypes associated with the investigated genes. Nevertheless, the identification of new genes and the verification of their association with bone density and/or quality (using both PCR and GWAS), remain a great challenge in the optimal prevention and treatment of osteoporosis.

Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to Eosinophilic Esophagitis

Objective: We report the first pediatric specific Phenome-Wide Association Study (PheWAS) using electronic medical records (EMRs). Given the early success of PheWAS in adult populations, we investigated the feasibility of this approach in pediatric cohorts in which associations between a previously known genetic variant and a wide range of clinical or physiological traits were evaluated. Although computationally intensive, this approach has potential to reveal disease mechanistic relationships between a variant and a network of phenotypes.

Method: Data on 5049 samples of European ancestry were obtained from the EMRs of two large academic centers in five different genotyped cohorts. Recently, these samples have undergone whole genome imputation. After standard quality controls, removing missing data and outliers based on principal components analyses (PCA), 4268 samples were used for the PheWAS study. We scanned for associations between 2476 single-nucleotide polymorphisms (SNP) with available genotyping data from previously published GWAS studies and 539 EMR-derived phenotypes. The false discovery rate was calculated and, for any new PheWAS findings, a permutation approach (with up to 1,000,000 trials) was implemented.

Results: This PheWAS found a variety of common variants (MAF > 10%) with prior GWAS associations in our pediatric cohorts including Juvenile Rheumatoid Arthritis (JRA), Asthma, Autism and Pervasive Developmental Disorder (PDD) and Type 1 Diabetes with a false discovery rate < 0.05 and power of study above 80%. In addition, several new PheWAS findings were identified including a cluster of association near the NDFIP1 gene for mental retardation (best SNP rs10057309, p = 4.33 × 10⁻⁷, OR = 1.70, 95%CI = 1.38 − 2.09); association near PLCL1 gene for developmental delays and speech disorder [best SNP rs1595825, p = 1.13 × 10⁻⁸, OR = 0.65(0.57 − 0.76)]; a cluster of associations in the IL5-IL13 region with Eosinophilic Esophagitis (EoE) [best at rs12653750, p = 3.03 × 10⁻⁹, OR = 1.73 95%CI = (1.44 − 2.07)], previously implicated in asthma, allergy, and eosinophilia; and association of variants in GCKR and JAZF1 with allergic rhinitis in our pediatric cohorts [best SNP rs780093, p = 2.18 × 10⁻⁵, OR = 1.39, 95%CI = (1.19 − 1.61)], previously demonstrated in metabolic disease and diabetes in adults.

Conclusion: The PheWAS approach with re-mapping ICD-9 structured codes for our European-origin pediatric cohorts, as with the previous adult studies, finds many previously reported associations as well as presents the discovery of associations with potentially important clinical implications.

Variation in the MC4R gene is associated with bone phenotypes in elderly Swedish women

Osteoporosis is characterized by reduced bone mineral density (BMD) and increased fracture risk. Fat mass is a determinant of bone strength and both phenotypes have a strong genetic component. In this study, we examined the association between obesity associated polymorphisms (SNPs) with body composition, BMD, Ultrasound (QUS), fracture and biomarkers (Homocysteine (Hcy), folate, Vitamin D and Vitamin B12) for obesity and osteoporosis. Five common variants: rs17782313 and rs1770633 (melanocortin 4 receptor (MC4R); rs7566605 (insulin induced gene 2 (INSIG2); rs9939609 and rs1121980 (fat mass and obesity associated (FTO) were genotyped in 2 cohorts of Swedish women: PEAK-25 (age 25, n = 1061) and OPRA (age 75, n = 1044). Body mass index (BMI), total body fat and lean mass were strongly positively correlated with QUS and BMD in both cohorts (r² = 0.2–0.6). MC4R rs17782313 was associated with QUS in the OPRA cohort and individuals with the minor C-allele had higher values compared to T-allele homozygotes (TT vs. CT vs. CC: BUA: 100 vs. 103 vs. 103; p = 0.002); (SOS: 1521 vs. 1526 vs. 1524; p = 0.008); (Stiffness index: 69 vs. 73 vs. 74; p = 0.0006) after adjustment for confounders. They also had low folate (18 vs. 17 vs. 16; p = 0.03) and vitamin D (93 vs. 91 vs. 90; p = 0.03) and high Hcy levels (13.7 vs 14.4 vs. 14.5; p = 0.06). Fracture incidence was lower among women with the C-allele, (52% vs. 58%; p = 0.067). Variation in MC4R was not associated with BMD or body composition in either OPRA or PEAK-25. SNPs close to FTO and INSIG2 were not associated with any bone phenotypes in either cohort and FTO SNPs were only associated with body composition in PEAK-25 (p≤0.001). Our results suggest that genetic variation close to MC4R is associated with quantitative ultrasound and risk of fracture.

Genome-wide association study identified UQCC locus for spine bone size in humans

Bone size (BS) contributes significantly to the risk of osteoporotic fracture. Osteoporotic spine fracture is one of the most disabling outcomes of osteoporosis. This study aims to identify genomic loci underlying spine BS variation in humans. We performed a genome-wide association scan in 2286 unrelated Caucasians using Affymetrix 6.0 SNP arrays. Areal BS (cm(2)) at lumbar spine was measured using dual energy X-ray absorptiometry scanners. SNPs of interest were subjected to replication analyses and meta-analyses with additional two independent Caucasian populations (N=1000 and 2503) and one Chinese population (N=1627). In the initial GWAS, 91 SNPs were associated with spine BS (P<1.0E-4). Eight contiguous SNPs were found clustering in a haplotype block within UQCC gene (ubiquinol-cytochrome creductase complex chaperone). Association of the above eight SNPs with spine BS was replicated in one Caucasian and one Chinese populations. Meta-analyses (N=7416) generated much stronger association signals for these SNPs (e.g., P=1.86E-07 for SNP rs6060373), supporting association of UQCC with spine BS across ethnicities. This study identified a novel locus, i.e., the UQCC gene, for spine BS variation in humans. Future functional studies will contribute to elucidating the mechanisms by which UQCC regulates bone growth and development.

Suggestion of GLYAT gene underlying variation of bone size and body lean mass as revealed by a bivariate genome-wide association study

Bone and muscle, two major tissue types of musculoskeletal system, have strong genetic determination. Abnormality in bone and/or muscle may cause musculoskeletal diseases such as osteoporosis and sarcopenia. Bone size phenotypes (BSPs), such as hip bone size (HBS), appendicular bone size (ABS), are genetically correlated with body lean mass (mainly muscle mass). However, the specific genes shared by these phenotypes are largely unknown. In this study, we aimed to identify the specific genes with pleiotropic effects on BSPs and appendicular lean mass (ALM). We performed a bivariate genome-wide association study (GWAS) by analyzing ~690,000 SNPs in 1,627 unrelated Han Chinese adults (802 males and 825 females) followed by a replication study in 2,286 unrelated US Caucasians (558 males and 1,728 females). We identified 14 interesting single nucleotide polymorphisms (SNPs) that may contribute to variation of both BSPs and ALM, with p values <10(-6) in discovery stage. Among them, the association of three SNPs (rs2507838, rs7116722, and rs11826261) in/near GLYAT (glycine-N-acyltransferase) gene was replicated in US Caucasians, with p values ranging from 1.89 × 10(-3) to 3.71 × 10(-4) for ALM-ABS, from 5.14 × 10(-3) to 1.11 × 10(-2) for ALM-HBS, respectively. Meta-analyses yielded stronger association signals for rs2507838, rs7116722, and rs11826261, with pooled p values of 1.68 × 10(-8), 7.94 × 10(-8), 6.80 × 10(-8) for ALB-ABS and 1.22 × 10(-4), 9.85 × 10(-5), 3.96 × 10(-4) for ALM-HBS, respectively. Haplotype allele ATA based on these three SNPs was also associated with ALM-HBS and ALM-ABS in both discovery and replication samples. Interestingly, GLYAT was previously found to be essential to glucose metabolism and energy metabolism, suggesting the gene's dual role in both bone development and muscle growth. Our findings, together with the prior biological evidence, suggest the importance of GLYAT gene in co-regulation of bone phenotypes and body lean mass.

Systems genetics in "-omics" era: current and future development

The systems genetics is an emerging discipline that integrates high-throughput expression profiling technology and systems biology approaches for revealing the molecular mechanism of complex traits, and will improve our understanding of gene functions in the biochemical pathway and genetic interactions between biological molecules. With the rapid advances of microarray analysis technologies, bioinformatics is extensively used in the studies of gene functions, SNP-SNP genetic interactions, LD block-block interactions, miRNA-mRNA interactions, DNA-protein interactions, protein-protein interactions, and functional mapping for LD blocks. Based on bioinformatics panel, which can integrate "-omics" datasets to extract systems knowledge and useful information for explaining the molecular mechanism of complex traits, systems genetics is all about to enhance our understanding of biological processes. Systems biology has provided systems level recognition of various biological phenomena, and constructed the scientific background for the development of systems genetics. In addition, the next-generation sequencing technology and post-genome wide association studies empower the discovery of new gene and rare variants. The integration of different strategies will help to propose novel hypothesis and perfect the theoretical framework of systems genetics, which will make contribution to the future development of systems genetics, and open up a whole new area of genetics.

Clinical review: Genome-wide association studies of skeletal phenotypes: what we have learned and where we are headed

CONTEXT

The primary goals of genome-wide association studies (GWAS) are to discover new molecular and biological pathways involved in the regulation of bone metabolism that can be leveraged for drug development. In addition, the identified genetic determinants may be used to enhance current risk factor profiles.

EVIDENCE ACQUISITION

There have been more than 40 published GWAS on skeletal phenotypes, predominantly focused on dual-energy x-ray absorptiometry-derived bone mineral density (BMD) of the hip and spine.

EVIDENCE SYNTHESIS

Sixty-six BMD loci have been replicated across all the published GWAS, confirming the highly polygenic nature of BMD variation. Only seven of the 66 previously reported genes (LRP5, SOST, ESR1, TNFRSF11B, TNFRSF11A, TNFSF11, PTH) from candidate gene association studies have been confirmed by GWAS. Among 59 novel BMD GWAS loci that have not been reported by previous candidate gene association studies, some have been shown to be involved in key biological pathways involving the skeleton, particularly Wnt signaling (AXIN1, LRP5, CTNNB1, DKK1, FOXC2, HOXC6, LRP4, MEF2C, PTHLH, RSPO3, SFRP4, TGFBR3, WLS, WNT3, WNT4, WNT5B, WNT16), bone development: ossification (CLCN7, CSF1, MEF2C, MEPE, PKDCC, PTHLH, RUNX2, SOX6, SOX9, SPP1, SP7), mesenchymal-stem-cell differentiation (FAM3C, MEF2C, RUNX2, SOX4, SOX9, SP7), osteoclast differentiation (JAG1, RUNX2), and TGF-signaling (FOXL1, SPTBN1, TGFBR3). There are still 30 BMD GWAS loci without prior molecular or biological evidence of their involvement in skeletal phenotypes. Other skeletal phenotypes that either have been or are being studied include hip geometry, bone ultrasound, quantitative computed tomography, high-resolution peripheral quantitative computed tomography, biochemical markers, and fractures such as vertebral, nonvertebral, hip, and forearm.

CONCLUSIONS

Although several challenges lie ahead as GWAS moves into the next generation, there are prospects of new discoveries in skeletal biology. This review integrates findings from previous GWAS and provides a roadmap for future directions building on current GWAS successes.

ANKRD7 and CYTL1 are novel risk genes for alcohol drinking behavior

BACKGROUND

Alcohol dependence (AD) is a complex disorder characterized by impaired control over drinking. It is determined by both genetic and environmental factors. The recent approach of genome-wide association study (GWAS) is a powerful tool for identifying complex disease-associated susceptibility alleles, however, a few GWASs have been conducted for AD, and their results are largely inconsistent. The present study aimed to screen the loci associated with alcohol-related phenotypes using GWAS technology.

METHODS

A genome-wide association study with the behavior of regular alcohol drinking and alcohol consumption was performed to identify susceptibility genes associated with AD, using the Affymetrix 500K SNP array in an initial sample consisting of 904 unrelated Caucasian subjects. Then, the initial results in GWAS were replicated in three independent samples: 1972 Caucasians in 593 nuclear families, 761 unrelated Caucasian subjects, and 2955 unrelated Chinese Hans.

RESULTS

Several genes were associated with the alcohol-related phenotypes at the genome-wide significance level, with the ankyrin repeat domain 7 gene (ANKRD7) showing the strongest statistical evidence for regular alcohol drinking and suggestive statistical evidence for alcohol consumption. In addition, certain haplotypes within the ANKRD7 and cytokine-like1 (CYTL1) genes were significantly associated with regular drinking behavior, such as one ANKRD7 block composed of the SNPs rs6466686-rs4295599-rs12531086 (P = 6.51 × 10(-8)). The association of alcohol consumption was successfully replicated with rs4295599 in ANKRD7 gene in independent Caucasian nuclear families and independent unrelated Chinese Hans, and with rs16836497 in CYTL1 gene in independent unrelated Caucasians. Meta-analyses based on both the GWAS and replication samples further supported the observed significant associations between the ANKRD7 or CYTL1 gene and alcohol consumption.

CONCLUSION

The evidence suggests that ANKRD7 and CYTL1 genes may play an important role in the variance in AD risk.

Genome-wide association study identifies HMGN3 locus for spine bone size variation in Chinese

Bone size (BS) is one of the major risk factors for osteoporotic fractures. BS variation is genetically determined to a substantial degree with heritability over 50%, but specific genes underlying variation of BS are still largely unknown. To identify specific genes for BS in Chinese, initial genome-wide association scan (GWAS) study and follow-up replication study were performed. In initial GWAS study, a group of 12 contiguous single-nucleotide polymorphism (SNP)s, which span a region of ~25 kb and locate at the upstream of HMGN3 gene (high-mobility group nucleosomal binding domain 3), achieved moderate association signals for spine BS, with P values ranging from 6.2E-05 to 1.8E-06. In the follow-up replication study, eight of the 12 SNPs were detected suggestive replicate associations with BS in 1,728 unrelated female Caucasians, which have well-known differences from Chinese in ethnic genetic background. The SNPs in the region of HMGN3 gene formed a tightly combined haplotype block in both Chinese and Caucasians. The results suggest that the genomic region containing HMGN3 gene may be associated with spine BS in Chinese.

Insights into the genetics of osteoporosis from recent genome-wide association studies

Osteoporosis, which is characterised by reduced bone mineral density (BMD) and an increased risk of fragility fractures, is the result of a complex interaction between environmental factors and genetic variants that confer susceptibility. Heritability studies have shown that BMD and other osteoporosis-related traits such as ultrasound properties of bone, skeletal geometry and bone turnover have significant inheritable components. Although previous linkage and candidate gene studies have provided few replicated loci for osteoporosis, genome-wide association approaches have produced clear and reproducible findings. To date, 20 genome-wide association studies (GWASs) for osteoporosis and related traits have been conducted, identifying dozens of genes. Further meta-analyses of GWAS data and deep resequencing of rare variants will uncover more novel susceptibility loci and ultimately provide possible therapeutic targets for fracture prevention.

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.

Common variants in a novel gene, FONG on chromosome 2q33.1 confer risk of osteoporosis in Japanese

Osteoporosis is a common disease characterized by low bone mass, decreased bone quality and increased predisposition to fracture. Genetic factors have been implicated in its etiology; however, the specific genes related to susceptibility to osteoporosis are not entirely known. To detect susceptibility genes for osteoporosis, we conducted a genome-wide association study in Japanese using ∼270,000 SNPs in 1,747 subjects (190 cases and 1,557 controls) followed by multiple levels of replication of the association using a total of ∼5,000 subjects (2,092 cases and 3,114 controls). Through these staged association studies followed by resequencing and linkage disequilibrium mapping, we identified a single nucleotide polymorphism (SNP), rs7605378 associated with osteoporosis. (combined P = 1.51×10⁻⁸, odds ratio = 1.25). This SNP is in a previously unknown gene on chromosome 2q33.1, FONG. FONG is predicted to encode a 147 amino-acid protein with a formiminotransferase domain in its N-terminal (FTCD_N domain) and is ubiquitously expressed in various tissues including bone. Our findings would give a new insight into osteoporosis etiology and pathogenesis.

Multilocus association testing of quantitative traits based on partial least-squares analysis

Because of combining the genetic information of multiple loci, multilocus association studies (MLAS) are expected to be more powerful than single locus association studies (SLAS) in disease genes mapping. However, some researchers found that MLAS had similar or reduced power relative to SLAS, which was partly attributed to the increased degrees of freedom (dfs) in MLAS. Based on partial least-squares (PLS) analysis, we develop a MLAS approach, while avoiding large dfs in MLAS. In this approach, genotypes are first decomposed into the PLS components that not only capture majority of the genetic information of multiple loci, but also are relevant for target traits. The extracted PLS components are then regressed on target traits to detect association under multilinear regression. Simulation study based on real data from the HapMap project were used to assess the performance of our PLS-based MLAS as well as other popular multilinear regression-based MLAS approaches under various scenarios, considering genetic effects and linkage disequilibrium structure of candidate genetic regions. Using PLS-based MLAS approach, we conducted a genome-wide MLAS of lean body mass, and compared it with our previous genome-wide SLAS of lean body mass. Simulations and real data analyses results support the improved power of our PLS-based MLAS in disease genes mapping relative to other three MLAS approaches investigated in this study. We aim to provide an effective and powerful MLAS approach, which may help to overcome the limitations of SLAS in disease genes mapping.

Confounding from cryptic relatedness in haplotype-based association studies

Cryptic relatedness was suggested to be an important source of confounding in population-based association studies (PBAS). The impact of cryptic relatedness on the performance of haplotype phase inference and haplotype-based association tests is not clear. In this study, we used the Hapmap genetic data to simulate a set of related samples. We evaluated the accuracy of haplotype phase inferred by PHASE 2.1 and calculated the power, type I error rates, accuracy and positive prediction value (PPV) of haplotype frequency-based association tests (HFAT) and haplotype similarity-based association tests (HSAT) under various scenarios, considering relatedness levels, disease models and sample sizes. Cryptic relatedness appeared to slightly increase the accuracy of haplotype phase inference. We observed significant negative effect of cryptic relatedness on the performance of HFAT and HSAT. Ignoring cryptic relatedness may increase spurious association results in haplotype-based PBAS.

Molecular genetic studies of gene identification for osteoporosis: the 2009 update

Osteoporosis is a complex human disease that results in increased susceptibility to fragility fractures. It can be phenotypically characterized using several traits, including bone mineral density, bone size, bone strength, and bone turnover markers. The identification of gene variants that contribute to osteoporosis phenotypes, or responses to therapy, can eventually help individualize the prognosis, treatment, and prevention of fractures and their adverse outcomes. Our previously published reviews have comprehensively summarized the progress of molecular genetic studies of gene identification for osteoporosis and have covered the data available to the end of September 2007. This review represents our continuing efforts to summarize the important and representative findings published between October 2007 and November 2009. The topics covered include genetic association and linkage studies in humans, transgenic and knockout mouse models, as well as gene-expression microarray and proteomics studies. Major results are tabulated for comparison and ease of reference. Comments are made on the notable findings and representative studies for their potential influence and implications on our present understanding of the genetics of osteoporosis.

Pathway-based genome-wide association analysis identified the importance of regulation-of-autophagy pathway for ultradistal radius BMD

Wrist fracture is not only one of the most common osteoporotic fractures but also a predictor of future fractures at other sites. Wrist bone mineral density (BMD) is an important determinant of wrist fracture risk, with high heritability. Specific genes underlying wrist BMD variation are largely unknown. Most published genome-wide association studies (GWASs) have focused only on a few top-ranking single-nucleotide polymorphisms (SNPs)/genes and considered each of the identified SNPs/genes independently. To identify biologic pathways important to wrist BMD variation, we used a novel pathway-based analysis approach in our GWAS of wrist ultradistal radius (UD) BMD, examining approximately 500,000 SNPs genome-wide from 984 unrelated whites. A total of 963 biologic pathways/gene sets were analyzed. We identified the regulation-of-autophagy (ROA) pathway that achieved the most significant result (p = .005, q(fdr) = 0.043, p(fwer) = 0.016) for association with UD BMD. The ROA pathway also showed significant association with arm BMD in the Framingham Heart Study sample containing 2187 subjects, which further confirmed our findings in the discovery cohort. Earlier studies indicated that during endochondral ossification, autophagy occurs prior to apoptosis of hypertrophic chondrocytes, and it also has been shown that some genes in the ROA pathway (e.g., INFG) may play important roles in osteoblastogenesis or osteoclastogenesis. Our study supports the potential role of the ROA pathway in human wrist BMD variation and osteoporosis. Further functional evaluation of this pathway to determine the mechanism by which it regulates wrist BMD should be pursued to provide new insights into the pathogenesis of wrist osteoporosis.

Osteocalcin gene polymorphisms influence concentration of serum osteocalcin and enhance fracture identification

Osteoporosis is a major health problem affecting more than 75 million people throughout Europe, the United States, and Japan. Epidemiologic studies have determined that both genetic and environmental factors contribute to the pathogenesis of osteoporosis. We have investigated the association between polymorphisms at the osteocalcin locus and variables linked to bone health. Osteocalcin provides a link between bone and energy metabolism, hence its potential importance as an osteoporosis candidate gene. In this study, we included a total of 996 women (all aged 75 years) from the Osteoporosis Prospective Risk Assessment (OPRA) cohort. We sequenced the osteocalcin gene along with flanking regions to search for novel coding polymorphisms. We also analyzed four polymorphisms selected from within and flanking regions of the osteocalcin gene to study their association with serum total osteocalcin levels (S-TotalOC), total-body (TB) bone mineral density (BMD), fracture, TB fat mass, and body mass index (BMI). The promoter polymorphism rs1800247 was significantly associated with S-TotalOC (p = .012) after controlling for BMI and TB BMD. The polymorphism rs1543297 was significantly associated with prospectively occurring fractures (p = .008). In a model taking into account rs1543297 and rs1800247, along with TB BMD, BMI, smoking, and S-TotalOC, the polymorphisms together were able to identify an additional 6% of women who sustained a fracture (p = .02). We found no association between the polymorphisms and TB BMD, BMI, or TB fat mass. In conclusion, polymorphisms in and around the osteocalcin locus are significantly associated with S-TotalOC and fracture. Genotyping at the osteocalcin locus could add valuable information in the identification of women at risk of osteoporosis.

Human difference in the genomic era: Facilitating a socially responsible dialogue

Background

The study of human genetic variation has been advanced by research such as genome-wide association studies, which aim to identify variants associated with common, complex diseases and traits. Significant strides have already been made in gleaning information on susceptibility, treatment, and prevention of a number of disorders. However, as genetic researchers continue to uncover underlying differences between individuals, there is growing concern that observed population-level differences will be inappropriately generalized as inherent to particular racial or ethnic groups and potentially perpetuate negative stereotypes.

Discussion

We caution that imprecision of language when conveying research conclusions, compounded by the potential distortion of findings by the media, can lead to the stigmatization of racial and ethnic groups.

Summary

It is essential that the scientific community and with those reporting and disseminating research findings continue to foster a socially responsible dialogue about genetic variation and human difference.

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.

PLCL1 rs7595412 variation is not associated with hip bone size variation in postmenopausal Danish women

BACKGROUND

Bone size (BS) variation is under strong genetic control and plays an important role in determining bone strength and fracture risk. Recently, a genome-wide association study identified polymorphisms associated with hip BS variation in the PLCL1 (phospholipase c-like 1) locus. Carriers of the major A allele of the most significant polymorphism, rs7595412, have around 17% larger hip BS than non-carriers. We therefore hypothesized that this polymorphism may also influence postmenopausal complications.

METHODS

The effects of rs7595412 on hip BS, bone mineral density (BMD), vertebral fractures, serum Crosslaps and osteocalcin levels were analyzed in 1,191 postmenopausal Danish women.

RESULTS

This polymorphism had no influence on hip and spine BS as well as on femur and spine BMD. Women carrying at least one copy of the A allele had lower levels of serum osteocalcin as compared with those homozygous for the G allele (p = 0.03) whereas no effect on serum Crosslaps was detected. Furthermore, women homozygous for the A allele were more affected by vertebral fractures than those carrying at least one copy of the G allele (p = 0.04).

CONCLUSIONS

In postmenopausal women, our results suggest that the PLCL1 rs7595412 polymorphism has no obvious effect on hip BS or BMD but may be nominally associated with increased proportion of vertebral fracture and increased levels of osteocalcin.

Genetics of osteoporosis: accelerating pace in gene identification and validation

Osteoporosis is characterized by low bone mineral density and structural deterioration of bone tissue, leading to an increased risk of fractures. It is the most common metabolic bone disorder worldwide, affecting one in three women and one in eight men over the age of 50. In the past 15 years, a large number of genes have been reported as being associated with osteoporosis. However, only in the past 4 years we have witnessed an accelerated pace in identifying and validating osteoporosis susceptibility loci. This increase in pace is mostly due to large-scale association studies, meta-analyses, and genome-wide association studies of both single nucleotide polymorphisms and copy number variations. A comprehensive review of these developments revealed that, to date, at least 15 genes (VDR, ESR1, ESR2, LRP5, LRP4, SOST, GRP177, OPG, RANK, RANKL, COLIA1, SPP1, ITGA1, SP7, and SOX6) can be reasonably assigned as confirmed osteoporosis susceptibility genes, whereas, another >30 genes are promising candidate genes. Notably, confirmed and promising genes are clustered in three biological pathways, the estrogen endocrine pathway, the Wnt/beta-catenin signaling pathway, and the RANKL/RANK/OPG pathway. New biological pathways will certainly emerge when more osteoporosis genes are identified and validated. These genetic findings may provide new routes toward improved therapeutic and preventive interventions of this complex disease.

A PCA-based method for ancestral informative markers selection in structured populations

Identification of population structure can help trace population histories and identify disease genes. Structured association (SA) is a commonly used approach for population structure identification and association mapping. A major issue with SA is that its performance greatly depends on the informativeness and the numbers of ancestral informative markers (AIMs). Present major AIM selection methods mostly require prior individual ancestry information, which is usually not available or uncertain in practice. To address this potential weakness, we herein develop a novel approach for AIM selection based on principle component analysis (PCA), which does not require prior ancestry information of study subjects. Our simulation and real genetic data analysis results suggest that, with equivalent AIMs, PCA-based selected AIMs can significantly increase the accuracy of inferred individual ancestries compared with traditionally randomly selected AIMs. Our method can easily be applied to whole genome data to select a set of highly informative AIMs in population structure, which can then be used to identify potential population structure and correct possible statistical biases caused by population stratification.

Correcting for cryptic relatedness in population-based association studies of continuous traits

Cryptic relatedness was suggested to be an important source of confounding in population-based association studies (PBAS). The magnitude and manner of cryptic relatedness affecting the performance of PBAS of continuous traits remain to be investigated. We simulated a set of related samples through biased sampling and inbreeding, and evaluated the power and type I error rates of simple association tests (SAT) without correcting for cryptic relatedness. We also used extended likelihood ratio tests (ELRT) to conduct PBAS accounting for cryptic relatedness, and compared it with genomic control (GC). Cryptic relatedness decreased the power as well as increased the type I error rates of SAT in both biased sampling and inbreeding models. The impact of cryptic relatedness on the performance of SAT appeared to be limited in the biased sampling model. However, cryptic relatedness in inbred populations may result in excessive false positive results of SAT. Compared with SAT and GC, ELRT obtained improved power and type I error rates under various scenarios. Ignoring cryptic relatedness may increase spurious association results in PBAS. Our ELRT provides a novel approach to control cryptic relatedness in PBAS of human continuous traits.

Bivariate genome-wide linkage analysis of femoral bone traits and leg lean mass: Framingham study

The risk of osteoporotic fracture is a function of both applied muscle mass and bone tissue distribution. Leg lean mass (LLM) and femoral bone geometry are both known to have substantial genetic components. Therefore, we estimated shared heritability (h(2)) and performed linkage analysis to identify chromosomal regions governing both LLM and bone geometry. A genome-wide scan (using 636 microsatellite markers) for linkage analyses was performed on 1346 adults from 327 extended families of the Framingham study. DXA measures were LLM, femoral neck length, neck-shaft angle (NSA), subperiosteal width, cross-sectional area (CSA), and section modulus (Z) at the femoral narrow neck and shaft (S) regions. Variance component linkage analysis was performed on normalized residuals (adjusted for age, height, BMI, and estrogen status in women). The results indicated substantial h(2) for LLM (0.42 +/- 0.07) that was comparable to bone geometry traits. Phenotypic correlations between LLM and bone geometry phenotypes ranged from 0.033 with NSA (p > 0.05) to 0.251 with S_Z (p < 0.001); genetic correlations ranged from 0.087 (NSA, p > 0.05) to 0.454 (S_Z, p < 0.001). Univariate linkage analysis of covariate-adjusted LLM identified no chromosomal regions with LOD scores >or=2.0; however, bivariate analysis identified two loci with LOD scores >3.0, shared by LLM with S_CSA on chromosome 12p12.3-12p13.2, and with NSA, on 14q21.3-22.1. In conclusion, we identified chromosomal regions potentially linked to both LLM and femoral bone geometry. Identification and subsequent characterization of these shared loci may further elucidate the genetic contributions to both osteoporosis and sarcopenia.

Genome-wide association and follow-up replication studies identified ADAMTS18 and TGFBR3 as bone mass candidate genes in different ethnic groups

To identify and validate genes associated with bone mineral density (BMD), which is a prominent osteoporosis risk factor, we tested 379,319 SNPs in 1000 unrelated white U.S. subjects for associations with BMD. For replication, we genotyped the most significant SNPs in 593 white U.S. families (1972 subjects), a Chinese hip fracture (HF) sample (350 cases, 350 controls), a Chinese BMD sample (2955 subjects), and a Tobago cohort of African ancestry (908 males). Publicly available Framingham genome-wide association study (GWAS) data (2953 whites) were also used for in silico replication. The GWAS detected two BMD candidate genes, ADAMTS18 (ADAM metallopeptidase with thrombospondin type 1 motif, 18) and TGFBR3 (transforming growth factor, beta receptor III). Replication studies verified the significant findings by GWAS. We also detected significant associations with hip fracture for ADAMTS18 SNPs in the Chinese HF sample. Meta-analyses supported the significant associations of ADAMTS18 and TGFBR3 with BMD (p values: 2.56 x 10(-5) to 2.13 x 10(-8); total sample size: n = 5925 to 9828). Electrophoretic mobility shift assay suggested that the minor allele of one significant ADAMTS18 SNP might promote binding of the TEL2 factor, which may repress ADAMTS18 expression. The data from NCBI GEO expression profiles also showed that ADAMTS18 and TGFBR3 genes were differentially expressed in subjects with normal skeletal fracture versus subjects with nonunion skeletal fracture. Overall, the evidence supports that ADAMTS18 and TGFBR3 might underlie BMD determination in the major human ethnic groups.

Genome-wide copy-number-variation study identified a susceptibility gene, UGT2B17, for osteoporosis

Osteoporosis, a highly heritable disease, is characterized mainly by low bone-mineral density (BMD), poor bone geometry, and/or osteoporotic fractures (OF). Copy-number variation (CNV) has been shown to be associated with complex human diseases. The contribution of CNV to osteoporosis has not been determined yet. We conducted case-control genome-wide CNV analyses, using the Affymetrix 500K Array Set, in 700 elderly Chinese individuals comprising 350 cases with homogeneous hip OF and 350 matched controls. We constructed a genomic map containing 727 CNV regions in Chinese individuals. We found that CNV 4q13.2 was strongly associated with OF (p = 2.0 x 10(-4), Bonferroni-corrected p = 0.02, odds ratio = 1.73). Validation experiments using PCR and electrophoresis, as well as real-time PCR, further identified a deletion variant of UGT2B17 in CNV 4q13.2. Importantly, the association between CNV of UGT2B17 and OF was successfully replicated in an independent Chinese sample containing 399 cases with hip OF and 400 controls. We further examined this CNV's relevance to major risk factors for OF (i.e., hip BMD and femoral-neck bone geometry) in both Chinese (689 subjects) and white (1000 subjects) samples and found consistently significant results (p = 5.0 x 10(-4) -0.021). Because UGT2B17 encodes an enzyme catabolizing steroid hormones, we measured the concentrations of serum testosterone and estradiol for 236 young Chinese males and assessed their UGT2B17 copy number. Subjects without UGT2B17 had significantly higher concentrations of testosterone and estradiol. Our findings suggest the important contribution of CNV of UGT2B17 to the pathogenesis of osteoporosis.