Powerful bivariate genome-wide association analyses suggest the SOX6 gene influencing both obesity and osteoporosis phenotypes in males

Bivariate quantitative Bayesian LASSO for detecting association of rare haplotypes with two correlated continuous phenotypes

In genetic association studies, the multivariate analysis of correlated phenotypes offers statistical and biological advantages compared to analyzing one phenotype at a time. The joint analysis utilizes additional information contained in the correlation and avoids multiple testing. It also provides an opportunity to investigate and understand shared genetic mechanisms of multiple phenotypes. Bivariate logistic Bayesian LASSO (LBL) was proposed earlier to detect rare haplotypes associated with two binary phenotypes or one binary and one continuous phenotype jointly. There is currently no haplotype association test available that can handle multiple continuous phenotypes. In this study, by employing the framework of bivariate LBL, we propose bivariate quantitative Bayesian LASSO (QBL) to detect rare haplotypes associated with two continuous phenotypes. Bivariate QBL removes unassociated haplotypes by regularizing the regression coefficients and utilizing a latent variable to model correlation between two phenotypes. We carry out extensive simulations to investigate the performance of bivariate QBL and compare it with that of a standard (univariate) haplotype association test, Haplo.score (applied twice to two phenotypes individually). Bivariate QBL performs better than Haplo.score in all simulations with varying degrees of power gain. We analyze Genetic Analysis Workshop 19 exome sequencing data on systolic and diastolic blood pressures and detect several rare haplotypes associated with the two phenotypes.

Deciphering the chromatin spatial organization landscapes during BMMSC differentiation

The differentiation imbalance in bone marrow mesenchymal stem cells (BMMSCs) is critical for the development of bone density diseases as the population ages. BMMSCs are precursor cells for osteoblasts and adipocytes; however, the chromatin organization landscapes during BMMSC differentiation remain elusive. In this study, we systematically delineate the four-dimensional (4D) genome and dynamic epigenetic atlas of BMMSCs by RNA sequencing (RNA-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), and high-throughput chromosome conformation capture (Hi-C). The structure analyses reveal 17.5% common and 28.5%-30% specific loops among BMMSCs, osteoblasts, and adipocytes. The subsequent correlation of genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) data with multi-omics analysis reveal 274 genes and 3634 single nucleotide polymorphisms (SNPs) associated with bone degeneration and osteoporosis (OP). We hypothesize that SNP mutations affect transcription factor (TF) binding sites, thereby affecting changes in gene expression. Furthermore, 26 motifs, 260 TFs, and 291 SNPs are identified to affect the eQTL. Among these genes, DAAM2, TIMP2, and TMEM241 were found to be essential for diseases such as bone degeneration and OP and may serve as potential drug targets.

The Role of SOX Transcription Factors in Ageing and Age-Related Diseases

The quest for eternal youth and immortality is as old as humankind. Ageing is an inevitable physiological process accompanied by many functional declines that are driving factors for age-related diseases. Stem cell exhaustion is one of the major hallmarks of ageing. The SOX transcription factors play well-known roles in self-renewal and differentiation of both embryonic and adult stem cells. As a consequence of ageing, the repertoire of adult stem cells present in various organs steadily declines, and their dysfunction/death could lead to reduced regenerative potential and development of age-related diseases. Thus, restoring the function of aged stem cells, inducing their regenerative potential, and slowing down the ageing process are critical for improving the health span and, consequently, the lifespan of humans. Reprograming factors, including SOX family members, emerge as crucial players in rejuvenation. This review focuses on the roles of SOX transcription factors in stem cell exhaustion and age-related diseases, including neurodegenerative diseases, visual deterioration, chronic obstructive pulmonary disease, osteoporosis, and age-related cancers. A better understanding of the molecular mechanisms of ageing and the roles of SOX transcription factors in this process could open new avenues for developing novel strategies that will delay ageing and prevent age-related diseases.

Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data

In recent years, methods were proposed for assigning feature importance scores to measure the contribution of individual features. While in some cases the goal is to understand a specific model, in many cases the goal is to understand the contribution of certain properties (features) to a real-world phenomenon. Thus, a distinction has been made between feature importance scores that explain a model and scores that explain the data. When explaining the data, machine learning models are used as proxies in settings where conducting many real-world experiments is expensive or prohibited. While existing feature importance scores show great success in explaining models, we demonstrate their limitations when explaining the data, especially in the presence of correlations between features. Therefore, we develop a set of axioms to capture properties expected from a feature importance score when explaining data and prove that there exists only one score that satisfies all of them, the Marginal Contribution Feature Importance (MCI). We analyze the theoretical properties of this score function and demonstrate its merits empirically.

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.

Association between osteoporosis and menopause in relation to SOX6 rs297325 variant in Taiwanese women

Objective:

Osteoporosis, the most prevalent bone disorder in humans, is a global public health issue and its relationship with menopause is well-established. The interaction between menopause and genes on osteoporosis risk is, however, yet to be fully elucidated. We assessed the association between menopause and osteoporosis in relation to the SOX6 rs297325 variant in Taiwanese women.

Methods:

There were 7,581 female participants, aged 30 to 70 years old. Information on SOX6 rs297325 and menopause were obtained from the Taiwan Biobank Database while that on osteoporosis was obtained from the National Health Insurance Research Database.

Results:

Menopause but not SOX6 rs297325 was significantly associated with a higher risk of osteoporosis (odds ratio [OR] = 1.48; 95% confidence interval [CI] = 1.04-2.10). The interaction between menopause and rs297325 on osteoporosis was significant (P = 0.0216). After stratification by rs297325 genotypes, the risk of osteoporosis was significantly higher in menopausal women having the TT + CC genotype (OR = 2.02; 95% CI = 1.21-3.38). After stratification by menopausal status and rs297325 genotypes, the OR; 95% CI was 0.62; 0.38 to 0.99 in premenopausal women with the TC + CC genotype and 1.24; 0.82 to 1.88 in menopausal women with the TC + CC genotype.

Conclusion:

SOX6 rs297325 was not significantly associated with osteoporosis but might have modulated the association between menopause and osteoporosis. The risk of osteoporosis was higher in menopausal women with the TC + CC genotype but lower in premenopausal women with the TC + CC genotype.

Identification of pleiotropic loci underlying hip bone mineral density and trunk lean mass

Bone mineral density (BMD) and lean body mass (LBM) not only have a considerable heritability each, but also are genetically correlated. However, common genetic determinants shared by both traits are largely unknown. In the present study, we performed a bivariate genome-wide association study (GWAS) meta-analysis of hip BMD and trunk lean mass (TLM) in 11,335 subjects from 6 samples, and performed replication in estimated heel BMD and TLM in 215,234 UK Biobank (UKB) participants. We identified 2 loci that nearly attained the genome-wide significance (GWS, p < 5.0 × 10-8) level in the discovery GWAS meta-analysis and that were successfully replicated in the UKB sample: 11p15.2 (lead SNP rs12800228, discovery p = 2.88 × 10-7, replication p = 1.95 × 10-4) and 18q21.32 (rs489693, discovery p = 1.67 × 10-7, replication p = 1.17 × 10-3). The above 2 pleiotropic loci may play a pleiotropic role for hip BMD and TLM development. So our findings provide useful insights that further enhance our understanding of genetic interplay between BMD and LBM.

The transcriptome-wide association search for genes and genetic variants which associate with BMI and gestational weight gain in women with type 1 diabetes

BACKGROUND

Clinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes; however, the genetic basis of the latter is rather unclear. Here we aim to find genes and genetic variants which influence BMI and/or GWG.

METHODS

We have genotyped 316 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays. The GIANT, ARIC and T2D-GENES summary statistics were used for TWAS (performed with PrediXcan) in adipose tissue. Next, the analysis of association of imputed expression with BMI in the general and diabetic cohorts (Analysis 1 and 2) or GWG (Analysis 3 and 4) was performed, followed by variant association analysis (1 Mb around identified loci) with the mentioned phenotypes.

RESULTS

In Analysis 1 we have found 175 BMI associated genes and 19 variants (p < 10-4) which influenced GWG, with the strongest association for rs11465293 in CCL24 (p = 3.18E-06). Analysis 2, with diabetes included in the model, led to discovery of 1812 BMI associated loci and 207 variants (p < 10-4) influencing GWG, with the strongest association for rs9690213 in PODXL (p = 9.86E-07). In Analysis 3, among 648 GWG associated loci, 2091 variants were associated with BMI (FDR < 0.05). In Analysis 4, 7 variants in GWG associated loci influenced BMI in the ARIC cohort.

CONCLUSIONS

Here, we have shown that loci influencing BMI might have an impact on GWG and GWG associated loci might influence BMI, both in the general and T1DM cohorts. The results suggest that both phenotypes are related to insulin signaling, glucose homeostasis, mitochondrial metabolism, ubiquitinoylation and inflammatory responses.

Three pleiotropic loci associated with bone mineral density and lean body mass

Both bone mineral density (BMD) and lean body mass (LBM) are important physiological measures with strong genetic determination. Besides, BMD and LBM might have common genetic factors. Aiming to identify pleiotropic genomic loci underlying BMD and LBM, we performed bivariate genome-wide association study meta-analyses of femoral neck bone mineral density and LBM at arms and legs, and replicated in the large-scale UK Biobank cohort sample. Combining the results from discovery meta-analysis and replication sample, we identified three genomic loci at the genome-wide significance level (p < 5.0 × 10-8): 2p23.2 (lead SNP rs4477866, discovery p = 3.47 × 10-8, replication p = 1.03 × 10-4), 16q12.2 (rs1421085, discovery p = 2.04 × 10-9, replication p = 6.47 × 10-14) and 18q21.32 (rs11152213, discovery p = 3.47 × 10-8, replication p = 6.69 × 10-6). Our findings not only provide useful insights into lean mass and bone mass development, but also enhance our understanding of the potential genetic correlation between BMD and LBM.

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 genomic variants at 17q21.31 associated with bone mineral density and body fat mass: a bivariate genome-wide association analysis

Osteoporosis and obesity are two severe complex diseases threatening public health worldwide. Both diseases are under strong genetic determinants as well as genetically correlated. Aiming to identify pleiotropic genes underlying obesity and osteoporosis, we performed a bivariate genome-wide association (GWA) meta-analysis of hip bone mineral density (BMD) and total body fat mass (TBFM) in 12,981 participants from seven samples, and followed by in silico replication in the UK biobank (UKB) cohort sample (N = 217,822). Combining the results from discovery meta-analysis and replication sample, we identified one novel locus, 17q21.31 (lead SNP rs12150327, NC_000017.11:g.44956910G > A, discovery bivariate P = 4.83 × 10^-9, replication P = 5.75 × 10^-5) at the genome-wide significance level (ɑ = 5.0 × 10^-8), which may have pleiotropic effects to both hip BMD and TBFM. Functional annotations highlighted several candidate genes, including KIF18B, C1QL1, and PRPF19 that may exert pleiotropic effects to the development of both body mass and bone mass. Our findings can improve our understanding of the etiology of osteoporosis and obesity, as well as shed light on potential new therapies.

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.

Two novel pleiotropic loci associated with osteoporosis and abdominal obesity

Aiming to uncover a shared genetic basis of abdominal obesity and osteoporosis, we performed a bivariate GWAS meta-analysis of femoral neck BMD (FNK-BMD) and trunk fat mass adjusted by trunk lean mass (TFMadj) in 11,496 subjects from 6 samples, followed by in silico replication in the large-scale UK Biobank (UKB) cohort. A series of functional investigations were conducted on the identified variants. Bivariate GWAS meta-analysis identified two novel pleiotropic loci 12q15 (lead SNP rs73134637, p = 3.45 × 10-7) and 10p14 (lead SNP rs2892347, p = 2.63 × 10-7) that were suggestively associated and that were replicated in the analyses of related traits in the UKB sample (osteoporosis p = 0.06 and 0.02, BMI p = 0.03 and 4.61 × 10-3, N up to 499,520). Cis-eQTL analysis demonstrated that allele C at rs73134637 was positively associated with IFNG expression in whole blood (N = 369, p = 0.04), and allele A at rs11254759 (10p14, p = 9.49 × 10-7) was negatively associated with PRKCQ expression in visceral adipose tissue (N = 313, p = 0.04) and in lymphocytes (N = 117, p = 0.03). As a proof-of-principle experiment, the function of rs11254759, which is 235 kb 5'-upstream from PRKCQ gene, was investigated by the dual-luciferase reporter assay, which clearly showed that the haplotype carrying rs11254759 regulated PRKCQ expression by upregulating PRKCQ promoter activity (p = 4.60 × 10-7) in an allelic specific manner. Mouse model analysis showed that heterozygous PRKCQ deficient mice presented decreased fat mass compared to wild-type control mice (p = 3.30 × 10-3). Mendelian randomization analysis demonstrated that both FNK-BMD and TFMadj were causally associated with fracture risk (p = 1.26 × 10-23 and 1.18 × 10-11). Our findings may provide useful insights into the genetic association between osteoporosis and abdominal obesity.

De Novo SOX6 Variants Cause a Neurodevelopmental Syndrome Associated with ADHD, Craniosynostosis, and Osteochondromas

SOX6 belongs to a family of 20 SRY-related HMG-box-containing (SOX) genes that encode transcription factors controlling cell fate and differentiation in many developmental and adult processes. For SOX6, these processes include, but are not limited to, neurogenesis and skeletogenesis. Variants in half of the SOX genes have been shown to cause severe developmental and adult syndromes, referred to as SOXopathies. We here provide evidence that SOX6 variants also cause a SOXopathy. Using clinical and genetic data, we identify 19 individuals harboring various types of SOX6 alterations and exhibiting developmental delay and/or intellectual disability; the individuals are from 17 unrelated families. Additional, inconstant features include attention-deficit/hyperactivity disorder (ADHD), autism, mild facial dysmorphism, craniosynostosis, and multiple osteochondromas. All variants are heterozygous. Fourteen are de novo, one is inherited from a mosaic father, and four offspring from two families have a paternally inherited variant. Intragenic microdeletions, balanced structural rearrangements, frameshifts, and nonsense variants are predicted to inactivate the SOX6 variant allele. Four missense variants occur in residues and protein regions highly conserved evolutionarily. These variants are not detected in the gnomAD control cohort, and the amino acid substitutions are predicted to be damaging. Two of these variants are located in the HMG domain and abolish SOX6 transcriptional activity in vitro. No clear genotype-phenotype correlations are found. Taken together, these findings concur that SOX6 haploinsufficiency leads to a neurodevelopmental SOXopathy that often includes ADHD and abnormal skeletal and other features.

A road map for understanding molecular and genetic determinants of osteoporosis

Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in 'systems genetics and genomics'. In this Review, we highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis. Furthermore, we summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis. The integration of multiple technologies will provide a road map to illuminate the complex pathogenesis of osteoporosis, especially from molecular functional aspects, in vivo in humans.

Analysis of RAMP3 gene polymorphism with body composition and bone density in young and elderly women

Background and aim

The Receptor Activity Modifying Proteins (RAMPs) are a group of accessory proteins, of which there are three in humans, that interact with a number of G-protein coupled receptors (GPCR) and play various roles in regulation of endocrine signaling. Studies in RAMP3 knockout (KO) mice reveal an age related phenotype with altered metabolic regulation and high bone mass. To translate these findings into a clinically relevant perspective, we investigated the association between RAMP3 gene variants, body composition and bone phenotypes in two population-based cohorts of Swedish women.

Methods

Five single nucleotide polymorphisms (SNP) in the vicinity of the RAMP3 gene were genotyped in the PEAK-25 cohort (n = 1061; 25 years) and OPRA (n = 1044; 75 years). Bone mineral density (BMD), fat mass and lean mass (total body; regional) were measured by DXA at baseline, 5 and 10 year follow-up.

Results

BMD did not differ with RAMP3 genotype in either cohort, although fracture risk was increased in the elderly women (OR 2.695 [95% CI 1.514–4.801]). Fat mass tended to be higher with RAMP3 SNPs; although only in elderly women. In the young women, changes in BMI and fat mass between ages 25–35 differed by genotype (p = 0.001; p < 0.001).

Conclusion

Variation in RAMP3 may contribute to age-related changes in body composition and risk of fracture.

Regulatory Role of RNA N6-Methyladenosine Modification in Bone Biology and Osteoporosis

Osteoporosis is a metabolic skeletal disorder in which bone mass is depleted and bone structure is destroyed to the degree that bone becomes fragile and prone to fractures. Emerging evidence suggests that N⁶-methyladenosine (m⁶A) modification, a novel epitranscriptomic marker, has a significant role in bone development and metabolism. M⁶A modification not only participates in bone development, but also plays important roles as writers and erasers in the osteoporosis. M⁶A methyltransferase METTL3 and demethyltransferase FTO involves in the delicate process between adipogenesis differentiation and osteogenic differentiation, which is important for the pathological development of osteoporosis. Conditional knockdown of the METTL3 in bone marrow stem cells (BMSCs) could suppress PI3K-Akt signaling, limit the expression of bone formation-related genes (such as Runx2 and Osterix), restrain the expression of vascular endothelial growth factor (VEGF) and down-regulate the decreased translation efficiency of parathyroid hormone receptor-1 mRNA. Meanwhile, knockdown of the METTL3 significantly promoted the adipogenesis process and janus kinase 1 (JAK1) protein expression via an m⁶A-dependent way. Specifically, there was a negative correlation between METTL3 expression and porcine BMSCs adipogenesis. The evidence above suggested that the relationship between METTL3 expression and adipogenesis was inverse, and osteogenesis was positive, respectively. Similarly, FTO regulated for BMSCs fate determination during osteoporosis through the GDF11-FTO-PPARγ axis, prompting the shift of MSC lineage commitment to adipocyte and inhibiting bone formation during osteoporosis. In this systematic review, we summarize the most up-to-date evidence of m⁶A RNA modification in osteoporosis and highlight the potential role of m⁶A in prevention, treatment, and management of osteoporosis.

Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43,870 individuals from the eMERGE network

The link between cardiovascular diseases and neurological disorders has been widely observed in the aging population. Disease prevention and treatment rely on understanding the potential genetic nexus of multiple diseases in these categories. In this study, we were interested in detecting pleiotropy, or the phenomenon in which a genetic variant influences more than one phenotype. Marker-phenotype association approaches can be grouped into univariate, bivariate, and multivariate categories based on the number of phenotypes considered at one time. Here we applied one statistical method per category followed by an eQTL colocalization analysis to identify potential pleiotropic variants that contribute to the link between cardiovascular and neurological diseases. We performed our analyses on ~530,000 common SNPs coupled with 65 electronic health record (EHR)-based phenotypes in 43,870 unrelated European adults from the Electronic Medical Records and Genomics (eMERGE) network. There were 31 variants identified by all three methods that showed significant associations across late onset cardiac- and neurologic- diseases. We further investigated functional implications of gene expression on the detected "lead SNPs" via colocalization analysis, providing a deeper understanding of the discovered associations. In summary, we present the framework and landscape for detecting potential pleiotropy using univariate, bivariate, multivariate, and colocalization methods. Further exploration of these potentially pleiotropic genetic variants will work toward understanding disease causing mechanisms across cardiovascular and neurological diseases and may assist in considering disease prevention as well as drug repositioning in future research.

SOX6 rs7117858 polymorphism is associated with osteoporosis and obesity-related phenotypes

BACKGROUND

SOX6 has been recently proposed as a pleiotropic gene for obesity and osteoporosis. The aim of this study was to investigate whether the rs7117858 genetic variant in SOX6 was associated with bone mass assessed by quantitative ultrasound (QUS) and obesity-related measures in a population of young adults.

METHODS

A cross-sectional study was conducted in 550 unrelated healthy individuals of Caucasian ancestry (381 (69.3%) female and 169 (30.7%) male; mean age 20.46 ± 2.69). Bone mass was assessed through calcaneal QUS) parameter (BUA, dB/MHz). Obesity-related traits including weight, body mass index (BMI), fat mass (FM) and fat-free mass (FFM) were analysed.

RESULTS

The linear regression analysis revealed that the rs7117858 SNP was significantly associated with FFM after adjustments for covariables in the whole sample (P = 0.027, β (95% CI) = 0.053 (0.092, 1.516). In addition, a significant association with QUS measurement adjusted for confounding factors was found in females (P = 0.043, β (95% CI) = 0.104 (0.138. 8.384).

CONCLUSIONS

We demonstrate for the first time that SOX6 influence FFM and QUS trait in a population of young adults, suggesting the implication of this gene in obesity and osteoporosis-related phenotypes during early adulthood.

Identification of Novel Potentially Pleiotropic Variants Associated With Osteoporosis and Obesity Using the cFDR Method

CONTEXT

Genome-wide association studies (GWASs) have been successful in identifying loci associated with osteoporosis and obesity. However, the findings explain only a small fraction of the total genetic variance.

OBJECTIVE

The aim of this study was to identify novel pleiotropic genes important in osteoporosis and obesity.

DESIGN AND SETTING

A pleiotropic conditional false discovery rate method was applied to three independent GWAS summary statistics of femoral neck bone mineral density, body mass index, and waist-to-hip ratio. Next, differential expression analysis was performed for the potentially pleiotropic genes, and weighted genes coexpression network analysis (WGCNA) was conducted to identify functional connections between the suggested pleiotropic genes and known osteoporosis/obesity genes using transcriptomic expression data sets in osteoporosis/obesity-related cells.

RESULTS

We identified seven potentially pleiotropic loci-rs3759579 (MARK3), rs2178950 (TRPS1), rs1473 (PUM1), rs9825174 (XXYLT1), rs2047937 (ZNF423), rs17277372 (DNM3), and rs335170 (PRDM6)-associated with osteoporosis and obesity. Of these loci, the PUM1 gene was differentially expressed in osteoporosis-related cells (B lymphocytes) and obesity-related cells (adipocytes). WGCNA showed that PUM1 positively interacted with several known osteoporosis genes (AKAP11, JAG1, and SPTBN1). ZNF423 was the highly connected intramodular hub gene and interconnected with 21 known osteoporosis-related genes, including JAG1, EN1, and FAM3C.

CONCLUSIONS

Our study identified seven potentially pleiotropic genes associated with osteoporosis and obesity. The findings may provide new insights into a potential genetic determination and codetermination mechanism of osteoporosis and obesity.

Integrated analysis of gene expression and copy number variations in MET proto‑oncogene‑transformed human primary osteoblasts

The aim of the present study was to screen the potential osteosarcoma (OS)‑associated genes and to obtain additional insight into the pathogenesis of OS. Transcriptional profile (ID: GSE28256) and copy number variations (CNV) profile were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) between MET proto‑oncogene‑transformed human primary osteoblast (MET‑HOB) samples and the control samples were identified using the Linear Models for Microarray Data package. Subsequently, CNV areas and CNVs were identified using cut‑off criterion of >30%‑overlap within the cases using detect_cnv.pl in PennCNV. Genes shared in DEGs and CNVs were obtained and discussed. Additionally, the Database for Annotation, Visualization and Integrated Discovery was used to identify significant Gene Ontology (GO) functions and pathways in DEGs with P<0.05. A total of 1,601 DEGs were screened out in MET‑HOBs and compared with control samples, including 784 upregulated genes, such as E2F transcription factor 1 (E2F1) and 2 (E2F2) and 817 downregulated genes, such as retinoblastoma 1 (RB1) and cyclin D1 (CCND1). DEGs were enriched in 344 GO terms, such as extracellular region part and extracellular matrix and 14 pathways, including pathways in cancer and extracellular matrix‑receptor interaction. Additionally, 239 duplications and 439 deletions in 678 genes from 1,313 chromosome regions were detected. A total of 12 genes were identified to be CNV‑driven genes, including cadherin 18, laminin subunit α 1, spectrin β, erythrocytic, ciliary rootlet coiled‑coil, rootletin pseudogene 2, β‑1,4-N-acetyl-galactosaminyltransferase 1, G protein regulated inducer of neurite outgrowth 1, EH domain binding protein 1‑like 1, growth factor independent 1, cathepsin Z, WNK lysine deficient protein kinase 1, glutathione S‑transferase mu 2 and microsomal glutathione S‑transferase 1. Therefore, cell cycle‑associated genes including E2F1, E2F2, RB1 and CCND1, and cell adhesion‑associated genes, such as CDH18 and LAMA1 may be used as diagnosis and/or therapeutic markers for patients with OS.

Hierarchical Association Coefficient Algorithm: New Method for Genome-Wide Association Study

Hierarchical association coefficient algorithm calculates the degree of association between observations and categories into a value named hierarchical association coefficient (HA-coefficient) between 0 for the lower limit and 1 for the upper limit. The HA-coefficient algorithm can be operated with stratified ascending categories based on the average of observations in each category. The upper limit refers to a condition where observations are increasingly ordered into the stratified ascending categories, whereas the lower limit refers to a condition where observations are decreasingly ordered into the stratified ascending categories. An HA-coefficient represents how close an observed categorization is to the upper limit, or how distant an observed categorization is from the lower limit. To demonstrate robustness and reliability, the HA-coefficient algorithm was applied to 3 different simulated data sets with the same pattern in terms of the association between observations and categories. From all simulated data sets, the same result was obtained, indicating that the HA-coefficient algorithm is robust and reliable.

A translational approach from an animal model identifies CD80 as a candidate gene for the study of bone phenotypes in postmenopausal women

This study represented a translational study that first compared gene expression of B cells of BM from ovariectomized and control mice, and then analyzed some of the differentially expressed genes in women. Results showed novel genetic associations with bone phenotypes and points to the CD80 gene as relevant in postmenopausal bone loss.

INTRODUCTION

Osteoporosis is a multifactorial disease with a strong genetic component. However, to date, research into osteoporosis has only been able to explain a small part of its heritability. Moreover, several components of the immune system are involved in the regulation of bone metabolism. Among them, B cells occupy a prominent place.

METHODS

The study consisted of two stages. In the first, gene expression in bone marrow B cells is compared between ovariectomized and SHAM control mice using microarrays. In the second, we studied the association of polymorphisms in some differentially expressed genes (DEG) in a cohort of postmenopausal women.

RESULTS

The present study has found 2791 DEG (false discovery rate (FDR) <5%), of which 1569 genes were upregulated (56.2%) and 1122 genes (43.8%) were downregulated. Among the most altered pathways were inflammation, interleukin signaling, B cell activation, TGF-beta signaling, oxidative stress response, and Wnt-signaling. Sixteen DEG were validated by MALDI-TOF mass spectrometry or qPCR. The translational stage of the study genotyped nine single nucleotide polymorphisms (SNPs) of DEG or related and detected association with bone mineral density (BMD) (nominal P values), while adjusting for confounders, for SNPs in the CD80, CD86, and HDAC5 genes. In the logistic regression analysis adjusted for confounders, in addition to the SNPs in the aforementioned genes, the SNPs in the MMP9 and SOX4 genes were associated with an increased risk of osteoporosis. Finally, two SNPs (in the CD80 and SOX6 genes) were associated with an increased risk of bone fragility fracture (FF). However, after Bonferroni correction for multiple testing, only the association between CD80 with BMD and risk of osteoporosis remained significant.

CONCLUSION

These results show that the use of animal models is an appropriate method for identifying genes associated with human bone phenotypes.

Genome-wide association studies identified multiple genetic loci for body size at four growth stages in Chinese Holstein cattle

The growth and maturity of cattle body size affect not only feed efficiency, but also productivity and longevity. Dissecting the genetic architecture of body size is critical for cattle breeding to improve both efficiency and productivity. The volume and weight of body size are indicated by several measurements. Among them, Heart Girth (HG) and Hip Height (HH) are the most important traits. They are widely used as predictors of body weight (BW). Few association studies have been conducted for HG and HH in cattle focusing on single growth stage. In this study, we extended the Genome-wide association studies to a full spectrum of four growth stages (6-, 12-, 18-, and 24-months after birth) in Chinese Holstein heifers. The whole genomic single nucleotide polymorphisms (SNPs) were obtained from the Illumina BovineSNP50 v2 BeadChip genotyped on 3,325 individuals. Estimated breeding values (EBVs) were derived for both HG and HH at the four different ages and analyzed separately for GWAS by using the Fixed and random model Circuitous Probability Unification (FarmCPU) method. In total, 27 SNPs were identified to be significantly associated with HG and HH at different growth stages. We found 66 candidate genes located nearby the associated SNPs, including nine genes that were known as highly related to development and skeletal and muscular growth. In addition, biological function analysis was performed by Ingenuity Pathway Analysis and an interaction network related to development was obtained, which contained 16 genes out of the 66 candidates. The set of putative genes provided valuable resources and can help elucidate the genomic architecture and mechanisms underlying growth traits in dairy cattle.

Analysis of multiple related phenotypes in genome-wide association studies

Most genome-wide association studies (GWAS) have been conducted by focusing on one phenotype of interest for identifying genetic variants associated with common complex phenotypes. However, despite many successful results from GWAS, only a small number of genetic variants tend to be identified and replicated given a very stringent genome-wide significance criterion, and explain only a small fraction of phenotype heritability. In order to improve power by using more information from data, we propose an alternative multivariate approach, which considers multiple related phenotypes simultaneously. We demonstrate through computer simulation that the multivariate approach can improve power for detecting disease-predisposing genetic variants and pleiotropic variants that have simultaneous effects on multiple related phenotypes. We apply the multivariate approach to a GWA dataset of 8,842 Korean individuals genotyped for 327,872 SNPs, and detect novel genetic variants associated with metabolic syndrome related phenotypes. Considering several related phenotype simultaneously, the multivariate approach provides not only more powerful results than the conventional univariate approach but also clue to identify pleiotropic genes that are important to the pathogenesis of many related complex phenotypes.

Genome-wide association study using family-based cohorts identifies the WLS and CCDC170/ESR1 loci as associated with bone mineral density

Background

Osteoporosis is a common and debilitating bone disease that is characterised by a low bone mineral density (BMD), a highly heritable trait. Genome-wide association studies (GWAS) have proven to be very successful in identifying common genetic variants associated with BMD adjusted for age, gender and weight, however a large portion of the genetic variance for this trait remains unexplained. There is evidence to suggest significant genetic correlation between body size traits and BMD. It has also recently been suggested that unintended bias can be introduced as a result of adjusting a phenotype for a correlated trait. We performed a GWAS meta-analysis in two populations (total n = 6,696) using BMD data adjusted for only age and gender, in an attempt to identify genetic variants associated with BMD including those that may have potential pleiotropic effects on BMD and body size traits.

Results

We observed a single variant, rs2566752, associated with spine BMD at the genome-wide significance level in the meta-analysis (P = 3.36 × 10⁻⁰⁹). Logistic regression analysis also revealed an association between rs2566752 and fracture rate in one of our study cohorts (P = 0.017, n = 5,654). This is an intronic variant located in the wntless Wnt ligand secretion mediator (WLS) gene (1p31.3), a known BMD locus which encodes an integral component of the Wnt ligand secretion pathway. Bioinformatics analyses of variants in moderate LD with rs2566752 produced strong evidence for a regulatory role for the variants rs72670452, rs17130567 and rs1430738. Expression quantitative trait locus (eQTL) analysis suggested that the variants rs12568456 and rs17130567 are associated with expression of the WLS gene in whole blood, cerebellum and temporal cortex brain tissue (P = 0.034–1.19 × 10⁻²³). Gene-wide association testing using the VErsatile Gene-based Association Study 2 (VEGAS2) software revealed associations between the coiled-coil domain containing 170 (CCDC170) gene, located adjacent to the oestrogen receptor 1 (ESR1) gene, and BMD at the spine, femoral neck and total hip sites (P = 1.0 × 10⁻⁰⁶, 2.0 × 10⁻⁰⁶ and 2.0 × 10⁻⁰⁶ respectively).

Conclusions

Genetic variation at the WLS and CCDC170/ESR1 loci were found to be significantly associated with BMD adjusted for only age and gender at the genome-wide level in this meta-analysis.

Endochondral ossification pathway genes and postmenopausal osteoporosis: Association and specific allele related serum bone sialoprotein levels in Han Chinese

Osteoporosis is a systemic skeletal disorder characterized by reduced bone mineral density (BMD) and disrupted bone architecture, predisposing the patient to increased fracture risk. Evidence from early genetic epidemiological studies has indicated a major role for genetics in the development of osteoporosis and the variation in BMD. In this study, we focused on two key genes in the endochondral ossification pathway, IBSP and PTHLH. Over 9,000 postmenopausal Han Chinese women were recruited, and 54 SNPs were genotyped. Two significant SNPs within IBSP, rs1054627 and rs17013181, were associated with BMD and postmenopausal osteoporosis by the two-stage strategy, and rs17013181 was also significantly associated with serum IBSP levels. Moreover, one haplotype (rs12425376-rs10843047-rs42294) covering the 5' end of PTHLH was associated with postmenopausal osteoporosis. Our results provide evidence for the association of these two key endochondral ossification pathway genes with BMD and osteoporosis in postmenopausal Han Chinese women. Combined with previous findings, we provide evidence that a particular SNP in IBSP has an allele-specific effect on mRNA levels, which would, in turn, reflect serum IBSP levels.

Polymorphisms and expression analysis of SOX-6 in relation to porcine growth, carcass, and meat quality traits

The aim of the study was to investigate single nucleotide polymorphisms (SNPs) and expression of SOX-6 to support its candidacy for growth, carcass, and meat quality traits in pigs. The first SNP, rs81358375, was associated with pH 45 min post mortem in loin (pH1L), the thickness of backfat and side fat, and carcass length in Pietrain (Pi) population, and related with backfat thickness and daily gain in Duroc × Pietrain F2 (DuPi) population. The other SNP, rs321666676, was associated with meat colour in Pi population. In DuPi population, the protein, not mRNA, level of SOX-6 in high pH1L pigs was significantly less abundant compared with low pH1L pigs, where microRNAs targeting SOX-6 were also differently regulated. This paper shows that SOX-6 could be a potential candidate gene for porcine growth, carcass, and meat quality traits based on genetic association and gene expression.

Efficient multiple-trait association and estimation of genetic correlation using the matrix-variate linear mixed model

Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM.

Disruption of SOX6 is associated with a rapid-onset dopa-responsive movement disorder, delayed development, and dysmorphic features

BACKGROUND

Sox6 is a transcription factor that is crucial for the differentiation and development of cortical interneurons and dopaminergic neurons of the substantia nigra pars compact. Loss-of-function mutations might thus result in complex paroxysmal diseases such as epilepsy syndromes or movement disorders.

PATIENT

We present a 15-year-old boy with delayed speech development and attention deficit hyperactivity disorder who presented with a rapid-onset generalized dopa-responsive dystonia.

RESULTS

Neurological examination revealed generalized dystonic and frequent athetoid movements of the arms, trunk, and neck. Gait was severely impaired secondary to frequent dystonic postures. Both a resting tremor and action tremors were observed in both hands. Speech was dysarthric but language comprehension was unimpaired. Testing for saccadic dysfunction revealed hypometric horizontal and vertical saccades. Physical examination was otherwise significant for a pectus carinatum and splenomegaly. Laboratory studies, brain magnetic resonance imaging, and electroencephalography were unremarkable. Treatment with levodopa/carbidopa led to a complete and sustained remission of neurological symptoms. Genetic testing revealed a mono-allelic de novo 84-kb deletion on chromosome 11p15.2 encompassing exons 14-16 of the SOX6 gene (chr11: 15944880-16029095, NCBI 37/hg19).

CONCLUSIONS

This is the first report of a dopa-responsive movement disorder associated with SOX6 disruption. SOX6 mutations should be considered in the differential diagnosis of unexplained dopa-responsive dystonia syndromes.

Global developmental delay, progressive relapsing-remitting parkinsonism, and spinal syrinx in a child with SOX6 mutation

SOX6, a member of the SOX gene family, plays a key role in the development of several mammalian tissues and organs, including the central nervous system. Specifically, this gene modulates the differentiation and proliferation of interneurons in the medial ganglionic eminence, as well as oligodendrocytes in the spinal cord. We describe the case of a 4-year-old girl with global developmental delay and a spinal cord syrinx who presented with recurrent episodes of parkinsonian symptoms subsequent to febrile illnesses. The symptoms included gait instability, tremor, and dysarthria, with a progressive relapsing-remitting course over the span of 2 years. The patient was later found to have a large deletion-type mutation in the SOX6 gene. This case is the first report in humans implying a role for SOX6 in basal ganglia function, as well as spinal cord development.

Genome-wide Association Studies for Osteoporosis: A 2013 Update

In the past few years, the bone field has witnessed great advances in genome-wide association studies (GWASs) of osteoporosis, with a number of promising genes identified. In particular, meta-analysis of GWASs, aimed at increasing the power of studies by combining the results from different study populations, have led to the identification of novel associations that would not otherwise have been identified in individual GWASs. Recently, the first whole genome sequencing study for osteoporosis and fractures was published, reporting a novel rare nonsense mutation. This review summarizes the important and representative findings published by December 2013. 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. Potential limitations of GWASs and their meta-analyses are evaluated, with an emphasis on understanding the reasons for inconsistent results between different studies and clarification of misinterpretation of GWAS meta-analysis results. Implications and challenges of GWAS are also discussed, including the need for multi- and inter-disciplinary studies.

A comparison of multivariate genome-wide association methods

Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study we directly compared a number of multivariate GWAS methods using simulated data. We focused on six methods that are implemented in the software packages PLINK, SNPTEST, MultiPhen, BIMBAM, PCHAT and TATES, and also compared them to standard univariate GWAS, analysis of the first principal component of the traits, and meta-analysis of univariate results. We simulated data (N = 1000) for three quantitative traits and one bi-allelic quantitative trait locus (QTL), and varied the number of traits associated with the QTL (explained variance 0.1%), minor allele frequency of the QTL, residual correlation between the traits, and the sign of the correlation induced by the QTL relative to the residual correlation. We compared the power of the methods using empirically fixed significance thresholds (α = 0.05). Our results showed that the multivariate methods implemented in PLINK, SNPTEST, MultiPhen and BIMBAM performed best for the majority of the tested scenarios, with a notable increase in power for scenarios with an opposite sign of genetic and residual correlation. All multivariate analyses resulted in a higher power than univariate analyses, even when only one of the traits was associated with the QTL. Hence, use of multivariate GWAS methods can be recommended, even when genetic correlations between traits are weak.

Regulation of Sox6 by cyclin dependent kinase 5 in brain

Cyclin dependent kinase 5 (Cdk5) is a proline-directed Ser/Thr kinase involved in various biological functions during normal brain development and neurodegeneration. In brain, Cdk5 activity is specific to post-mitotic neurons, due to neuronal specific expression of its activator p35. The biological functions of Cdk5 have been ascribed to its cytoplasmic substrates, however not much is known in nucleus. Here, we show that nuclear transcription factor Sox6 is a direct nuclear target of Cdk5. Sox6 is expressed in Tuj1 positive neurons, suggesting that Sox6 is expressed in differentiating neurons. The expression of Sox6 is high in mitotic nuclei during embryonic day 12 (E12) and gradually decreases during development into adult. On the other hand, Cdk5 expression gradually increases during its development. We show that Sox6 is expressed in mitotic nuclei in embryonic day 12 (E12) and in migrating neurons of E16. Sox6 is phosphorylated in vivo. Sox6 was detected by phospho-Ser/Thr and phospho-Ser/Thr-Pro and MPM-2 (Mitotic protein #2) antibodies in brain. Furthermore, calf intestinal alkaline phosphatase (CIAP) digestion resulted in faster migration of Sox6 band. The GST-Sox6 was phosphorylated by Cdk5/p35. The mass spectrometry analysis revealed that Sox6 is phosphorylated at T119PER motif. We show that Sox6 steady state levels are regulated by Cdk5. Cdk5 knockout mice die in utero and Sox6 protein expression is remarkably high in Cdk5-/- brain, however, there is no change in mRNA expression, suggesting a post-translational regulation of Sox6 by Cdk5. Transfection of primary cortical neurons with WT Cdk5 reduced Sox6 levels, while dominant negative (DN) Cdk5 and p35 increased Sox6 levels. Thus, our results indicate that Cdk5 regulates Sox6 steady state protein level that has an important role in brain development and function.

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.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

Background

Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls.

Methods

In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point.

Results

Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations.

Conclusions

In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests.

Gene expression profiles in human and mouse primary cells provide new insights into the differential actions of vitamin D3 metabolites

1α,25-Dihydroxyvitamin D₃ (1α,25(OH)₂D₃) had earlier been regarded as the only active hormone. The newly identified actions of 25-hydroxyvitamin D₃ (25(OH)D₃) and 24R,25-dihydroxyvitamin D₃ (24R,25(OH)₂D₃) broadened the vitamin D₃ endocrine system, however, the current data are fragmented and a systematic understanding is lacking. Here we performed the first systematic study of global gene expression to clarify their similarities and differences. Three metabolites at physiologically comparable levels were utilized to treat human and mouse fibroblasts prior to DNA microarray analyses. Human primary prostate stromal P29SN cells (hP29SN), which convert 25(OH)D₃ into 1α,25(OH)₂D₃ by 1α-hydroxylase (encoded by the gene CYP27B1), displayed regulation of 164, 171, and 175 genes by treatment with 1α,25(OH)₂D₃, 25(OH)D₃, and 24R,25(OH)₂D₃, respectively. Mouse primary Cyp27b1 knockout fibroblasts (mCyp27b1^−/−), which lack 1α-hydroxylation, displayed regulation of 619, 469, and 66 genes using the same respective treatments. The number of shared genes regulated by two metabolites is much lower in hP29SN than in mCyp27b1^−/−. By using DAVID Functional Annotation Bioinformatics Microarray Analysis tools and Ingenuity Pathways Analysis, we identified the agonistic regulation of calcium homeostasis and bone remodeling between 1α,25(OH)₂D₃ and 25(OH)D₃ and unique non-classical actions of each metabolite in physiological and pathological processes, including cell cycle, keratinocyte differentiation, amyotrophic lateral sclerosis signaling, gene transcription, immunomodulation, epigenetics, cell differentiation, and membrane protein expression. In conclusion, there are three distinct vitamin D₃ hormones with clearly different biological activities. This study presents a new conceptual insight into the vitamin D₃ endocrine system, which may guide the strategic use of vitamin D₃ in disease prevention and treatment.

QTL-based association analyses reveal novel genes influencing pleiotropy of metabolic syndrome (MetS)

OBJECTIVE

Metabolic Syndrome (MetS) is a phenotype cluster predisposing to type 2 diabetes and cardiovascular disease. We conducted a study to elucidate the genetic basis underlying linkage signals for multiple representative traits of MetS that we had previously identified at two significant QTLs on chromosomes 3q27 and 17p12.

DESIGN AND METHODS

We performed QTL-specific genomic and transcriptomic analyses in 1,137 individuals from 85 extended families that contributed to the original linkage. We tested in SOLAR association of MetS phenotypes with QTL-specific haplotype-tagging SNPs as well as transcriptional profiles of peripheral blood mononuclear cells (PBMCs).

RESULTS

SNPs significantly associated with MetS phenotypes under the prior hypothesis of linkage mapped to seven genes at 3q27 and seven at 17p12. Prioritization based on biologic relevance, SNP association, and expression analyses identified two genes: insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) at 3q27 and tumor necrosis factor receptor 13B (TNFRSF13B) at 17p12. Prioritized genes could influence cell-cell adhesion and adipocyte differentiation, insulin/glucose responsiveness, cytokine effectiveness, plasma lipid levels, and lipoprotein densities.

CONCLUSIONS

Using an approach combining genomic, transcriptomic, and bioinformatic data we identified novel candidate genes for MetS.

GWAS of DNA Methylation Variation Within Imprinting Control Regions Suggests Parent-of-Origin Association

Imprinting control regions (ICRs) play a fundamental role in establishing and maintaining the non-random monoallelic expression of certain genes, via common regulatory elements such as non-coding RNAs and differentially methylated regions (DMRs) of DNA. We recently surveyed DNA methylation levels within four ICRs (H19-ICR, IGF2-DMR, KvDMR, and NESPAS-ICR) in whole-blood genomic DNA from 128 monozygotic (MZ) and 128 dizygotic (DZ) human twin pairs. Our analyses revealed high individual variation and intra-domain covariation in methylation levels across CpGs and emphasized the interaction between epigenetic variation and the underlying genetic sequence in a parent-of-origin fashion. Here, we extend our analysis to conduct two genome-wide screenings of single nucleotide polymorphisms (SNPs) underlying either intra-domain covariation or parent-of-origin-dependent association with methylation status at individual CpG sites located within ICRs. Although genome-wide significance was not surpassed due to sample size limitations, the most significantly associated SNPs found through multiple-trait genome-wide association (MQFAM) included the previously described rs10732516, which is located in the vicinity of the H19-ICR. Similarly, we identified an association between rs965808 and methylation status within the NESPAS-ICR. This SNP is positioned within an intronic region of the overlapping genes GNAS and GNAS-AS1, which are imprinted genes regulated by the NESPAS-ICR. Sixteen other SNPs located in regions apart from the analyzed regions displayed suggestive association with intra-domain methylation. Additionally, we identified 13 SNPs displaying parent-of-origin association with individual methylation sites through family-based association testing. In this exploratory study, we show the value and feasibility of using alternative GWAS approaches in the study of the interaction between epigenetic state and genetic sequence within imprinting regulatory domains. Despite the relatively small sample size, we identified a number of SNPs displaying suggestive association either in a domain-wide or in a parent-of-origin fashion. Nevertheless, these associations will require future experimental validation or replication in larger and independent samples.

Genome-wide approaches for identifying genetic risk factors for osteoporosis

Osteoporosis, the most common type of bone disease worldwide, is clinically characterized by low bone mineral density (BMD) and increased susceptibility to fracture. Multiple genetic and environmental factors and gene-environment interactions have been implicated in its pathogenesis. Osteoporosis has strong genetic determination, with the heritability of BMD estimated to be as high as 60%. More than 80 genes or genetic variants have been implicated in risk of osteoporosis by hypothesis-free genome-wide studies. However, these genes or genetic variants can only explain a small portion of BMD variation, suggesting that many other genes or genetic variants underlying osteoporosis risk await discovery. Here, we review recent progress in genome-wide studies of osteoporosis and discuss their implications for medicine and the major challenges in the field.

Association of single nucleotide polymorphism Rs2236518 in PRDM16 gene with BMI in Chinese males

AIM

PRD1-BF-1-RIZ1 homologous domain containing protein-16 (PRDM16) is a cell-autonomous transcriptional component that stimulates the development of brown fat cells. The aim of this study was to investigate the contribution of genetic variants of PRDM16 to obesity-related phenotype variations in Chinese.

METHODS

A total of 3204 subjects (consisting of 400 male-offspring nuclear families, 401 female-offspring nuclear families, and 729 unrelated older males) were recruited. Ten tag single nucleotide polymorphisms (SNPs) within the PRDM16 gene were genotyped using multiplex quantitative real-time PCR by Taqman assay. Body compositions were measured by dual-energy X-ray absorptiometry (DXA). The associations of the SNPs with the obesity-related phenotypes were analyzed using the quantitative transmission disequilibrium test (QTDT), GLM-ANOVA and PLINK statistical methods.

RESULTS

Rs2236518 was the only SNP that was associated with BMI in young (aged 20-40 years) males (P=0.011) using QTDT, and in the older men (aged 50-80 years) (P=0.003) using GLM-ANOVA. No significant associations were detected in the females. Nor was a relationship found between any haplotype and obesity-related phenotypes. When PLINK was used, no significant relationship was detected between 10 SNPs and obesity-related phenotypes in any of the studied cohorts.

CONCLUSION

Rs2236518 is associated with BMI in the young males (using QTDT), and the older males (using GLM-ANOVA).However, the result is not confirmed using PLINK. The discrepancy needs to be further addressed.

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

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

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.

Association between the SPRY1 gene polymorphism and obesity-related traits and osteoporosis in Korean women

BACKGROUND

Emerging evidence has revealed a close relationship between obesity and osteoporosis. It was reported recently that conditional knockout of the Spry1 gene in mice adipocytes causes an increase in body fat and a decrease in bone mass, and that these phenotypes are rescued by Spry1 overexpression in adipose tissue. In this study, we investigated whether genetic variation in the human SPRY1 gene is associated with obesity-related phenotypes and/or osteoporosis in humans.

METHODS

We performed a candidate gene association analysis between the four single nucleotide polymorphisms (SNPs) and 14 imputed SNPs in the SPRY1 gene and obesity-related traits and osteoporosis in a Korean women cohort (3013 subjects).

RESULTS

All four SPRY1 gene SNPs were significantly associated with either obesity-related traits or osteoporosis. The TGCC haplotype in the SRPY1 gene showed simultaneous association with an increased risk for obesity-related traits, percentage body fat (p=0.0087) and percentage abdominal fat (p=0.047), and osteoporosis (odds ratio=1.50; p=0.025) in the recessive genetic model.

CONCLUSIONS

Our results support a previous finding in conditional Spry1 gene knockout mice and suggest that the SPRY1 gene is an important genetic factor for determining the risk of both obesity and osteoporosis in humans.

Bone mineral density-associated polymorphisms are associated with obesity-related traits in Korean adults in a sex-dependent manner

Obesity and osteoporosis share common physiological factors, including the presence of atherosclerosis, a risk factor for cardiometabolic disease, as well as a common progenitor that differentiates into both adipocytes and osteoblasts. Among the 23 polymorphisms associated with bone mineral density (BMD) in recent genome-wide association studies (GWASs), an Osterix polymorphism has been identified and associated with childhood obesity in girls. Therefore, we focused on elucidating polymorphisms associated with adulthood obesity in a sex-dependent manner among the previously published BMD-associated polymorphisms from GWASs. We performed 2 screenings of 18 BMD-associated polymorphisms for obesity-related traits in 2,362 adults aged >20 years. We excluded 13 polymorphisms showing deviations from Hardy–Weinberg equilibrium or no association with obesity-related traits (body mass index, waist circumference (WC), and waist-to-hip ratio). Among 5 selected polymorphisms (rs9594738 of RANKL, rs17066364 of NUFIP1, rs7227401 of OSBPL1A, and rs1856057 and rs2982573 of ESR1) analyzed, 2 polymorphisms (rs9594738 and rs17066364) were associated with obesity-related traits. We found sex-dependent associations such that the 4 polymorphisms (excluding rs9594738 of RANKL) were associated with abdominal traits such as WC and waist-to-hip ratio only in men. In addition, when the combined genetic risk score (GRS) for WC increase was calculated with 4 SNPs (rs9594738, rs17066364, rs7227401, and rs1856057) exhibiting similar trends for both sexes, the magnitude of the GRS effect for the WC increase was larger in men than in women (effect size = 0.856 cm, P = 0.0000452 for men; effect size = 0.598 cm, P = 0.00228 for women). In summary, we found 4 polymorphisms, previously related to osteoporosis, to be associated to obesity-related traits in a sex-dependent manner in Korean adults, particularly in men.

Bivariate genome-wide association study suggests fatty acid desaturase genes and cadherin DCHS2 for variation of both compressive strength index and appendicular lean mass in males

Compressive strength index (CSI) is a newly established index for predicting hip fracture, the most serious consequence of osteoporosis. Appendicular lean mass (ALM), which influences skeletal strength of the lower limbs, is another trait associated with the risk of hip fracture. In this study, we performed a bivariate genome-wide association study (GWAS) to identify new candidate genes responsible for both CSI and ALM. In our discovery sample of 1627 unrelated Chinese subjects (802 males and 825 females), we scanned 909,509 SNPs using the Affymetrix Human Genome SNP 6.0 genotyping array. We successfully replicated our results in a sample of 2286 Caucasian subjects (558 males and 1728 females). The results indicated that five SNPs (rs174583, rs174577, rs174549, rs174548, rs7672337) in the FADS1, FADS2, and DCHS2 genes had significant bivariate associations with CSI and ALM in male subjects for both the GWAS discovery (with P<8.42×10(-6)) and the Caucasian sample (with P<0.07). We performed further replication analysis in a 2nd Caucasian sample with 501 Caucasian male subjects, using Affymetrix 500k arrays, and found that two of the above SNPs (rs174548 and rs174549, P=0.07) had bivariate associations with both CSI and ALM in males; the other 3 SNPs were not typed with the 500k array. The above findings suggest that the 3 genes, FADS1, FADS2, and DCHS2, containing these SNPs might play dual roles influencing both CSI and ALM in males. Our findings provide new insights into our understanding of the genetic basis of bone metabolism and the pathogenesis of osteoporosis.

Polymorphisms in the inflammatory genes CIITA, CLEC16A and IFNG influence BMD, bone loss and fracture in elderly women

Osteoclast activity and the fine balance between bone formation and resorption is affected by inflammatory factors such as cytokines and T lymphocyte activity, mediated by major histocompatibility complex (MHC) molecules, in turn regulated by the MHC class II transactivator (MHC2TA). We investigated the effect of functional polymorphisms in the MHC2TA gene (CIITA), and two additional genes; C-type lectin domain 16A (CLEC16A), in linkage disequilibrium with CIITA and Interferon-γ (IFNG), an inducer of CIITA; on bone density, bone resorption markers, bone loss and fracture risk in 75 year-old women followed for up to 10 years (OPRA n = 1003) and in young adult women (PEAK-25 n = 999). CIITA was associated with BMD at age 75 (lumbar spine p = 0.011; femoral neck (FN) p = 0.049) and age 80 (total body p = 0.015; total hip p = 0.042; FN p = 0.028). Carriers of the CIITA rs3087456(G) allele had 1.8–3.4% higher BMD and displayed increased rate of bone loss between age 75 and 80 (FN p = 0.013; total hip p = 0.030; total body p = 3.8E⁻⁵). Despite increasing bone loss, the rs3087456(G) allele was protective against incident fracture overall (p = 0.002), osteoporotic fracture and hip fracture. Carriers of CLEC16A and IFNG variant alleles had lower BMD (p<0.05) and ultrasound parameters and a lower risk of incident fracture (CLEC16A, p = 0.011). In 25-year old women, none of the genes were associated with BMD. In conclusion, variation in inflammatory genes CIITA, CLEC-16A and INFG appear to contribute to bone phenotypes in elderly women and suggest a role for low-grade inflammation and MHC class II expression for osteoporosis pathogenesis.

The genetic pleiotropy of musculoskeletal aging

Musculoskeletal aging is detrimental to multiple bodily functions and starts early, probably in the fourth decade of an individual's life. Sarcopenia is a health problem that is expected to only increase as a greater portion of the population lives longer; prevalence of the related musculoskeletal diseases is similarly expected to increase. Unraveling the biological and biomechanical associations and molecular mechanisms underlying these diseases represents a formidable challenge. There are two major problems making disentangling the biological complexity of musculoskeletal aging difficult: (a) it is a systemic, rather than "compartmental," problem, which should be approached accordingly, and (b) the aging per se is neither well defined nor reliably measurable. A unique challenge of studying any age-related condition is a need of distinguishing between the "norm" and "pathology," which are interwoven throughout the aging organism. We argue that detecting genes with pleiotropic functions in musculoskeletal aging is needed to provide insights into the potential biological mechanisms underlying inter-individual differences insusceptibility to the musculoskeletal diseases. However, exploring pleiotropic relationships among the system's components is challenging both methodologically and conceptually. We aimed to focus on genetic aspects of the cross-talk between muscle and its "neighboring" tissues and organs (tendon, bone, and cartilage), and to explore the role of genetics to find the new molecular links between skeletal muscle and other parts of the "musculoskeleton." Identification of significant genetic variants underlying the musculoskeletal system's aging is now possible more than ever due to the currently available advanced genomic technologies. In summary, a "holistic" genetic approach is needed to study the systems's normal functioning and the disease predisposition in order to improve musculoskeletal health.