Copy number variation in CNP267 region may be associated with hip bone size

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.

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.

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.

Genome-wide association study identified CNP12587 region underlying height variation in Chinese females

Introduction

Human height is a highly heritable trait considered as an important factor for health. There has been limited success in identifying the genetic factors underlying height variation. We aim to identify sequence variants associated with adult height by a genome-wide association study of copy number variants (CNVs) in Chinese.

Methods

Genome-wide CNV association analyses were conducted in 1,625 unrelated Chinese adults and sex specific subgroup for height variation, respectively. Height was measured with a stadiometer. Affymetrix SNP6.0 genotyping platform was used to identify copy number polymorphisms (CNPs). We constructed a genomic map containing 1,009 CNPs in Chinese individuals and performed a genome-wide association study of CNPs with height.

Results

We detected 10 significant association signals for height (p<0.05) in the whole population, 9 and 11 association signals for Chinese female and male population, respectively. A copy number polymorphism (CNP12587, chr18:54081842-54086942, p = 2.41×10⁻⁴) was found to be significantly associated with height variation in Chinese females even after strict Bonferroni correction (p = 0.048). Confirmatory real time PCR experiments lent further support for CNV validation. Compared to female subjects with two copies of the CNP, carriers of three copies had an average of 8.1% decrease in height. An important candidate gene, ubiquitin-protein ligase NEDD4-like (NEDD4L), was detected at this region, which plays important roles in bone metabolism by binding to bone formation regulators.

Conclusions

Our findings suggest the important genetic variants underlying height variation in Chinese.

Genome-wide association study of copy number variants suggests LTBP1 and FGD4 are important for alcohol drinking

Alcohol dependence (AD) is a complex disorder characterized by psychiatric and physiological dependence on alcohol. AD is reflected by regular alcohol drinking, which is highly inheritable. In this study, to identify susceptibility genes associated with alcohol drinking, we performed a genome-wide association study of copy number variants (CNVs) in 2,286 Caucasian subjects with Affymetrix SNP6.0 genotyping array. We replicated our findings in 1,627 Chinese subjects with the same genotyping array. We identified two CNVs, CNV207 (combined p-value 1.91E-03) and CNV1836 (combined p-value 3.05E-03) that were associated with alcohol drinking. CNV207 and CNV1836 are located at the downstream of genes LTBP1 (870 kb) and FGD4 (400 kb), respectively. LTBP1, by interacting TGFB1, may down-regulate enzymes directly participating in alcohol metabolism. FGD4 plays a role in clustering and trafficking GABA(A) receptor and subsequently influence alcohol drinking through activating CDC42. Our results provide suggestive evidence that the newly identified CNV regions and relevant genes may contribute to the genetic mechanism of alcohol dependence.