Bone Mineral Density (BMD) is major index for diagnosing osteoporosis. PhosSNPs are non-synonymous SNPs that affect protein phosphorylation. The relevance and significance of phosSNPs to BMD and osteoporosis is unknown. This study aims to identify and characterize phosSNPs significant for BMD in humans. We conducted a pilot genome-wide phosSNP association study for BMD in three independent population samples, involving ~5,000 unrelated individuals. We identified and replicated three phosSNPs associated with both spine BMD and hip BMD in Caucasians. Association with hip BMD for one of these phosSNPs, i.e., rs6265 (major/minor allele: G/A) in BDNF gene, was also suggested in Chinese. Consistently in both ethnicities, individuals carrying AA genotype have significant lower hip BMD than carriers of GA and GG genotypes. Through in vitro molecular and cellular studies, we found that compared to osteoblastic cells transfected with wild-type BDNF-Val66 (encoded with allele G at rs6265), transfection of variant BDNF-Met66 (encoded with allele A at rs6265) significantly decreased BDNF protein phosphorylation (at amino acid residue T62), expression of osteoblastic genes (OPN, BMP2, and ALP), and osteoblastic activity. The findings are consistent with and explain our prior observations in general human populations. We conclude that phosSNP rs6265, via regulating BDNF protein phosphorylation and osteoblast differentiation, influence hip BMD in humans. This study represents our first endeavor to dissect the functions of phosSNPs in bone, which might stimulate extended large-scale studies on bone or similar studies on other human complex traits and diseases.
BMD; SNP; protein phosphorylation; BDNF; osteoblast
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.
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.
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.
The evidence suggests that ANKRD7 and CYTL1 genes may play an important role in the variance in AD risk.
alcohol dependence; ANKRD7; CYTL1; genome-wide association study
Osteoporosis is characterized by low bone mineral density (BMD), a highly heritable trait that is determined, in part, by the actions and interactions of multiple genes. While an increasing number of genes have been identified to have independent effects on BMD, few studies have been performed to identify genes that interact with one another to affect BMD. In this study, we performed gene-gene interaction analyses in selected candidate genes in individuals with extremely high vs. low hip BMD (20% tails of the distributions), in two independent US Caucasian samples. The first sample contained 916 unrelated subjects with extreme hip BMD Z-scores selected from a population composed of 2,286 subjects. The second sample consisted of 400 unrelated subjects with extreme hip BMD Z-scores selected from a population composed of 1,000 subjects. Combining results from these two samples, we found one interacting gene pair (RBMS3 vs. ZNF516) which, even after Bonferroni correction for multiple testing, showed consistently significant effects on hip BMD. RMBS3 harbored two SNPs, rs6549904 and rs7640046, both of which had significant interactions with a SNP, rs4891159, located on ZNF516 (P values: 7.04×10−11 and 1.03×10−10). We further validated these results in two additional samples of Caucasian and African descent. The gene pair, RBMS3 vs. ZNF516, was successfully replicated in the Caucasian sample (P values: 8.07×10−3 and 2.91×10−3). For the African sample, a significant interaction was also detected (P values: 0.031 and 0.043), but the direction of the effect was opposite to that observed in the three Caucasian samples. By providing evidence for genetic interactions underlying BMD, this study further delineated the genetic architecture of osteoporosis.
interaction; association; BMD; osteoporosis
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.
Genome-wide association study; Osteoporosis
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 2,286 unrelated Caucasians using Affymetrix 6.0 SNP arrays. Areal BS (cm2) 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 = 1,000 and 2,503) and one Chinese population (N = 1,627).
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 were replicated in one Caucasian and one Chinese populations. Meta-analyses (N = 7,416) 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.
Spine bone size; GWAS; UQCC
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 1728 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 were 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.
Bivariate GWAS; Bone size; Lean mass; GLYAT
It is usually observed that among genes there exist strong statistical interactions associated with diseases of public health importance. Gene interactions can potentially contribute to the improvement of disease classification accuracy. Especially when gene expression differs across different classes are not great enough, it is more important to take use of gene interactions for disease classification analyses. However, most gene selection algorithms in classification analyses merely focus on genes whose expression levels show differences across classes, and ignore the discriminatory information from gene interactions. In this study, we develop a two-stage algorithm that can take gene interaction into account during a gene selection procedure. Its biggest advantage is that it can take advantage of discriminatory information from gene interactions as well as gene expression differences, by using “Bayes error” as a gene selection criterion. Using simulated and real microarray data sets, we demonstrate the ability of gene interactions for classification accuracy improvement, and present that the proposed algorithm can yield small informative sets of genes while leading to highly accurate classification results. Thus our study may give a novel sight for future gene selection algorithms of human diseases discrimination.
It has been a research focus to uncover the genetic determination of complex diseases caused by rare variants. As the vast majority of genomic variants represent background variation, highlighting potentially causal mutations through weighting scheme is critical to the success of rare variants aimed association studies. In this study, we propose a novel Bayesian marker selection approach to perform weighting-based association test. In this approach, individual association signal and its direction are used to weight variants. In addition, the predicted biological function of variants is taken as prior information to direct the selection of likely causal variants. Simulation studies show that the proposed method has improved power over several existing methods in certain conditions. Analyses of two empirical datasets demonstrate its applicability.
weighting; Bayesian marker selection; rare variants; association
Osteoporosis (OP) is characterized by low bone mineral density (BMD) and has strong genetic determination. However, specific genetic variants influencing BMD and contributing to pathogenesis of osteoporosis are largely uncharacterized. Current genetic studies in bone filed, which aimed at identification of OP risk genes, are mostly focused on DNA, RNA, or protein level individually, lacking integrative evidences from the three levels of genetic information flow to confidently ascertain the significance of genes for osteoporosis. Our previous proteomics study discovered that superoxide dismutase 2 (SOD2) in circulating monocytes (CMCs, i.e., potential osteoclast precursors) was significantly up-regulated at protein level in vivo in Chinese with low vs. high hip BMD. Herein, at mRNA level, we found that SOD2 gene expression was also up-regulated in CMC (p < 0.05) in Chinese with low vs. high hip BMD. At DNA level, in 1,627 unrelated Chinese subjects, we identified eight SNPs at SOD2 gene locus that were suggestively associated with hip BMD (peak signal at rs11968525, p = 0.048). Among the eight SNPs, three SNPs (rs7754103, rs7754295, and rs2053949) were associated with SOD2 mRNA expression level (p < 0.05), suggesting that they are expression quantitative trait locus (eQTL) regulating SOD2 gene expression. In conclusion, the present integrative evidences from DNA, RNA, and protein levels supported SOD2 as a susceptibility gene for osteoporosis.
Osteoporosis; SOD2; eQTL; BMD
MicroRNAs (miRNAs) regulate posttranscriptional gene expression usually by binding to 3'-untranslated regions (3'-UTRs) of target message RNAs (mRNAs). Hence genetic polymorphisms on 3'-UTRs of mRNAs may alter binding affinity between miRNAs target 3'-UTRs, thereby altering translational regulation of target mRNAs and/or degradation of mRNAs, leading to differential protein expression of target genes. Based on a database that catalogues predicted polymorphisms in miRNA target sites (poly-miRTSs), we selected 568 polymorphisms within 3'-UTRs of target mRNAs and performed association analyses between these selected poly-miRTSs and osteoporosis in 997 white subjects who were genotyped by Affymetrix Human Mapping 500K arrays. Initial discovery (in the 997 subjects) and replication (in 1728 white subjects) association analyses identified three poly-miRTSs (rs6854081, rs1048201, and rs7683093) in the fibroblast growth factor 2 (FGF2) gene that were significantly associated with femoral neck bone mineral density (BMD). These three poly-miRTSs serve as potential binding sites for 9 miRNAs (eg, miR-146a and miR-146b). Further gene expression analyses demonstrated that the FGF2 gene was differentially expressed between subjects with high versus low BMD in three independent sample sets. Our initial and replicate association studies and subsequent gene expression analyses support the conclusion that these three polymorphisms of the FGF2 gene may contribute to susceptibility to osteoporosis, most likely through their effects on altered binding affinity for specific miRNAs. © 2011 American Society for Bone and Mineral Research.
MICRORNA; OSTEOPOROSIS; ASSOCIATION; POLYMORPHISM
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, qfdr = 0.043, pfwer = 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. © 2010 American Society for Bone and Mineral Research.
osteoporosis; bone mineral density; genome-wide association; regulation of autophagy; whites
Bone mineral density (BMD) measured at the femoral neck (FN) is the most important risk phenotype for osteoporosis and has been used as a reference standard for describing osteoporosis. The specific genes influencing FN BMD remain largely unknown. To identify such genes, we first performed a genome-wide association (GWA) analysis for FN BMD in a discovery sample consisting of 983 unrelated white subjects. We then tested the top significant single-nucleotide polymorphisms (SNPs; 175 SNPs with p < 5 × 10−4) for replication in a family-based sample of 2557 white subjects. Combing results from these two samples, we found that two genes, parathyroid hormone (PTH) and interleukin 21 receptor (IL21R), achieved consistent association results in both the discovery and replication samples. The PTH gene SNPs, rs9630182, rs2036417, and rs7125774, achieved p values of 1.10 × 10−4, 3.24 × 10−4, and 3.06 × 10−4, respectively, in the discovery sample; p values of 6.50 × 10−4, 5.08 × 10−3, and 5.68 × 10−3, respectively, in the replication sample; and combined p values of 3.98 × 10−7, 9.52 × 10−6, and 1.05 × 10−5, respectively, in the total sample. The IL21R gene SNPs, rs8057551, rs8061992, and rs7199138, achieved p values of 1.51 × 10−4, 1.53 × 10−4, and 3.88 × 10−4, respectively, in the discovery sample; p values of 2.36 × 10−3, 6.74 × 10−3, and 6.41 × 10−3, respectively, in the replication sample; and combined p values of 2.31 × 10−6, 8.62 × 10−6, and 1.41 × 10−5, respectively, in the total sample. The effect size of each SNP was approximately 0.11 SD estimated in the discovery sample. PTH and IL21R both have potential biologic functions important to bone metabolism. Overall, our findings provide some new clues to the understanding of the genetic architecture of osteoporosis. © 2010 American Society for Bone and Mineral Research.
genome-wide association; BMD; PTH; IL21R; osteoporosis
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 × 10−7), an index of bone structural instability, and with femoral cortical thickness (CT, P = 1.9 × 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 × 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 × 10−3 for BR and P = 1.4 × 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 × 10−3) was found. Our observations suggest that RTP3 may be a novel candidate gene for femoral neck bone geometry. © 2010 American Society for Bone and Mineral Research
genome-wide association; femoral neck bone geometry; bone fracture; RTP3
Osteoporosis is characterized mainly by low bone mineral density (BMD). Many cytokines and chemokines have been related with bone metabolism. Monocytes in the immune system are important sources of cytokines and chemokines for bone metabolism. However, no study has investigated in vivo expression of a large number of various factors simultaneously in human monocytes underlying osteoporosis. This study explored the in vivo expression pattern of general cytokines, chemokines, and their receptor genes in human monocytes and validated the significant genes by qRT-PCR and genetic association analyses. Expression profilings were performed in monocyte samples from 26 Chinese and 20 Caucasian premenopausal women with discordant BMD. Genome-wide association analysis with BMD variation was conducted in 1000 unrelated Caucasians. We selected 168 cytokines, chemokines, osteoclast-related factors, and their receptor genes for analyses. Significantly, the signal transducer and activator of transcription 1 (STAT1) gene was upregulated in the low versus the high BMD groups in both Chinese and Caucasians. We also revealed a significant association of the STAT1 gene with BMD variation in the 1000 Caucasians. Thus we conclude that the STAT1 gene is important in human circulating monocytes in the etiology of osteoporosis. © 2010 American Society for Bone and Mineral Research.
STAT1; bmd; monocytes; osteoporosis; microarray; SNP
Femoral neck (FN) bone geometry is an important predictor of bone strength with high heritability. Previous studies have revealed certain candidate genes for FN bone geometry. However, the majority of the underlying genetic factors remain to be discovered. In this study, pathway-based genome-wide association analysis was performed to explore the joint effects of genes within biological pathways on FN bone geometry variations in a cohort of 1,000 unrelated U.S. whites. Nominal significant associations (nominal p value < 0.05) were observed between 76 pathways and a key FN bone geometry variable - section modulus (Z), biomechanically indicative of bone strength subject to bending. Among them, EphrinA-EphR pathway was most significantly associated with FN Z even after multiple testing adjustments (pFWER value = 0.035). The association of EphrinA-EphR pathway with FN Z was also observed in an independent sample from Framingham Osteoporosis Study. Overall, these results suggest the significant genetic contribution of EphrinA-EphR pathway to femoral neck bone geometry.
Bone strength; Femoral neck bone geometry; Genetic factor; Pathway-based genome-wide association analysis; EphrinA-EphR pathway
Recent genome-wide association studies have identified a novel polymorphism rs1042725 in HMGA2 gene for human adult height, a highly heritable complex trait. Replications in independent populations are needed to evaluate a positive finding and determine its generality. Thus, we performed a replication study to examine the associations between polymorphisms in HMGA2 and adult height in two US Caucasian populations (an unrelated sample of 998 subjects and a family-based sample of 8,385 subjects) and a Chinese population (1,638 unrelated Han subjects). We confirmed the association between rs1042725 in HMGA2 and adult height both in the unrelated and family-based Caucasian populations (overall P = 4.25×10−9). Another two SNPs (rs7968902 and rs7968682), which were in high linkage disequilibrium with rs1042725, also achieved the significance level in both Caucasian populations (overall P = 6.34×10−7, and 2.72×10−9, respectively). Our results provide a strong support to the initial finding. Moreover, SNP rs1042725 was firstly found to be associated with adult height (P = 0.008) in the Chinese population, and the effect is in the same direction as in the Caucasian populations, suggesting that it is a common variant across different populations. Our study further highlights the importance of the HMGA2 gene involved in normal growth.
replication; adult height; HMGA2; association
Recent genome-wide association (GWA) studies have identified a number of novel genes/variants predisposing to obesity. However, most GWA studies have focused on individual single-nucleotide polymorphism (SNPs)/genes with a strong statistical association with a phenotypic trait without considering potential biological interplay of the tested genes. In this study, we performed biological pathway-based GWA analysis for BMI and body fat mass. We used individual level genotype data generated from 1,000 unrelated US whites that were genotyped for ~500,000 SNPs. Statistical analysis of pathways was performed using a modification of the Gene Set Enrichment Algorithm. A total of 963 pathways extracted from the BioCarta, Kyoto Encyclopedia of Genes and Genomes (KEGG), Ambion GeneAssist, and Gene Ontology (GO) databases were analyzed. Among all of the pathways analyzed, the vasoactive intestinal peptide (VIP) pathway was most strongly associated with fat mass (nominal P = 0.0009) and was the third most strongly associated pathway with BMI (nominal P = 0.0006). After multiple testing correction, the VIP pathway achieved false-discovery rate (FDR) q values of 0.042 and 0.120 for fat mass and BMI, respectively. Our study is the first to demonstrate that the VIP pathway may play an important role in development of obesity. The study also highlights the importance of pathway-based GWA analysis in identification of additional genes/variants for complex human diseases.
Traditional transmission disequilibrium test (TDT) based methods for genetic association analyses are robust to population stratification at the cost of a substantial loss of power. We here describe a novel method for family-based association studies that corrects for population stratification with the use of an extension of principal component analysis (PCA). Specifically, we adopt PCA on unrelated parents in each family. We then infer principal components for children from those for their parents through a TDT-like strategy. Two test statistics within variance-components model are proposed for association tests. Simulation results show that the proposed tests have correct type I error rates regardless of population stratification, and have greatly improved power over two popular TDT-based methods: QTDT and FBAT. The application to the Genetic Analysis Workshop 16 (GAW16) data sets attests to the feasibility of the proposed method.
Family Based Association Tests (FBATs); Transmission Disequilibrium Test (TDT); Principal Component Analysis (PCA); Variance-Components
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.
Cryptic relatedness; Population-based association studies; Likelihood ratio tests
Bone mineral density (BMD) and femoral neck cross-sectional geometric parameters (FNCSGPs) are under strong genetic control. DNA copy number variation (CNV) is an important source of genetic diversity for human diseases. This study aims to identify CNVs associated with BMD and FNCSGPs.
Genome-wide CNV association analyses were conducted in 1,000 unrelated Caucasian subjects for BMD at the spine, hip, femoral neck, and for three FNCSGPs - cortical thickness (CT), cross section area (CSA), and buckling ratio (BR). BMD was measured by dual energy X-ray absorptiometry (DEXA). CT, CSA, and BR were estimated using DEXA measurements. Affymetrix 500K arrays and copy number analysis tool was used to identify CNVs.
A CNV in VPS13B gene was significantly associated with spine, hip and FN BMDs, and CT, CSA, and BR (p < 0.05). Compared to subjects with 2 copies of the CNV, carriers of one copy had an average of 14.6%, 12.4%, and 13.6% higher spine, hip, and FN BMD, 20.0% thicker CT, 10.6% larger CSA, and 12.4% lower BR. Thus a decrease of the CNV consistently produced stronger bone, thereby reducing osteoporotic fracture risk.
VPS13B gene, via affecting BMD and FNCSGPs, is a novel osteoporosis risk gene
copy number variation; bone mineral density; bone geometry; osteoporosis
Genome-wide association (GWA) study is becoming a powerful tool in deciphering genetic basis of complex human diseases/traits. Currently, the univariate analysis is the most commonly used method to identify genes associated with a certain disease/phenotype under study. A major limitation with the univariate analysis is that it may not make use of the information of multiple correlated phenotypes, which are usually measured and collected in practical studies. The multivariate analysis has proven to be a powerful approach in linkage studies of complex diseases/traits, but it has received little attention in GWA. In this study, we aim to develop a bivariate analytical method for GWAS, which can be used for a complex situation that a continuous trait and a binary trait measured are under study. Based on the modified extended generalized estimating equation (EGEE) method we proposed herein, we assessed the performance of our bivariate analyses through extensive simulations as well as real data analyses. In the study, to develop an EGEE approach for bivariate genetic analyses, we combined two different generalized linear models corresponding to phenotypic variables using a Seemingly Unrelated Regression (SUR) model. The simulation results demonstrated that our EGEE-based bivariate analytical method outperforms univariate analyses in increasing statistical power under a variety of simulation scenarios. Notably, EGEE-based bivariate analyses have consistent advantages over univariate analyses whether or not there exits a phenotypic correlation between the two traits. Our study has practical importance, as one can always use multivariate analyses as a screening tool when multiple phenotypes are available, without extra costs of statistical power and false positive rate. Analyses on empirical GWA data further affirm the advantages of our bivariate analytical method.
Cigarette smoking is the leading preventable cause of death in the US. Although smoking behavior has a significant genetic determination, the specific genes and associated mechanisms underlying smoking behavior are largely unknown. Here, we performed a genome-wide association study on smoking behavior in 840 Caucasians, including 417 males and 423 females, in which we examined ∼380,000 SNPs. We found that a cluster of nine SNPs upstream from the IL15 gene were associated with smoking status in males, with the most significant SNP, rs4956302, achieving a p value (8.80×10−8) of genome-wide significance. Another SNP, rs17354547, that is highly conserved across multiple species, achieved a p value of 5.65×10−5. These two SNPs, together with two additional SNPs (rs1402812 and rs4956396) were selected from the above nine SNPs for replication in an African-American sample containing 1,251 subjects, including 412 males and 839 females. The SNP rs17354547 was successfully replicated in the male subgroup of the replication sample; it was associated with smoking quantity (SQ), the Heaviness of Smoking Index (HSI) and the Fagerstrom Test for Nicotine Dependence (FTND), with p values of 0.031, 0.0046 and 0.019, respectively. In addition, a haplotype formed by rs17354547, rs1402812 and rs4956396 was also associated with SQ, HSI and FTND, achieving p values of 0.039, 0.0093 and 0.0093, respectively. To further confirm our findings, we performed an in silico replication study of the nine SNPs in a Framingham Heart Study sample containing 7,623 Caucasians from 1,731 families, among which, 3,491 subjects are males and 4,132 are females. Again, male-specific association with smoking status was observed, for which seven of the nine SNPs achieved significant p values (p<0.05) and two achieved marginally significant p values (p<0.10) in males. Several of the nine SNPs, including the highly conserved one across species, rs17354547, are located at potential transcription factor binding sites, suggesting transcription regulation as a possible function for these SNPs. Through this function, the SNPs may modulate gene expression of IL15, a key cytokine regulating immune function. As the immune system has long been recognized to influence drug addiction behavior, our association findings suggest a novel mechanism for smoking addiction involving immune modulation via the IL15 pathway.
smoking; nicotine addiction; IL15; genomewide association; genetics
Osteoporosis (OP) is a major public health problem, mainly characterized by low bone mineral density (BMD). Circulating monocytes (CMCs) may serve as progenitors of osteoclasts and produce a wide variety of factors important to bone metabolism. However, the specific action mechanism of CMCs in the pathogenesis of OP is far from clear. We performed a comparative protein expression profiling study of CMCs in Chinese premenopausal females with extremely discordant BMD, identified a total of 38 differentially expressed proteins, and confirmed with Western blotting five proteins: ras suppressor protein1 (RSU1), gelsolin (GSN), manganese-containing superoxide dismutase (SOD2), glutathione peroxidase 1(GPX1), and prolyl 4-hydroxylase β subunit (P4HB). These proteins might affect CMCs’ trans-endothelium, differentiation, and/or downstream osteoclast functions, thus contribute to differential osteoclastogenesis and finally lead to BMD variation. The findings promote our understanding of the role of CMCs in BMD determination, and provide an insight into the pathogenesis of human OP.
Bone mineral density; Circulating monocyte; Osteoclastogenesis; Protein
Genetic association analyses with haplotypes may be more powerful than analyses with single markers, under certain conditions. Furthermore, simultaneously considering multiple correlated traits may make use of additional information that would not be considered when analyzing individual traits. In this study, we propose a haplotype based test of association for multivariate quantitative traits in unrelated samples. Specifically, we extend a population based haplotype trend regression (HTR) approach to multivariate scenarios. We mainly focused on bivariate HTR, and the simulation results showed that the proposed method had correct pre-specified type-I error rates. The power of the proposed method was largely influenced by the size and source of correlation between variables, being greatest when correlation of a specific gene was opposite in sign to the residual correlation.
Multivariate haplotype trend regression; residual correlation
The relationship between obesity and osteoporosis has been widely studied, and epidemiological evidence shows that obesity is correlated with increased bone mass. Previous analyses, however, did not control for the mechanical loading effects of total body weight on bone mass and may have generated a confounded or even biased relationship between obesity and osteoporosis.
To re-evaluate the relationship between obesity and osteoporosis by accounting for the mechanical loading effects of total body weight on bone mass.
We measured whole body fat mass, lean mass, percentage fat mass (PFM), body mass index (BMI), and bone mass in two large samples of different ethnicity: 1,988 unrelated Chinese subjects and 4,489 Caucasian subjects from 512 pedigrees. We first evaluated the Pearson correlations among different phenotypes. We then dissected the phenotypic correlations into genetic and environmental components, with bone mass unadjusted, or adjusted, for body weight. This allowed us to compare the results with and without controlling for mechanical loading effects of body weight on bone mass.
In both Chinese and Caucasians, when the mechanical loading effect of body weight on bone mass was adjusted for, the phenotypic correlation (including its genetic and environmental components) between fat mass (or PFM) and bone mass was negative. Further multivariate analyses in subjects stratified by body weight confirmed the inverse relationship between bone mass and fat mass, after mechanical loading effects due to total body weight was controlled.
Increasing fat mass may not have a beneficial effect on bone mass.