Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis.

Background: The immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data. Methods: The discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results. Results: Three signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA. Conclusion: The present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA.

A Mendelian randomization study for drug repurposing reveals bezafibrate and fenofibric acid as potential osteoporosis treatments.

Background: Lipid pathways have been implicated in the pathogenesis of osteoporosis (OP). Lipid-lowering drugs may be used to prevent and treat OP. However, the causal interpretation of results from traditional observational designs is controversial by confounding. We aimed to investigate the causal association between genetically proxied lipid-lowering drugs and OP risk. Methods: We conducted two-step Mendelian randomization (MR) analyses to investigate the causal association of genetically proxied lipid-lowering drugs on the risk of OP. The first step MR was used to estimate the associations of drug target genes expression with low-density lipoprotein cholesterol (LDL-C) levels. The significant SNPs in the first step MR were used as instrumental variables in the second step MR to estimate the associations of LDL-C levels with forearm bone mineral density (FA-BMD), femoral neck BMD (FN-BMD), lumbar spine BMD (LS-BMD) and fracture. The significant lipid-lowering drugs after MR analyses were further evaluated for their effects on bone mineralization using a dexamethasone-induced OP zebrafish model. Results: The first step MR analysis found that the higher expression of four genes (HMGCR, NPC1L1, PCSK9 and PPARG) was significantly associated with a lower LDL-C level. The genetically decreased LDL-C level mediated by the PPARG was significantly associated with increased FN-BMD (BETA = -1.38, p = 0.001) and LS-BMD (BETA = -2.07, p = 3.35 × 10-5) and was marginally significantly associated with FA-BMD (BETA = -2.36, p = 0.008) and reduced fracture risk (OR = 3.47, p = 0.008). Bezafibrate (BZF) and Fenofibric acid (FBA) act as PPARG agonists. Therefore genetically proxied BZF and FBA had significant protective effects on OP. The dexamethasone-induced OP zebrafish treated with BZF and FBA showed increased bone mineralization area and integrated optical density (IOD) with alizarin red staining. Conclusion: The present study provided evidence that BZF and FBA can increase BMD, suggesting their potential effects in preventing and treating OP. These findings potentially pave the way for future studies that may allow personalized selection of lipid-lowering drugs for those at risk of OP.

Functional Enrichment Analysis Identifying Regulatory Information Associated with Human Fracture.

Dozens of loci associated with fracture have been identified by genome-wide association studies (GWASs). However, most of these variants are located in the noncoding regions including introns, long terminal repeats, and intergenic regions. Although combining regulation information helps to identify the causal SNPs and interpret the involvement of these variants in the etiology of human fracture, regulation information which was truly associated with fracture was unknown. A novel functional enrichment method GARFIELD (GWAS Analysis of Regulatory of Functional Information Enrichment with LD correction) was applied to identify fracture-associated regulation information, including transcript factor binding sites, expression quantitative trait loci (eQTLs), chromatin states, enhancer, promoter, dyadic, super enhancer and Epigenome marks. Fracture SNPs were significantly enriched in exon (Bonferroni correction, p value < 7.14 × 10-3) at two GWAS p value thresholds through GARFIELD. High level of fold-enrichment was observed in super enhancer of monocyte and the enhancer of chondrocyte (Bonferroni correction, p value < 4.45 × 10-3). eQTLs of 44 tissues/cells and 10 transcription factors (TFs) were identified to be associated with human fracture. These results provide new insight into the etiology of human fracture, which might increase the identification of the causal SNPs through the fine-mapping study combined with functional annotation, as well as polygenic risk score.

Dissection of Cellular Communication between Human Primary Osteoblasts and Bone Marrow Mesenchymal Stem Cells in Osteoarthritis at Single-Cell Resolution.

Background and Objectives: Osteoblasts are derived from bone marrow mesenchymal stem cells (BMMSCs) and play important role in bone remodeling. While our previous studies have investigated the cell subtypes and heterogeneity in osteoblasts and BMMSCs separately, cell-to-cell communications between osteoblasts and BMMSCs in vivo in humans have not been characterized. The aim of this study was to investigate the cellular communication between human primary osteoblasts and bone marrow mesenchymal stem cells. Methods and Results: To investigate the cell-to-cell communications between osteoblasts and BMMSCs and identify new cell subtypes, we performed a systematic integration analysis with our single-cell RNA sequencing (scRNA-seq) transcriptomes data from BMMSCs and osteoblasts. We successfully identified a novel preosteoblasts subtype which highly expressed ATF3, CCL2, CXCL2 and IRF1. Biological functional annotations of the transcriptomes suggested that the novel preosteoblasts subtype may inhibit osteoblasts differentiation, maintain cells to a less differentiated status and recruit osteoclasts. Ligand-receptor interaction analysis showed strong interaction between mature osteoblasts and BMMSCs. Meanwhile, we found FZD1 was highly expressed in BMMSCs of osteogenic differentiation direction. WIF1 and SFRP4, which were highly expressed in mature osteoblasts were reported to inhibit osteogenic differentiation. We speculated that WIF1 and sFRP4 expressed in mature osteoblasts inhibited the binding of FZD1 to Wnt ligand in BMMSCs, thereby further inhibiting osteogenic differentiation of BMMSCs. Conclusions: Our study provided a more systematic and comprehensive understanding of the heterogeneity of osteogenic cells. At the single cell level, this study provided insights into the cell-to-cell communications between BMMSCs and osteoblasts and mature osteoblasts may mediate negative feedback regulation of osteogenesis process.

Imputation of Human Primary Osteoblast Single Cell RNA-Seq Data Identified Three Novel Osteoblastic Subtypes.

BACKGROUND: Recently, single-cell RNA sequencing (scRNA-seq) technology was increasingly used to study transcriptomics at a single-cell resolution, scRNA-seq analysis was complicated by the "dropout", where the data only captures a small fraction of the transcriptome. This phenomenon can lead to the fact that the actual expressed transcript may not be detected. We previously performed osteoblast subtypes classification and dissection on freshly isolated human osteoblasts. MATERIALS AND METHODS: Here, we used the scImpute method to impute the missing values of dropout genes from a scRNA-seq dataset generated on freshly isolated human osteoblasts. RESULTS: Based on the imputed gene expression patterns, we discovered three new osteoblast subtypes. Specifically, these newfound osteoblast subtypes are osteoblast progenitors, and two undetermined osteoblasts. Osteoblast progenitors showed significantly high expression of proliferation related genes (FOS, JUN, JUNB and JUND). Analysis of each subtype showed that in addition to bone formation, these undetermined osteoblasts may involve osteoclast and adipocyte differentiation and have the potential function of regulate immune activation. CONCLUSIONS: Our findings provided a new perspective for studying the osteoblast heterogeneity and potential biological functions of these freshly isolated human osteoblasts at the single-cell level, which provides further insight into osteoblasts subtypes under various (pathological) physiological conditions.

Genome-wide meta-analysis of alcohol use disorder in East Asians.

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. Genome-wide association studies (GWAS) have identified ~30 AUD risk genes in European populations, but many fewer in East Asians. We conducted GWAS and genome-wide meta-analysis of AUD in 13,551 subjects with East Asian ancestry, using published summary data and newly genotyped data from five cohorts: (1) electronic health record (EHR)-diagnosed AUD in the Million Veteran Program (MVP) sample; (2) DSM-IV diagnosed alcohol dependence (AD) in a Han Chinese-GSA (array) cohort; (3) AD in a Han Chinese-Cyto (array) cohort; and (4) two AD Thai cohorts. The MVP and Thai samples included newly genotyped subjects from ongoing recruitment. In total, 2254 cases and 11,297 controls were analyzed. An AUD polygenic risk score was analyzed in an independent sample with 4464 East Asians (Genetic Epidemiology Research in Adult Health and Aging (GERA)). Phenotypes from survey data and ICD-9-CM diagnoses were tested for association with the AUD PRS. Two risk loci were detected: the well-known functional variant rs1229984 in ADH1B and rs3782886 in BRAP (near the ALDH2 gene locus) are the lead variants. AUD PRS was significantly associated with days per week of alcohol consumption (beta = 0.43, SE = 0.067, p = 2.47 × 10-10) and nominally associated with pack years of smoking (beta = 0.09, SE = 0.05, p = 4.52 × 10-2) and ever vs. never smoking (beta = 0.06, SE = 0.02, p = 1.14 × 10-2). This is the largest GWAS of AUD in East Asians to date. Building on previous findings, we were able to analyze pleiotropy, but did not identify any new risk regions, underscoring the importance of recruiting additional East Asian subjects for alcohol GWAS.

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

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

Identification of novel variants associated with osteoporosis, type 2 diabetes and potentially pleiotropic loci using pleiotropic cFDR method.

AIMS: Clinical and epidemiological findings point to an association between type 2 diabetes (T2D) and osteoporosis. Genome-wide association studies (GWASs) have been fruitful in identifying some loci potentially associated with osteoporosis and T2D respectively. However, the total genetic variance for each of these two diseases and the shared genetic determination between them are largely unknown. The aim of this study was to identify novel genetic variants for osteoporosis and/or T2D. METHODS: First, using a pleiotropic conditional false discovery rate (cFDR) method, we analyzed two GWAS summary data of femoral neck bone mineral density (FN_BMD, n = 53,236) and T2D (n = 159,208) to identify novel shared genetic loci. FN_BMD is an important risk factor for osteoporosis. Next, to explore the potential functions of the identified potential pleiotropic genes, differential expression analysis was performed for them in monocytes and peripheral blood mononuclear cells (PBMCs) as these cells are relevant to the etiology of osteoporosis and/or T2D. Further, weighted gene co-expression analysis (WGCNA) was conducted to identify functional connections between novel pleiotropic genes and known osteoporosis/T2D susceptibility genes by using transcriptomic expression datasets in bone biopsies (E-MEXP-1618) and pancreatic islets (GSE50397). Finally, multi-trait fine mapping for the detected pleiotropic risk loci were conducted to identify the SNPs that have the highest probability of being causal for both FN_BMD and T2D. RESULTS: We identified 27 significant SNPs with cFDR<0.05 for FN_BMD and 61 SNPs for T2D respectively. Four loci, rs7068487 (PLEKHA1), rs10885421 (TCF7L2), rs944082 (GNG12-AS1 (WLS)) and rs2065929 (PIFO||PGCP1), were found to be potentially pleiotropic and shared between FN_BMD and T2D (ccFDR<0.05). PLEKHA1 was found differentially expressed in circulating monocytes between high and low BMD subjects, and PBMCs between diabetic and non-diabetic conditions. WGCNA showed that PLEKHA1 and TCF7L2 were interconnected with multiple osteoporosis and T2D associated genes in bone biopsy and pancreatic islets, such as JAG, EN1 and CPE. Fine mapping showed that rs11200594 was a potentially causal variant in the locus of PLEKHA1. rs11200594 is also an eQTL of PLEKHA1 in multiple tissue (e.g. peripheral blood cells, adipose and ovary) and is in strong LD with a number of functional variants. CONCLUSIONS: Four potential pleiotropic loci were identified for shared genetic determination of osteoporosis and T2D. Our study highlights PLEKHA1 as an important potentially pleiotropic gene. The findings may help us gain a better understanding of the shared genetic determination between these two important disorders.

Integration of summary data from GWAS and eQTL studies identified novel causal BMD genes with functional predictions.

PURPOSE: Osteoporosis is a common global health problem characterized by low bone mineral density (BMD) and increased risk of fracture. Genome-wide association studies (GWAS) have identified >100 genetic loci associated with BMD. However, the functional genes responsible for most associations remain largely unknown. We conducted an innovative summary statistic data-based Mendelian randomization (SMR) analysis to identify novel causal genes associated with BMD and explored their potential functional significance. METHODS: After quality control of the largest GWAS meta-analysis data of BMD and the largest expression quantitative trait loci (eQTL) meta-analysis data from peripheral blood samples, 5967 genes were tested using the SMR method. Another eQTL data was used to verify the results. Next we performed a fine-mapping association analysis to investigate the functional SNP in the identified loci. Weighted gene co-expression network analysis (WGCNA) was used to explore functional relationships for the identified novel genes with known putative osteoporosis genes. Further, we assessed functions of the identified genes through in vitro cellular study or previous functional studies. RESULTS: We identified two potentially causal genes (ASB16-AS1 and SYN2) associated with BMD. SYN2 was a novel osteoporosis candidate gene and ASB16-AS1 locus was known to be associated with BMD but was not the nearest gene to the top GWAS SNP. Fine-mapping association analysis showed that rs184478 and rs795000 was predicted to be possible causal SNPs in ASB16-AS1 and SYN2, respectively. ASB16-AS1 co-expressed with several known putative osteoporosis risk genes. In vitro cellular study showed that over-expressed ASB16-AS1 increased the expression of osteoblastogenesis related genes (BMP2 and ALPL), indicating its functional significance. CONCLUSION: Our findings support that ASB16-AS1 and SYN2 may represent two novel functional genes underlying BMD variation. The findings provide a basis for further functional mechanistic studies.

Genome-wide association study of lncRNA polymorphisms with bone mineral density.

Recent studies suggested that long noncoding RNAs (lncRNAs) were widely transcribed in the genome, but their potential roles in the genetic complexity of human disorders required further exploration. The purpose of the present study was to explore genetic polymorphisms of lncRNAs associated with bone mineral density (BMD) and its potential value. Based on the lncRNASNP database, 55,906 lncSNPs were selected to conduct a genome-wide association study meta-analysis among 11,140 individuals of seven independent studies for BMDs at femoral neck (FN), lumbar spine, and total hip (HIP). Promising results were replicated in Genetic Factors for Osteoporosis Consortium (GEFOS Sequencing, n = 32,965). We found two lncRNA loci that were significantly associated with BMD. MEF2C antisense RNA 1 (MEF2C-AS1) located at 5q14.3 was significantly associated with FN-BMD after Bonferroni correction, and the strongest association signal was detected at rs6894139 (P = 3.03 × 10-9 ). LOC100506136 rs6465531 located at 7q21.3 showed significant association with HIP-BMD (P = 7.43 × 10-7 ). MEF2C-AS1 rs6894139 was replicated in GEFOS Sequencing with P-value of 1.43 × 10-23 . Our results illustrated the important role of polymorphisms in lncRNAs in determining variations of BMD and provided justification and evidence for subsequent functional studies.

Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.

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.

Whole-exome sequencing in amyotrophic lateral sclerosis suggests NEK1 is a risk gene in Chinese.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a progressive neurological disease characterised by the degeneration of motor neurons, which are responsible for voluntary movement. There remains limited understanding of disease aetiology, with median survival of ALS of three years and no effective treatment. Identifying genes that contribute to ALS susceptibility is an important step towards understanding aetiology. The vast majority of published human genetic studies, including for ALS, have used samples of European ancestry. The importance of trans-ethnic studies in human genetic studies is widely recognised, yet a dearth of studies of non-European ancestries remains. Here, we report analyses of novel whole-exome sequencing (WES) data from Chinese ALS and control individuals. METHODS: WES data were generated for 610 ALS cases and 460 controls drawn from Chinese populations. We assessed evidence for an excess of rare damaging mutations at the gene level and the gene set level, considering only singleton variants filtered to have allele frequency less than 5 × 10-5 in reference databases. To meta-analyse our results with a published study of European ancestry, we used a Cochran-Mantel-Haenszel test to compare gene-level variant counts in cases vs controls. RESULTS: No gene passed the genome-wide significance threshold with ALS in Chinese samples alone. Combining rare variant counts in Chinese with those from the largest WES study of European ancestry resulted in three genes surpassing genome-wide significance: TBK1 (p = 8.3 × 10-12), SOD1 (p = 8.9 × 10-9) and NEK1 (p = 1.1 × 10-9). In the Chinese data alone, SOD1 and NEK1 were nominally significantly associated with ALS (p = 0.04 and p = 7 × 10-3, respectively) and the case/control frequencies of rare coding variants in these genes were similar in Chinese and Europeans (SOD1: 1.5%/0.2% vs 0.9%/0.1%, NEK1 1.8%/0.4% vs 1.9%/0.8%). This was also true for TBK1 (1.2%/0.2% vs 1.4%/0.4%), but the association with ALS in Chinese was not significant (p = 0.14). CONCLUSIONS: While SOD1 is already recognised as an ALS-associated gene in Chinese, we provide novel evidence for association of NEK1 with ALS in Chinese, reporting variants in these genes not previously found in Europeans.

Cross-ethnic meta-analysis identifies association of the GPX3-TNIP1 locus with amyotrophic lateral sclerosis.

Cross-ethnic genetic studies can leverage power from differences in disease epidemiology and population-specific genetic architecture. In particular, the differences in linkage disequilibrium and allele frequency patterns across ethnic groups may increase gene-mapping resolution. Here we use cross-ethnic genetic data in sporadic amyotrophic lateral sclerosis (ALS), an adult-onset, rapidly progressing neurodegenerative disease. We report analyses of novel genome-wide association study data of 1,234 ALS cases and 2,850 controls. We find a significant association of rs10463311 spanning GPX3-TNIP1 with ALS (p = 1.3 × 10-8), with replication support from two independent Australian samples (combined 576 cases and 683 controls, p = 1.7 × 10-3). Both GPX3 and TNIP1 interact with other known ALS genes (SOD1 and OPTN, respectively). In addition, GGNBP2 was identified using gene-based analysis and summary statistics-based Mendelian randomization analysis, although further replication is needed to confirm this result. Our results increase our understanding of genetic aetiology of ALS.Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease. Here, Wray and colleagues identify association of the GPX3-TNIP1 locus with ALS using cross-ethnic meta-analyses.

Functional relevance for associations between osteoporosis and genetic variants.

Osteoporosis is characterized by increased bone loss and deterioration of bone microarchitecture, which will lead to reduced bone strength and increased risk of fragility fractures. Previous studies have identified many genetic loci associated with osteoporosis, but functional mechanisms underlying the associations have rarely been explored. In order to explore the potential molecular functional mechanisms underlying the associations for osteoporosis, we performed integrative analyses by using the publically available datasets and resources. We searched 128 identified osteoporosis associated SNPs (P<10-6), and 8 SNPs exert cis-regulation effects on 11 eQTL target genes. Among the 8 SNPs, 2 SNPs (RPL31 rs2278729 and LRP5 rs3736228) were confirmed to impact the expression of 3 genes (RPL31, CPT1A and MTL5) that were differentially expressed between human subjects of high BMD group and low BMD group. All of the functional evidence suggested the important functional mechanisms underlying the associations of the 2 SNPs (rs2278729 and rs3736228) and 3 genes (RPL31, CPT1A and MTL5) with osteoporosis. This study may provide novel insights into the functional mechanisms underlying the osteoporosis associated genetic variants, which will help us to comprehend the potential mechanisms underlying the genetic association for osteoporosis.

SNP-SNP interactions between WNT4 and WNT5A were associated with obesity related traits in Han Chinese Population.

Considering the biological roles of WNT4 and WNT5A involved in adipogenesis, we aimed to investigate whether SNPs in WNT4 and WNT5A contribute to obesity related traits in Han Chinese population. Targeted genomic sequence for WNT4 and WNT5A was determined in 100 Han Chinese subjects and tag SNPs were selected. Both single SNP and SNP × SNP interaction association analyses with body mass index (BMI) were evaluated in the 100 subjects and another independent sample of 1,627 Han Chinese subjects. Meta-analyses were performed and multiple testing corrections were carried out using the Bonferroni method. Consistent with the Genetic Investigation of ANthropometric Traits (GIANT) dataset results, we didn't detect significant association signals in single SNP association analyses. However, the interaction between rs2072920 and rs11918967, was associated with BMI after multiple testing corrections (combined P = 2.20 × 10-4). The signal was also significant in each contributing data set. SNP rs2072920 is located in the 3'-UTR of WNT4 and SNP rs11918967 is located in the intron of WNT5A. Functional annotation results revealed that both SNPs might be involved in transcriptional regulation of gene expression. Our results suggest that a combined effect of SNPs via WNT4-WNT5A interaction may affect the variation of BMI in Han Chinese population.

Bivariate genome-wide association analyses identified genetic pleiotropic effects for bone mineral density and alcohol drinking in Caucasians.

Several studies indicated bone mineral density (BMD) and alcohol intake might share common genetic factors. The study aimed to explore potential SNPs/genes related to both phenotypes in US Caucasians at the genome-wide level. A bivariate genome-wide association study (GWAS) was performed in 2069 unrelated participants. Regular drinking was graded as 1, 2, 3, 4, 5, or 6, representing drinking alcohol never, less than once, once or twice, three to six times, seven to ten times, or more than ten times per week respectively. Hip, spine, and whole body BMDs were measured. The bivariate GWAS was conducted on the basis of a bivariate linear regression model. Sex-stratified association analyses were performed in the male and female subgroups. In males, the most significant association signal was detected in SNP rs685395 in DYNC2H1 with bivariate spine BMD and alcohol drinking (P = 1.94 × 10-8). SNP rs685395 and five other SNPs, rs657752, rs614902, rs682851, rs626330, and rs689295, located in the same haplotype block in DYNC2H1 were the top ten most significant SNPs in the bivariate GWAS in males. Additionally, two SNPs in GRIK4 in males and three SNPs in OPRM1 in females were suggestively associated with BMDs (of the hip, spine, and whole body) and alcohol drinking. Nine SNPs in IL1RN were only suggestively associated with female whole body BMD and alcohol drinking. Our study indicated that DYNC2H1 may contribute to the genetic mechanisms of both spine BMD and alcohol drinking in male Caucasians. Moreover, our study suggested potential pleiotropic roles of OPRM1 and IL1RN in females and GRIK4 in males underlying variation of both BMD and alcohol drinking.

Integrating Epigenomic Elements and GWASs Identifies BDNF Gene Affecting Bone Mineral Density and Osteoporotic Fracture Risk.

To identify susceptibility genes for osteoporosis, we conducted an integrative analysis that combined epigenomic elements and previous genome-wide association studies (GWASs) data, followed by validation at population and functional levels, which could identify common regulatory elements and predict new susceptibility genes that are biologically meaningful to osteoporosis. By this approach, we found a set of distinct epigenomic elements significantly enriched or depleted in the promoters of osteoporosis-associated genes, including 4 transcription factor binding sites, 27 histone marks, and 21 chromatin states segmentation types. Using these epigenomic marks, we performed reverse prediction analysis to prioritize the discovery of new candidate genes. Functional enrichment analysis of all the prioritized genes revealed several key osteoporosis related pathways, including Wnt signaling. Genes with high priority were further subjected to validation using available GWASs datasets. Three genes were significantly associated with spine bone mineral density, including BDNF, PDE4D, and SATB2, which all closely related to bone metabolism. The most significant gene BDNF was also associated with osteoporotic fractures. RNA interference revealed that BDNF knockdown can suppress osteoblast differentiation. Our results demonstrated that epigenomic data could be used to indicate common epigenomic marks to discover additional loci with biological functions for osteoporosis.

Identification of IDUA and WNT16 Phosphorylation-Related Non-Synonymous Polymorphisms for Bone Mineral Density in Meta-Analyses of Genome-Wide Association Studies.

Protein phosphorylation regulates a wide variety of cellular processes. Thus, we hypothesize that single-nucleotide polymorphisms (SNPs) that may modulate protein phosphorylation could affect osteoporosis risk. Based on a previous conventional genome-wide association (GWA) study, we conducted a three-stage meta-analysis targeting phosphorylation-related SNPs (phosSNPs) for femoral neck (FN)-bone mineral density (BMD), total hip (HIP)-BMD, and lumbar spine (LS)-BMD phenotypes. In stage 1, 9593 phosSNPs were meta-analyzed in 11,140 individuals of various ancestries. Genome-wide significance (GWS) and suggestive significance were defined by α = 5.21 × 10(-6) (0.05/9593) and 1.00 × 10(-4), respectively. In stage 2, nine stage 1-discovered phosSNPs (based on α = 1.00 × 10(-4)) were in silico meta-analyzed in Dutch, Korean, and Australian cohorts. In stage 3, four phosSNPs that replicated in stage 2 (based on α = 5.56 × 10(-3), 0.05/9) were de novo genotyped in two independent cohorts. IDUA rs3755955 and rs6831280, and WNT16 rs2707466 were associated with BMD phenotypes in each respective stage, and in three stages combined, achieving GWS for both FN-BMD (p = 8.36 × 10(-10), p = 5.26 × 10(-10), and p = 3.01 × 10(-10), respectively) and HIP-BMD (p = 3.26 × 10(-6), p = 1.97 × 10(-6), and p = 1.63 × 10(-12), respectively). Although in vitro studies demonstrated no differences in expressions of wild-type and mutant forms of IDUA and WNT16B proteins, in silico analyses predicts that WNT16 rs2707466 directly abolishes a phosphorylation site, which could cause a deleterious effect on WNT16 protein, and that IDUA phosSNPs rs3755955 and rs6831280 could exert indirect effects on nearby phosphorylation sites. Further studies will be required to determine the detailed and specific molecular effects of these BMD-associated non-synonymous variants.