An in vivo genome wide gene expression study of circulating monocytes suggested GBP1, STAT1 and CXCL10 as novel risk genes for the differentiation of peak bone mass

Integrative analysis of multi-omics data to detect the underlying molecular mechanisms for obesity in vivo in humans

BACKGROUND

Obesity is a complex, multifactorial condition in which genetic play an important role. Most of the systematic studies currently focuses on individual omics aspect and provide insightful yet limited knowledge about the comprehensive and complex crosstalk between various omics levels.

SUBJECTS AND METHODS

Therefore, we performed a most comprehensive trans-omics study with various omics data from 104 subjects, to identify interactions/networks and particularly causal regulatory relationships within and especially those between omic molecules with the purpose to discover molecular genetic mechanisms underlying obesity etiology in vivo in humans.

RESULTS

By applying differentially analysis, we identified 8 differentially expressed hub genes (DEHGs), 14 differentially methylated regions (DMRs) and 12 differentially accumulated metabolites (DAMs) for obesity individually. By integrating those multi-omics biomarkers using Mendelian Randomization (MR) and network MR analyses, we identified 18 causal pathways with mediation effect. For the 20 biomarkers involved in those 18 pairs, 17 biomarkers were implicated in the pathophysiology of obesity or related diseases.

CONCLUSIONS

The integration of trans-omics and MR analyses may provide us a holistic understanding of the underlying functional mechanisms, molecular regulatory information flow and the interactive molecular systems among different omic molecules for obesity risk and other complex diseases/traits.

Osteoclast fusion and bone loss are restricted by interferon inducible guanylate binding proteins

Chronic inflammation during many diseases is associated with bone loss. While interferons (IFNs) are often inhibitory to osteoclast formation, the complex role that IFN and interferon-stimulated genes (ISGs) play in osteoimmunology during inflammatory diseases is still poorly understood. We show that mice deficient in IFN signaling components including IFN alpha and beta receptor 1 (IFNAR1), interferon regulatory factor 1 (IRF1), IRF9, and STAT1 each have reduced bone density and increased osteoclastogenesis compared to wild type mice. The IFN-inducible guanylate-binding proteins (GBPs) on mouse chromosome 3 (GBP1, GBP2, GBP3, GBP5, GBP7) are required to negatively regulate age-associated bone loss and osteoclastogenesis. Mechanistically, GBP2 and GBP5 both negatively regulate in vitro osteoclast differentiation, and loss of GBP5, but not GBP2, results in greater age-associated bone loss in mice. Moreover, mice deficient in GBP5 or chromosome 3 GBPs have greater LPS-mediated inflammatory bone loss compared to wild type mice. Overall, we find that GBP5 contributes to restricting age-associated and inflammation-induced bone loss by negatively regulating osteoclastogenesis.

Identification and Analysis of Genes Underlying Bone Mineral Density by Integrating Microarray Data of Osteoporosis

Osteoporosis is a kind of brittle bone disease, which is characterized by a reduction in bone mineral density (BMD). In recent years, a number of genes and pathophysiological mechanisms have been identified for osteoporosis. However, the genes associated with BMD remain to be explored. Toward this end, we integrated multiple osteoporosis microarray datasets to identify and systematically characterize BMD-related genes. By integrating the differentially expressed genes from three osteoporosis microarray datasets, 152 genes show differentially expressed between high and low BMD osteoporosis samples in at least two of the three datasets. Among them, 88 were up-regulated in high BMD samples and 64 were up-regulated in low BMD samples. The expression of ZFP36, JUNB and TMEM8A were increased at high BMD samples in all three datasets. Hub genes were further identified by co-expression network analysis. Functional enrichment analysis showed that the gene up-regulated in high BMD were enriched in immune-related functions, suggesting that the immune system plays an important role in osteoporosis. Our study explored BMD-related genes based on the integration of osteoporosis microarray data, providing guidance to other researchers from a new perspective.

Screening pathways and hub genes involved in osteoclastogenesis by gene expression analysis of circulating monocytes based on Gibbs sampling

Differential expression pathways and hub genes in circulating monocytes from healthy Chinese women with high peak bone mass (PBM) vs. low PBM were explored using a Markov chain Monte Carlo (MCMC) algorithm. Human circulating monocytes transcription profiling (containing 14 samples with high PBM and 12 samples with low PBM) and KEGG pathways were all downloaded from the public database. Initial state of all the pathways were constructed and Gibbs sampling was performed to obtain a Markov chain and the posterior values of all the pathways were calculated. The probability (α) of occurrence of each pathway was calculated based on the posterior value and it was adjusted by taking gene expression variation into account. Pathways with α_adj >0.8 were considered as differentially expressed pathways. Then, these steps were performed again on all the genes in the differentially expressed pathways to find the hub genes in the differential pathways. After Gibbs sampling, neuroactive ligand-receptor interaction (hsa04080) with α_adj = 0.986 was screened out as the differentially expressed pathway. Analyzing the genes in this pathway, three genes (neurotensin, tachykinin receptor 3 and follicle-stimulating hormone receptor) with α_adj >0.8 were identified as hub genes in circulating monocytes which may associate with osteoporosis development. One pathway and three genes which may possess close relationship with osteoporosis development were found in this study. These results provide insights into our understanding of the role of circulating monocytes in osteoporosis development.

Gene-based GWAS analysis for consecutive studies of GEFOS

By integrating the multilevel biological evidence and bioinformatics analyses, the present study represents a systemic endeavor to identify BMD-associated genes and their roles in skeletal metabolism.

INTRODUCTION

Single-nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) have already identified about 100 loci associated with bone mineral density (BMD), but these loci only explain a small proportion of heritability to osteoporosis risk. In the present study, we performed a gene-based analysis of the largest GWASs in the bone field to identify additional BMD-associated genes.

METHODS

BMD-associated genes were identified by combining the summary statistic P values of SNPs across individual genes in the two consecutive meta-analyses of GWASs from the Genetic Factors for Osteoporosis (GEFOS) studies. The potential functionality of these genes to bone was partially assessed by differential gene expression analysis. Additionally, the consistency of the identification of potential bone mineral density (BMD)-associated variants were evaluated by estimating the correlation of the P values of the same single-nucleotide polymorphisms (SNPs)/genes between the two consecutive Genetic Factors for Osteoporosis Studies (GEFOS) with largely overlapping samples.

RESULTS

Compared to the SNP-based analysis, the gene-based strategy identified additional BMD-associated genes with genome-wide significance and increased their mutual replication between the two GEFOS datasets. Among these BMD-associated genes, three novel genes (UBTF, AAAS, and C11orf58) were partially validated at the gene expression level. The correlation analysis presented a moderately high between-study consistency of potential BMD-associated variants.

CONCLUSIONS

Gene-based analysis as a supplementary strategy to SNP-based genome-wide association studies, when applied here, is shown that it helped identify some novel BMD-associated genes. In addition to its empirically increased statistical power, gene-based analysis also provides a higher testing stability for identification of BMD genes.

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.

The evolutionary dynamics of microRNAs in domestic mammals

MiRNAs are crucial regulators of gene expression found across both the plant and animal kingdoms. While the number of annotated miRNAs deposited in miRBase has greatly increased in recent years, few studies provided comparative analyses across sets of related species, or investigated the role of miRNAs in the evolution of gene regulation. We generated small RNA libraries across 5 mammalian species (cow, dog, horse, pig and rabbit) from 4 different tissues (brain, heart, kidney and testis). We identified 1676 miRBase and 413 novel miRNAs by manually curating the set of computational predictions obtained from miRCat and miRDeep2. Our dataset spanning five species has enabled us to investigate the molecular mechanisms and selective pressures driving the evolution of miRNAs in mammals. We highlight the important contributions of intronic sequences (366 orthogroups), duplication events (135 orthogroups) and repetitive elements (37 orthogroups) in the emergence of new miRNA loci. We use this framework to estimate the patterns of gains and losses across the phylogeny, and observe high levels of miRNA turnover. Additionally, the identification of lineage-specific losses enables the characterisation of the selective constraints acting on the associated target sites. Compared to the miRBase subset, novel miRNAs tend to be more tissue specific. 20 percent of novel orthogroups are restricted to the brain, and their target repertoires appear to be enriched for neuron activity and differentiation processes. These findings may reflect an important role for young miRNAs in the evolution of brain expression plasticity. Many seed sequences appear to be specific to either the cow or the dog. Analyses on the associated targets highlight the presence of several genes under artificial positive selection, suggesting an involvement of these miRNAs in the domestication process. Altogether, we provide an overview on the evolutionary mechanisms responsible for miRNA turnover in 5 domestic species, and their possible contribution to the evolution of gene regulation.

Identification of an Epigenetic Signature of Osteoporosis in Blood DNA of Postmenopausal Women

Osteoporosis is one of the most common age-related progressive bone diseases in elderly people. Approximately one in three women and one in five men are predisposed to developing osteoporosis. In postmenopausal women, a reduction in BMD leads to an increased risk of fractures. In the current study, we delineated the DNA methylation signatures in whole blood samples of postmenopausal osteoporotic women. We obtained whole blood DNA from 22 normal women and 22 postmenopausal osteoporotic women (51 to 89 years old) from the Canadian Multicenter Osteoporosis Study (CaMos) cohort. These DNA samples were subjected to Illumina Infinium human methylation 450 K analysis. Illumina 450K raw data were analyzed by Genome Studio software. Analysis of the female participants with early and advanced osteoporosis resulted in the generation of a list of 1233 differentially methylated CpG sites when compared with age-matched normal women. T test, ANOVA, and post hoc statistical analyses were performed, and 77 significantly differentially methylated CpG sites were identified. From the 13 most significant genes, ZNF267, ABLIM2, RHOJ, CDKL5, and PDCD1 were selected for their potential role in bone biology. A weighted polygenic DNA methylation score of these genes predicted osteoporosis at an early stage with high sensitivity and specificity and correlated with measures of bone density. Pyrosequencing analysis of these genes was performed to validate the results obtained from Illumina 450 K methylation analysis. The current study provides proof of principal for the role of DNA methylation in osteoporosis. Using whole blood DNA methylation analysis, women at risk of developing osteoporosis can be identified before a diagnosis of osteoporosis is made using BMD as a screening method. Early diagnosis will help to select patients who might benefit from early therapeutic intervention. © 2018 American Society for Bone and Mineral Research.

Genome-wide identification of m6A-associated SNPs as potential functional variants for bone mineral density

This study investigated the effect of the N⁶-methyladenosine (m⁶A)-associated SNPs on bone mineral density (BMD) and found plenty of m⁶A-SNPs that were associated with BMD. This study increases our understanding on the regulation patterns of SNP and may provide new clues for further detection of functional mechanism underlying the associations between SNPs and osteoporosis.

INTRODUCTION

m⁶A plays critical roles in many fundamental biological processes and a variety of diseases. The m⁶A-associated SNPs may be potential functional variants for BMD. The aim of this study was to investigate the effect of the genome-wide m⁶A-SNPs on BMD.

METHODS

We examined the association of m⁶A-SNPs with femoral neck (FN) and lumbar spine (LS) BMD in 32,961 individuals and quantitative heel ultrasounds (eBMD) in 142,487 individuals. Furthermore, we performed expression quantitative trait locus (eQTL) analyses for the m⁶A-SNPs using whole genome data of about 10.5 million SNPs and 21,323 mRNAs from 43 Chinese individuals, as well as public available data. Differential expression analyses were also performed to support the identified genes.

RESULTS

We found 138, 125, and 993 m⁶A-SNPs which were associated with FN-BMD, LS-BMD, and eBMD (P < 0.05), respectively. The associations of rs11614913 (P = 8.92 × 10^-10) in MIR196A2 and rs1110720 (P = 2.05 × 10^-10) in ESPL1 with LS-BMD reached the genome-wide significance level. In addition, a total of 24 m⁶A-SNPs were significantly associated with eBMD (P < 5.0 × 10^-8). Further eQTL analyses showed that 47 of these BMD-associated m⁶A-SNPs were associated with expressions of the 46 corresponding local genes. Moreover, the expressions of 26 of these genes were associated with BMD.

CONCLUSION

The present study represents the first effort of investigating the associations and the mechanisms underlying the link between m⁶A-SNPs and BMD. The results suggested that m⁶A-SNP may play important roles in the pathology of osteoporosis.

Differential network as an indicator of osteoporosis with network entropy

Osteoporosis is a common skeletal disorder characterized by a decrease in bone mass and density. The peak bone mass (PBM) is a significant determinant of osteoporosis. To gain insights into the indicating effect of PBM to osteoporosis, this study focused on characterizing the PBM networks and identifying key genes. One biological data set with 12 monocyte low PBM samples and 11 high PBM samples was derived to construct protein-protein interaction networks (PPINs). Based on clique-merging, module-identification algorithm was used to identify modules from PPINs. The systematic calculation and comparison were performed to test whether the network entropy can discriminate the low PBM network from high PBM network. We constructed 32 destination networks with 66 modules divided from monocyte low and high PBM networks. Among them, network 11 was the only significantly differential one (P<0.05) with 8 nodes and 28 edges. All genes belonged to precursors of osteoclasts, which were related to calcium transport as well as blood monocytes. In conclusion, based on the entropy in PBM PPINs, the differential network appears to be a novel therapeutic indicator for osteoporosis during the bone monocyte progression; these findings are helpful in disclosing the pathogenetic mechanisms of osteoporosis.

"Omics" Signatures in Peripheral Monocytes from Women with Low BMD Condition

Postmenopausal osteoporosis (PMO) is a result of increased bone resorption compared to formation. Osteoclasts are responsible for bone resorption, which are derived from circulating monocytes that undertake a journey from the blood to the bone for the process of osteoclastogenesis. In recent times, the use of high throughput technologies to explore monocytes from women with low versus high bone density has led to the identification of candidate molecules that may be deregulated in PMO. This review provides a list of molecules in monocytes relevant to bone density which have been identified by "omics" studies in the last decade or so. The molecules in monocytes that are deregulated in low BMD condition may contribute to processes such as monocyte survival, migration/chemotaxis, adhesion, transendothelial migration, and differentiation into the osteoclast lineage. Each of these processes may be crucial to the overall route of osteoclastogenesis and an increase in any/all of these processes can lead to increased bone resorption and subsequently low bone density. Whether these molecules are indeed the cause or effect is an arena currently unexplored.

Guanylate Binding Protein 1 Inhibits Osteogenic Differentiation of Human Mesenchymal Stromal Cells Derived from Bone Marrow

Guanylate Binding Proteins (GBPs) are a group of cytokine-inducible large guanosine triphosphatase. Previous studies have shown high expression of GBP1 in circulating monocytes of premenopausal subjects was correlated to extremely low peak bone mass, which is considered as an important determinant of osteoporosis. However, whether GBPs play a role in regulation of osteogenesis of mesenchymal stromal cells (MSCs) remains largely unknown. In the present study, we found that mRNA expression of GBP1 was highest among all the GBPs, and it was dramatically downregulated during osteogenic differentiation of human MSCs derived from bone marrow (hBM-MSCs). While siRNA-mediated knockdown of GBP1 promoted osteogenesis, overexpression of GBP1 suppressed osteogenesis of hBM-MSCs. Furthermore, we found GBP1 is required for expression of indoleamine 2,3 dioxygenase (IDO), Interleukin 6 (IL-6) and IL-8 induced by treatment with Interferon-γ (IFN-γ). Depletion of GBP1 rescued the inhibited osteogenesis induced by IFN-γ treatment, at least in part. Collectively, our findings indicate GBP1 inhibits osteogenic differentiation of MSCs, and inhibition of GBP1 expression may prevent development of osteoporosis and facilitate MSC-based bone regeneration.

Network based subcellular proteomics in monocyte membrane revealed novel candidate genes involved in osteoporosis

In this study, label-free-based quantitative subcellular proteomics integrated with network analysis highlighted several candidate genes including P4HB, ITGB1, CD36, and ACTN1 that may be involved in osteoporosis. All of them are predicted as significant membrane proteins with high confidence and enriched in bone-related biological process. The results were further verified in transcriptomic and genomic levels.

INTRODUCTION

Osteoporosis is a metabolic bone disease mainly characterized by low bone mineral density (BMD). As the precursors of osteoclasts, peripheral blood monocytes (PBMs) are supported to be important candidates for identifying genes related to osteoporosis. We performed subcellular proteomics study to identify significant membrane proteins that involved in osteoporosis.

METHODS

To investigate the association between monocytes, membrane proteins, and osteoporosis, we performed label-free quantitative subcellular proteomics in 59 male subjects with discordant BMD levels, with 30 high vs. 29 low BMD subjects. Subsequently, we performed integrated gene enrichment analysis, functional annotation, and pathway and network analysis based on multiple bioinformatics tools.

RESULTS

A total of 1070 membrane proteins were identified and quantified. By comparing the proteins' expression level, we found 36 proteins that were differentially expressed between high and low BMD groups. Protein localization prediction supported the notion that the differentially expressed proteins, P4HB (p = 0.0021), CD36 (p = 0.0104), ACTN1 (p = 0.0381), and ITGB1 (p = 0.0385), are significant membrane proteins. Functional annotation and pathway and network analysis highlighted that P4HB, ITGB1, CD36, and ACTN1 are enriched in osteoporosis-related pathways and terms including "ECM-receptor interaction," "calcium ion binding," "leukocyte transendothelial migration," and "reduction of cytosolic calcium levels." Results from transcriptomic and genomic levels provided additional supporting evidences.

CONCLUSION

Our study strongly supports the significance of the genes P4HB, ITGB1, CD36, and ACTN1 to the etiology of osteoporosis risk.

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.

Identification of candidate genes in osteoporosis by integrated microarray analysis

Objectives

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis.

Methods

We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs.

Results

A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57).

Conclusion

Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.

Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594–601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1.

Elevated Response to Type I IFN Enhances RANKL-Mediated Osteoclastogenesis in Usp18-Knockout Mice

A balance between bone formation and bone resorption is critical for the maintenance of bone mass. In many pathological conditions, including chronic inflammation, uncontrolled activation of osteoclast differentiation often causes excessive bone resorption that results in osteoporosis. In this study, we identified the osteopenia phenotype of mice lacking Usp18 (also called Ubp43), which is a deISGylating enzyme and is known as a negative regulator of type I IFN signaling. The expression of Usp18 was induced in preosteoclasts upon receptor activator of NF-κB ligand (RANKL) treatment. In an in vitro osteoclast-differentiation assay, bone marrow macrophages from Usp18-deficient mice exhibited an enhanced differentiation to multinucleated cells, elevated activation of NFATc1, and an increased expression of osteoclast marker genes upon RANKL treatment. Furthermore, in vitro quantification of bone resorption revealed a great increase in osteoclastic activities in Usp18-deficient cells. Interestingly, proinflammatory cytokine genes, such as IP-10 (CXCL10), were highly expressed in Usp18-deficient bone marrow macrophages upon RANKL treatment compared with wild-type cells. In addition, serum cytokine levels, especially IP-10, were significantly high in Usp18-knockout mice. In sum, we suggest that, although type I IFN is known to restrict osteoclast differentiation, the exaggerated activation of the type I IFN response in Usp18-knockout mice causes an osteopenia phenotype in mice.

Establishment of a Novel Primary Human Skeletal Myoblast Cellular Model for Chikungunya Virus Infection and Pathogenesis

Chikungunya virus (CHIKV) is a re-emerging arbovirus known to cause chronic myalgia and arthralgia and is now considered endemic in countries across Asia and Africa. The tissue tropism of CHIKV infection in humans remains, however, ill-defined. Due to the fact that myositis is commonly observed in most patients infected with CHIKV, we sought to develop a clinically relevant cellular model to better understand the pathogenesis of CHIKV infection. In this study, primary human skeletal muscle myoblasts (HSMM) were established as a novel human primary cell line that is highly permissive to CHIKV infection, with maximal amounts of infectious virions observed at 16 hours post infection. Genome-wide microarray profiling analyses were subsequently performed to identify and map genes that are differentially expressed upon CHIKV infection. Infection of HSMM cells with CHIKV resulted in altered expressions of host genes involved in skeletal- and muscular-associated disorders, innate immune responses, cellular growth and death, host metabolism and virus replication. Together, this study has shown the establishment of a clinically relevant primary human cell model that paves the way for the further analysis of host factors and their involvement in the various stages of CHIKV replication cycle and viral pathogenesis.

Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women

Background

Existing microarray studies of bone mineral density (BMD) have been critical for understanding the pathophysiology of osteoporosis, and have identified a number of candidate genes. However, these studies were limited by their relatively small sample sizes and were usually analyzed individually. Here, we propose a novel network-based meta-analysis approach that combines data across six microarray studies to identify functional modules from human protein-protein interaction (PPI) data, and highlight several differentially expressed genes (DEGs) and a functional module that may play an important role in BMD regulation in women.

Methods

Expression profiling studies were identified by searching PubMed, Gene Expression Omnibus (GEO) and ArrayExpress. Two meta-analysis methods were applied across different gene expression profiling studies. The first, a nonparametric Fisher’s method, combined p-values from individual experiments to identify genes with large effect sizes. The second method combined effect sizes from individual datasets into a meta-effect size to gain a higher precision of effect size estimation across all datasets. Genes with Q test’s p-values < 0.05 or I² values > 50% were assessed by a random effects model and the remainder by a fixed effects model. Using Fisher’s combined p-values, functional modules were identified through an integrated analysis of microarray data in the context of large protein–protein interaction (PPI) networks. Two previously published meta-analysis studies of genome-wide association (GWA) datasets were used to determine whether these module genes were genetically associated with BMD. Pathway enrichment analysis was performed with a hypergeometric test.

Results

Six gene expression datasets were identified, which included a total of 249 (129 high BMD and 120 low BMD) female subjects. Using a network-based meta-analysis, a consensus module containing 58 genes (nodes) and 83 edges was detected. Pathway enrichment analysis of the 58 module genes revealed that these genes were enriched in several important KEGG pathways including Osteoclast differentiation, B cell receptor signaling pathway, MAPK signaling pathway, Chemokine signaling pathway and Insulin signaling pathway. The importance of module genes was replicated by demonstrating that most module genes were genetically associated with BMD in the GWAS data sets. Meta-analyses were performed at the individual gene level by combining p-values and effect sizes. Five candidate genes (ESR1, MAP3K3, PYGM, RAC1 and SYK) were identified based on gene expression meta-analysis, and their associations with BMD were also replicated by two BMD meta-analysis studies.

Conclusions

In summary, our network-based meta-analysis not only identified important differentially expressed genes but also discovered biologically meaningful functional modules for BMD determination. Our study may provide novel therapeutic targets for osteoporosis in women.

Bone health nutraceuticals alter microarray mRNA gene expression: A randomized, parallel, open-label clinical study

BACKGROUND AND OBJECTIVE

Dietary intake of fruits and vegetables has been suggested to have a role in promoting bone health. More specifically, the polyphenols they contain have been linked to physiological effects related to bone mineral density and bone metabolism. In this research, we use standard microarray analyses of peripheral whole blood from post-menopausal women treated with two fixed combinations of plant extracts standardized to polyphenol content to identify differentially expressed genes relevant to bone health.

METHODS

In this 28-day open-label study, healthy post-menopausal women were randomized into three groups, each receiving one of three investigational fixed combinations of plant extracts: an anti-resorptive (AR) combination of pomegranate fruit (Punica granatum L.) and grape seed (Vitis vinifera L.) extracts; a bone formation (BF) combination of quercetin (Dimorphandra mollis Benth) and licorice (Glycyrrhiza glabra L.) extracts; and a fixed combination of all four plant extracts (AR plus BF). Standard microarray analysis was performed on peripheral whole blood samples taken before and after each treatment. Annotated genes were analyzed for their association to bone health by comparison to a gene library.

RESULTS

The AR combination down-regulated a number of genes involved in reduction of bone resorption including cathepsin G (CTSG) and tachykinin receptor 1 (TACR1). The AR combination also up-regulated genes associated with formation of extracellular matrix including heparan sulfate proteoglycan 2 (HSPG2) and hyaluronoglucosaminidase 1 (HYAL1). In contrast, treatment with the BF combination resulted in up-regulation of bone morphogenetic protein 2 (BMP-2) and COL1A1 (collagen type I α1) genes which are linked to bone and collagen formation while down-regulating genes linked to osteoclastogenesis. Treatment with a combination of all four plant extracts had a distinctly different effect on gene expression than the results of the AR and BF combinations individually. These results could be due to multiple feedback systems balancing activities of osteoblasts and osteoclasts.

CONCLUSION

In summary, this ex-vivo microarray study indicated that the pomegranate, grape seed, quercetin and licorice combinations of plant extracts modulated gene expression for both osteoclastic and osteogenic processes.

Circulating monocytes: an appropriate model for bone-related study

Peripheral blood monocytes (PBMs) are an important source of precursors of osteoclasts, the bone-resorbing cells and the cytokines produced by PBMs that have profound effects on osteoclast differentiation, activation, and apoptosis. So PBMs represent a highly valuable and unique working cell model for bone-related study. Finding an appropriate working cell model for clinical and (epi-)genomic studies of human skeletal disorders is a challenge. Peripheral blood monocytes (PBMs) can give rise to osteoclasts, the bone-resorbing cells. Particularly, PBMs provide the sole source of osteoclast precursors for adult peripheral skeleton where the bone marrow is normally hematopoietically inactive. PBMs can secrete potent pro- and anti-inflammatory cytokines, which are important for osteoclast differentiation, activation, and apoptosis. Reduced production of PBM cytokines represents a major mechanism for the inhibitory effects of sex hormones on osteoclastogenesis and bone resorption. Abnormalities in PBMs have been linked to various skeletal disorders/traits, strongly supporting for the biological relevance of PBMs with bone metabolism and disorders. Here, we briefly review the origin and further differentiation of PBMs. In particular, we discuss the close relationship between PBMs and osteoclasts, and highlight the utility of PBMs in study the pathophysiological mechanisms underlying various skeletal disorders.

Gene-based association analysis identified novel genes associated with bone mineral density

Genetic factors contribute to the variation of bone mineral density (BMD), which is a major risk factor of osteoporosis. The aim of this study was to identify more “novel” genes for BMD. Based on the publicly available SNP-based P values, we performed an initial gene-based analysis in a total of 32,961 individuals. Furthermore, we performed differential expression, pathway and protein-protein interaction analyses to find supplementary evidence to support the significance of the identified genes. About 21,695 genes for femoral neck (FN)-BMD and 21,683 genes for lumbar spine (LS)-BMD were analyzed using gene-based association analysis. A total of 35 FN-BMD associated genes and 53 LS-BMD associated genes were identified (P < 2.3×10^-6) after Bonferroni correction. Among them, 64 genes have not been reported in previous SNP-based genome-wide association studies. Differential expression analysis further supported the significant associations of 14 genes with FN-BMD and 19 genes with LS-BMD. Especially, WNT3 and WNT9B in the Wnt signaling pathway for FN-BMD were further supported by pathway analysis and protein-protein interaction analysis. The present study took the advantage of gene-based association method to perform a supplementary analysis of the GWAS dataset and found some BMD-associated genes. The evidence taken together supported the importance of Wnt signaling pathway genes in determining osteoporosis. Our findings provided more insights into the genetic basis of osteoporosis.

Attenuated monocyte apoptosis, a new mechanism for osteoporosis suggested by a transcriptome-wide expression study of monocytes

BACKGROUND

Osteoporosis is caused by excessive bone resorption (by osteoclasts) over bone formation (by osteoblasts). Monocytes are important to osteoporosis by serving as progenitors of osteoclasts and produce cytokines for osteoclastogenesis.

AIM

To identify osteoporosis-related genes, we performed microarray analyses of monocytes using Affymetrix 1.0 ST arrays in 42 (including 16 pre- and 26 postmenopausal) high hip BMD (bone mineral density) vs. 31 (including 15 pre- and 16 postmenopausal) low hip BMD Caucasian female subjects. Here, high vs. low BMD is defined as belonging to top vs. bottom 30% of BMD values in population.

METHOD

Differential gene expression analysis in high vs. low BMD subjects was conducted in the total cohort as well as pre- and post-menopausal subjects. Focusing on the top differentially expressed genes identified in the total, the pre- and the postmenopausal subjects (with a p <5E-03), we performed replication of the findings in 3 independent datasets of microarray analyses of monocytes (total N = 125).

RESULTS

We identified (in the 73 subjects) and successfully replicated in all the 3 independent datasets 2 genes, DAXX and PLK3. Interestingly, both genes are apoptosis induction genes and both down-regulated in the low BMD subjects. Moreover, using the top 200 genes identified in the meta-analysis across all of the 4 microarray datasets, GO term enrichment analysis identified a number of terms related to induction of apoptosis, for which the majority of component genes are also down-regulated in the low BMD subjects. Overall, our result may suggest that there might be a decreased apoptosis activity of monocytes in the low BMD subjects.

CONCLUSION

Our study for the first time suggested a decreased apoptosis rate (hence an increased survival) of monocytes, an important osteoclastogenic cell, as a novel mechanism for osteoporosis.

Integrative analysis of GWASs, human protein interaction, and gene expression identified gene modules associated with BMDs

CONTEXT

To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk.

METHODS

First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa.

RESULTS

In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation.

CONCLUSION

We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis.

Integrative analysis of multiple diverse omics datasets by sparse group multitask regression

A variety of high throughput genome-wide assays enable the exploration of genetic risk factors underlying complex traits. Although these studies have remarkable impact on identifying susceptible biomarkers, they suffer from issues such as limited sample size and low reproducibility. Combining individual studies of different genetic levels/platforms has the promise to improve the power and consistency of biomarker identification. In this paper, we propose a novel integrative method, namely sparse group multitask regression, for integrating diverse omics datasets, platforms, and populations to identify risk genes/factors of complex diseases. This method combines multitask learning with sparse group regularization, which will: (1) treat the biomarker identification in each single study as a task and then combine them by multitask learning; (2) group variables from all studies for identifying significant genes; (3) enforce sparse constraint on groups of variables to overcome the "small sample, but large variables" problem. We introduce two sparse group penalties: sparse group lasso and sparse group ridge in our multitask model, and provide an effective algorithm for each model. In addition, we propose a significance test for the identification of potential risk genes. Two simulation studies are performed to evaluate the performance of our integrative method by comparing it with conventional meta-analysis method. The results show that our sparse group multitask method outperforms meta-analysis method significantly. In an application to our osteoporosis studies, 7 genes are identified as significant genes by our method and are found to have significant effects in other three independent studies for validation. The most significant gene SOD2 has been identified in our previous osteoporosis study involving the same expression dataset. Several other genes such as TREML2, HTR1E, and GLO1 are shown to be novel susceptible genes for osteoporosis, as confirmed from other studies.

Analysis of protein-protein interaction network and functional modules on primary osteoporosis

Background

Primary osteoporosis is an age-related disease, and the main cause of this disease is the failure of bone homeostasis. Previous studies have shown that primary osteoporosis is associated with gene mutations.

To explore the functional modules of the PPI (protein-protein interaction) network of differentially expressed genes (DEGs), and the related pathways participating in primary osteoporosis.

Methods

The gene expression profile of primary osteoporosis GSE35956 was downloaded from the GEO (Gene Expression Omnibus) database and included five MSC (mesenchymal stem cell) specimens of normal osseous tissue and five MSC specimens of osteoporosis. The DEGs between the two types of MSC specimens were identified by the samr package in R language. In addition, the functions and pathways of DEGs were enriched. Then the DEGs were mapped to String to acquire PPI pairs and the PPI network was constructed with by these PPI pairs. Topological properties of the network were calculated by Network Analyzer, and modules in the network were screened by Cluster ONE software. Subsequently, the fronting five modules whose P-value was less than 1.0e-05 were identified and function analysis was conducted.

Results

A total of 797 genes were filtered as DEGs from these ten specimens of GSE35956 with 660 up-regulated genes and 137 down-regulated genes. Meanwhile, up-regulated DEGs were mainly enriched in functions and pathways related to cell cycle and DNA replication. Furthermore, there were 4,135 PPI pairs and 377 nodes in the PPI network. Four modules were enriched in different pathways, including cell cycle and DNA replication pathway in module 2.

Conclusions

In this paper, we explored the genes and pathways involved in primary osteoporosis based on gene expression profiles, and the present findings have the potential to be used clinically for the future treatment of primary osteoporosis.

Role of RANKL (TNFSF11)-dependent osteopetrosis in the dental phenotype of Msx2 null mutant mice

The MSX2 homeoprotein is implicated in all aspects of craniofacial skeletal development. During postnatal growth, MSX2 is expressed in all cells involved in mineralized tissue formation and plays a role in their differentiation and function. Msx2 null (Msx2 (-/-)) mice display complex craniofacial skeleton abnormalities with bone and tooth defects. A moderate form osteopetrotic phenotype is observed, along with decreased expression of RANKL (TNFSF11), the main osteoclast-differentiating factor. In order to elucidate the role of such an osteopetrosis in the Msx2 (-/-) mouse dental phenotype, a bone resorption rescue was performed by mating Msx2 (-/-) mice with a transgenic mouse line overexpressing Rank (Tnfrsf11a). Msx2 (-/-) Rank(Tg) mice had significant improvement in the molar phenotype, while incisor epithelium defects were exacerbated in the enamel area, with formation of massive osteolytic tumors. Although compensation for RANKL loss of function could have potential as a therapy for osteopetrosis, but in Msx2 (-/-) mice, this approach via RANK overexpression in monocyte-derived lineages, amplified latent epithelial tumor development in the peculiar continuously growing incisor.

Characterization of the DNA methylome and its interindividual variation in human peripheral blood monocytes

AIM

Peripheral blood monocytes (PBMs) play multiple and critical roles in the immune response, and abnormalities in PBMs have been linked to a variety of human disorders. However, the DNA methylation landscape in PBMs is largely unknown. In this study, we characterized epigenome-wide DNA methylation profiles in purified PBMs.

MATERIALS & METHODS

PBMs were isolated from freshly collected peripheral blood from 18 unrelated healthy postmenopausal Caucasian females. Epigenome-wide DNA methylation profiles (the methylome) were characterized by using methylated DNA immunoprecipitation combined with high-throughput sequencing.

RESULTS

Distinct patterns were revealed at different genomic features. For instance, promoters were commonly (∼58%) found to be unmethylated; whereas protein coding regions were largely (∼84%) methylated. Although CpG-rich and -poor promoters showed distinct methylation patterns, interestingly, a negative correlation between promoter methylation levels and gene transcription levels was consistently observed across promoters with high to low CpG densities. Importantly, we observed substantial interindividual variation in DNA methylation across the individual PBM methylomes and the pattern of this interindividual variation varied between different genomic features, with highly variable regions enriched for repetitive DNA elements. Furthermore, we observed a modest but significant excess (p < 2.2 × 10(-16)) of genes showing a negative correlation between interindividual promoter methylation and transcription levels. These significant genes were enriched in biological processes that are closely related to PBM functions, suggesting that alteration in DNA methylation is likely to be an important mechanism contributing to the interindividual variation in PBM function, and PBM-related phenotypic and disease-susceptibility variation in humans.

CONCLUSION

This study represents a comprehensive analysis of the human PBM methylome and its interindividual variation. Our data provide a valuable resource for future epigenomic and multiomic studies, exploring biological and disease-related regulatory mechanisms in PBMs.

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.

Systems-level analysis of genome-wide association data

Genome-wide association studies (GWAS) have emerged as the method of choice for identifying common variants affecting complex disease. In a GWAS, particular attention is placed, for obvious reasons, on single-nucleotide polymorphisms (SNPs) that exceed stringent genome-wide significance thresholds. However, it is expected that many SNPs with only nominal evidence of association (e.g., P < 0.05) truly influence disease. Efforts to extract additional biological information from entire GWAS datasets have primarily focused on pathway-enrichment analyses. However, these methods suffer from a number of limitations and typically fail to lead to testable hypotheses. To evaluate alternative approaches, we performed a systems-level analysis of GWAS data using weighted gene coexpression network analysis. A weighted gene coexpression network was generated for 1918 genes harboring SNPs that displayed nominal evidence of association (P ≤ 0.05) from a GWAS of bone mineral density (BMD) using microarray data on circulating monocytes isolated from individuals with extremely low or high BMD. Thirteen distinct gene modules were identified, each comprising coexpressed and highly interconnected GWAS genes. Through the characterization of module content and topology, we illustrate how network analysis can be used to discover disease-associated subnetworks and characterize novel interactions for genes with a known role in the regulation of BMD. In addition, we provide evidence that network metrics can be used as a prioritizing tool when selecting genes and SNPs for replication studies. Our results highlight the advantages of using systems-level strategies to add value to and inform GWAS.

Detection of significant pathways in osteoporosis based on graph clustering

Osteoporosis is the most common and serious skeletal disorder among the elderly, characterized by a low bone mineral density (BMD). Low bone mass in the elderly is highly dependent on their peak bone mass (PBM) as young adults. Circulating monocytes serve as early progenitors of osteoclasts and produce significant molecules for bone metabolism. An improved understanding of the biology and genetics of osteoclast differentiation at the pathway level is likely to be beneficial for the development of novel targeted approaches for osteoporosis. The objective of this study was to explore gene expression profiles comprehensively by grouping individual differentially expressed genes (DEGs) into gene sets and pathways using the graph clustering approach and Gene Ontology (GO) term enrichment analysis. The results indicated that the DEGs between high and low PBM samples were grouped into nine gene sets. The genes in clusters 1 and 8 (including GBP1, STAT1, CXCL10 and EIF2AK2) may be associated with osteoclast differentiation by the immune system response. The genes in clusters 2, 7 and 9 (including SOCS3, SOD2, ATF3, ADM EGR2 and BCL2A1) may be associated with osteoclast differentiation by responses to various stimuli. This study provides a number of candidate genes that warrant further investigation, including DDX60, HERC5, RSAD2, SIGLEC1, CMPK2, MX1, SEPING1, EPSTI1, C9orf72, PHLDA2, PFKFB3, PLEKHG2, ANKRD28, IL1RN and RNF19B.

An integrative study ascertained SOD2 as a susceptibility gene for osteoporosis in Chinese

Osteoporosis is characterized by low BMD and has strong genetic determination. However, specific genetic variants influencing BMD and contributing to the pathogenesis of osteoporosis are largely uncharacterized. Current genetic studies in bone, which are aimed at identification of osteoporosis risk genes, are focused mostly on DNA, RNA, or the protein level individually, lacking integrative evidence 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, ie, potential osteoclast precursors) was significantly upregulated at protein level in vivo in Chinese with low versus high hip BMD. Herein, at mRNA level, we found that SOD2 gene expression also was upregulated in CMCs (p < 0.05) in Chinese with low versus high hip BMD. At the DNA level, in 1627 unrelated Chinese subjects, we identified eight single-nucleotide polymorphisms (SNPs) at the 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 the SOD2 mRNA expression level (p < 0.05), suggesting that they are expression quantitative trait loci (eQTLs) regulating SOD2 gene expression. In conclusion, this integrative evidence from DNA, RNA, and protein levels support SOD2 as a susceptibility gene for osteoporosis.

Effects of intermittent parathyroid hormone treatment on osteoprogenitor cells in postmenopausal women

Intermittent parathyroid hormone (PTH) 1-34 treatment stimulates bone formation, but the molecular mechanisms mediating this effect have not been previously studied in humans. Thus, we used magnetic activated cell sorting to isolate hematopoietic lineage negative (lin-)/alkaline phosphatase positive (AP+) osteoprogenitor cells from bone marrow of 20 postmenopausal women treated with PTH (1-34) for 14 days and 19 control subjects. Serum PINP and CTX increased in PTH-treated subjects (by 97% and 30%, respectively, P<0.001). Bone marrow lin-/AP+ cells from PTH-treated subjects showed an increase in the RANKL/OPG mRNA ratio (by 7.5-fold, P=0.011) and in the mRNAs for c-fos (a known PTH-responsive gene, by 42%, P=0.035) and VEGF-C (by 57%, P=0.046). Gene Set Enrichment Analysis (GSEA, testing for changes in pre-specified pathways) demonstrated that PTH had no effect on osteoblast proliferation, apoptosis, or differentiation markers. However, PTH treatment resulted in a significant decrease (GSEA P-value, 0.005) in a panel of BMP target genes in the lin-/AP+ cells. Our findings thus identify several future directions for studying mechanisms of PTH action in humans. First, given the increasing evidence that PTH induces angiogenesis, the role of increased VEGF-C production by bone marrow osteoprogenitor cells in mediating this effect and the anabolic response to PTH warrants further study. Second, while the observed inhibition of BMP target gene expression by PTH is not consistent with the anabolic effects of PTH on bone and requires further validation, these data do generate the hypothesis that an inhibition of BMP signaling by PTH may, over time, limit the availability of mature osteoblasts on bone surfaces and thereby contribute to the observed waning of the anabolic response to PTH.

Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data

Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD.

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

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

Impact of female cigarette smoking on circulating B cells in vivo: the suppressed ICOSLG, TCF3, and VCAM1 gene functional network may inhibit normal cell function

As pivotal immune guardians, B cells were found to be directly associated with the onset and development of many smoking-induced diseases. However, the in vivo molecular response of B cells underlying the female cigarette smoking remains unknown. Using the genome-wide Affymetrix HG-133A GeneChip microarray, we firstly compared the gene expression profiles of peripheral circulating B cells between 39 smoking and 40 non-smoking healthy US white women. A total of 125 differential expressed genes were identified in our study, and 75.2% of them were down-regulated in smokers. We further obtained genotypes of 702 single nucleotide polymorphisms in those promising genes and assessed their associations with smoking status. Using a novel multicriteria evaluation model integrating information from microarray and the association studies, several genes were further revealed to play important roles in the response of smoking, including ICOSLG (CD275, inducible T-cell co-stimulator ligand), TCF3 (E2A immunoglobulin enhancer binding factors E12/E47), VCAM1 (CD106, vascular cell adhesion molecule 1), CCR1 (CD191, chemokine C-C motif receptor 1) and IL13 (interleukin 13). The differential expression of ICOSLG (p = 0.0130) and TCF3 (p = 0.0125) genes between the two groups were confirmed by real-time reverse transcription PCR experiment. Our findings support the functional importance of the identified genes in response to the smoking stimulus. This is the first in vivo genome-wide expression study on B cells at today's context of high prevalence rate of smoking for women. Our results highlight the potential usage of integrated analyses for unveiling the novel pathogenesis mechanism and emphasized the significance of B cells in the etiology of smoking-induced disease.

Gene expression profiling in monocytes and SNP association suggest the importance of the STAT1 gene for osteoporosis in both Chinese and Caucasians

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.

Genetics of osteoporosis: accelerating pace in gene identification and validation

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