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

A Machine Learning Framework for Screening Plasma Cell-Associated Feature Genes to Estimate Osteoporosis Risk and Treatment Vulnerability

Osteoporosis, in which bones become fragile owing to low bone density and impaired bone mass, is a global public health concern. Bone mineral density (BMD) has been extensively evaluated for the diagnosis of low bone mass and osteoporosis. Circulating monocytes play an indispensable role in bone destruction and remodeling. This work proposed a machine learning-based framework to investigate the impact of circulating monocyte-associated genes on bone loss in osteoporosis patients. Females with discordant BMD levels were included in the GSE56815, GSE7158, GSE7429, and GSE62402 datasets. Circulating monocyte types were quantified via CIBERSORT, with subsequent selection of plasma cell-associated DEGs. Generalized linear models, random forests, extreme gradient boosting (XGB), and support vector machines were adopted for feature selection. Artificial neural networks and nomograms were subsequently constructed for osteoporosis diagnosis, and the molecular machinery underlying the identified genes was explored. SVM outperformed the other tuned models; thus, the expression of several genes (DEFA4, HLA-DPB1, LCN2, HP, and GAS7) associated with osteoporosis were determined. ANNs and nomograms were proposed to robustly distinguish low and high BMDs and estimate the risk of osteoporosis. Clozapine, aspirin, pyridoxine, etc. were identified as possible treatment agents. The expression of these genes is extensively posttranscriptionally regulated by miRNAs and m6A modifications. Additionally, they participate in modulating key signaling pathways, e.g., autophagy. The machine learning framework based on plasma cell-associated feature genes has the potential for estimating personalized risk stratification and treatment vulnerability in osteoporosis patients.

Differential Gene Expression Profiles and Pathways Highlight the Role of Osteoimmunology in Neurofibromatosis Type 1-Related Dystrophic Scoliosis With Osteopenia

STUDY DESIGN

Microarray approach and integrated gene network analysis.

OBJECTIVE

To explore the differential genetic expression profile, Gene Ontology terms, and Kyoto Encyclopedia of Genes and Genomes pathways in human trabecular bone (HTB)-derived cells of dystrophic scoliosis secondary to neurofibromatosis type 1 (DS-NF1) and compare these to normal controls.

SUMMARY OF BACKGROUND DATA

The pathogenesis of DS-NF1 and the accompanying generalized osteopenia remain unclear. We hypothesized that HTBs may play a significant role in the etiology and pathogenesis of DS-NF1.

MATERIALS AND METHODS

Microarray analysis was used to identify differentially expressed genes of HTBs from patients with DS-NF1 compared with those from healthy individuals. Functional and pathway enrichment analysis were implemented through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway database. Then, the "search tool for the retrieval of interacting genes/proteins" database, Cytoscape, and "Molecular Complex Detection" were applied to construct the protein-protein interaction (PPI) network and screen hub genes. Pathway enrichment analysis was further performed for hub genes and gene clusters identified through module analysis. Six potential crucial genes were selected for validation by reverse transcription polymerase chain reaction.

RESULTS

Bioinformatic analysis revealed that there are 401 previously unrecognized differentially expressed genes (238 up and 163 downregulated genes) in HTBs from patients with DS-NF1, and they were mainly enriched in terms of immune response, type-I interferon (IFN) signaling, TNF signaling pathway and etinoic acid inducible gene I-like receptor signaling pathway. Five hub genes, including signal transducer and activator of transcription 1, 2'-5'-oligoadenylate synthetase-like, IFN induced with helicase C domain 1, IFN regulatory factor 7, and MX dynamin-like GTPase 1 were identified through PPI network, which were mainly enriched in terms of Jak-STAT and etinoic acid inducible gene I-like receptor signaling pathway. An independently dysregulated protein cluster containing CCL2, CXCL1, CXCL3, CX3CL1, TLR1 , and CXCL12 was also identified through the PPI network. This indicated that the upper abnormally expressed genes may play essential roles in DS-NF1 pathogenesis and accompanied osteopenia.

CONCLUSION

Six key genes were identified in the progression of DS-NF1-related osteopenia. Immune response might play a key role in the progression of osteopenia, whereas a CXCL12 -mediated osteogenic effect might play a protective role.

Identifying a causal link between prolactin signaling pathways and COVID-19 vaccine-induced menstrual changes

COVID-19 vaccines have been instrumental tools in the fight against SARS-CoV-2 helping to reduce disease severity and mortality. At the same time, just like any other therapeutic, COVID-19 vaccines were associated with adverse events. Women have reported menstrual cycle irregularity after receiving COVID-19 vaccines, and this led to renewed fears concerning COVID-19 vaccines and their effects on fertility. Herein we devised an informatics workflow to explore the causal drivers of menstrual cycle irregularity in response to vaccination with mRNA COVID-19 vaccine BNT162b2. Our methods relied on gene expression analysis in response to vaccination, followed by network biology analysis to derive testable hypotheses regarding the causal links between BNT162b2 and menstrual cycle irregularity. Five high-confidence transcription factors were identified as causal drivers of BNT162b2-induced menstrual irregularity, namely: IRF1, STAT1, RelA (p65 NF-kB subunit), STAT2 and IRF3. Furthermore, some biomarkers of menstrual irregularity, including TNF, IL6R, IL6ST, LIF, BIRC3, FGF2, ARHGDIB, RPS3, RHOU, MIF, were identified as topological genes and predicted as causal drivers of menstrual irregularity. Our network-based mechanism reconstruction results indicated that BNT162b2 exerted biological effects similar to those resulting from prolactin signaling. However, these effects were short-lived and didn't raise concerns about long-term infertility issues. This approach can be applied to interrogate the functional links between drugs/vaccines and other side effects.

Comparisons of gene expression between peripheral blood mononuclear cells and bone tissue in osteoporosis

Osteoporosis (OP) is one of the major public health problems in the world. However, the biomarkers between the peripheral blood mononuclear cells (PBMs) and bone tissue for prognosis of OP have not been well characterized. This study aimed to explore the similarities and differences of the gene expression profiles between the PBMs and bone tissue and identify potential genes, transcription factors (TFs) and hub proteins involved in OP. The patients were enrolled as an experimental group, and healthy subjects served as normal controls. Human whole-genome expression chips were used to analyze gene expression profiles from PBMs and bone tissue. And the differentially expressed genes (DEGs) were subsequently studied using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. The above DEGs were constructed into protein-protein interaction network. Finally, TF-DEGs regulation networks were constructed. Microarray analysis revealed that 226 DEGs were identified between OP and normal controls in the PBMs, while 2295 DEGs were identified in the bone tissue. And 13 common DEGs were obtained by comparing the 2 tissues. The Gene Ontology analysis indicated that DEGs in the PBMs were more involved in immune response, while DEGs in bone were more involved in renal response and urea transmembrane transport. And the Kyoto Encyclopedia of Genes and Genomes analysis indicated almost all of the pathways in the PBMs were overlapped with those in the bone tissue. Furthermore, protein-protein interaction network presented 6 hub proteins: PI3K1, APP, GNB5, FPR2, GNG13, and PLCG1. APP has been found to be associated with OP. Finally, 5 key TFs were identified by TF-DEGs regulation networks analysis (CREB1, RUNX1, STAT3, CREBBP, and GLI1) and were supposed to be associated with OP. This study enhanced our understanding of the pathogenesis of OP. PI3K1, GNB5, FPR2, GNG13, and PLCG1 might be the potential targets of OP.

Gene set analysis of transcriptomics data identifies new biological processes associated with early markers of atherosclerosis but not with those of osteoporosis: Atherosclerosis-osteoporosis co/multimorbidity study in the Young Finns Study

AIM

We aimed at identifying the shared biological processes underlying atherosclerosis-osteoporosis co/multimorbidity.

METHODS

We performed gene set analysis (GSA) of whole-blood transcriptomic data to identify biological processes shared by the early markers of these two diseases. Early markers of diseases, carotid intima-media thickness (CIMT) for atherosclerosis and trabecular bone mineral density (BMD) from distal radius and tibia for osteoporosis, were used to categorize the study participants into cases and controls. Participants with high CIMT (>90th percentile) were defined as cases for subclinical atherosclerosis. Study population-based T-scores for BMD were calculated and T-score ≤ -1 was used for the definition of low BMD cases i.e., early indicator of osteoporosis.

RESULTS

We did not identify any gene sets jointly associated with early markers of atherosclerosis and osteoporosis. We identified three novel and replicated 234 gene sets significantly associated with high CIMT with false discovery rate (FDR) ≤ 0.01. Only two genes, both related to the immune system, were identified to be associated with high CIMT by traditional differential gene expression analysis. However, none of the studied gene sets or individual genes were significantly associated with tibial or radial BMD. The three novel CIMT associated gene sets contained genes involved in copper homeostasis, neural crest cell migration and nicotinate and nicotinamide metabolism. The 234 replicated gene sets in this study are related to the immune system, hypoxia and apoptosis, consistent with the existing literature on atherosclerosis.

CONCLUSIONS

This study identified novel biological processes associated with high CIMT but not with reduced BMD.

STAT1 and CXCL10 involve in M1 macrophage polarization that may affect osteolysis and bone remodeling in extrapulmonary tuberculosis

OBJECTIVE

This study was aimed to reveal the molecular mechanism of bone destruction due to macrophage polarization leading to during extrapulmonary tuberculosis (EPTB) infection.

METHODS

The dataset GSE83456 was downloaded from the GEO database, and the xCell tool was used to obtain the 64 types of immune cells. The flow cytometry was performed to identified the differences between M1 and M2 macrophages between EPTB and the healthy controls (HCs). The enrichment analyses were performed on the differentially expressed genes (DEGs) and their functionally related modules. The hub genes were screened out, and their relationships with EPTB and the immune cell subtypes were further analyzed.

RESULTS

The flow cytometric analysis validated this hypothesis of M1-macrophage polarization correlated with the pathogenesis of EPTB. Of the obtained 103 DEGs, 97 genes were upregulated, and 6 genes were downregulated. The GO and KEGG pathway analyses showed that the DEGs were particularly involved in the immune-related processes. The hub genes (STAT1 and CXCL10) might be involved in M1-macrophage polarization and correlated with the pathogenesis of EPTB. STAT1 and CXCL10 could also behave as biomarkers for EPTB.

CONCLUSION

STAT1 and CXCL10 were involved in the M1-macrophage polarization and correlated with the pathogenesis of EPTB. Besides, both of them could also behave as biomarkers for EPTB diagnosis and provide the required clues for targeted therapy in the future.

Associations between osteoporosis and drug exposure: A post-marketing study of the World Health Organization pharmacovigilance database (VigiBase®)

BACKGROUND

Bone remodeling is a complex process, and many conditions (including drug exposure) lead to osteoporosis. Here, we sought to detect new disproportionality signals for drugs associated with osteoporosis.

METHODS

We performed a disproportionality analysis of the World Health Organization's VigiBase® pharmacovigilance database through April 12, 2020. The frequency of reports on osteoporosis for all identified drug classes was compared with that for all other drugs and quoted as the reporting odds ratio (ROR) [95% confidence interval (CI)].

RESULTS

Of the 7,594,968 cases spontaneously recorded to VigiBase®, 4758 concerned osteoporosis. New disproportionality signals with a pharmacologically plausible mechanism were found for drugs used in neurology (levodopa (ROR [95%CI]: 10.18 [4.33-25.10]), selective serotonin agonists (4.22 [2.34-7.00]) and memantine (4.10 [1.56-8.93])), hematology (romiplostim (4.93 [1.15-21.10])), pulmonology (macitentan (3.02 [1.84-4.90])), ophthalmology (ranibizumab (3.31 [1.00-10.51])) and rheumatology (tofacitinib (3.65 [3.00-4.40])). The robustness of these new results is supported by the significant RORs for the vast majority of drugs already known to induce osteoporosis and/or increase the fracture risk, namely glucocorticoids, gonadotropin-releasing hormone analogs, anti-aromatases, androgen receptor blockers, thyroid hormones, proton pump inhibitors, thiazolidinediones, vitamin K antagonists, loop diuretics, protease inhibitors, nucleoside and nucleotide reverse transcriptase inhibitors, and enzyme-inducing antiepileptics including barbiturates and derivatives, hydantoin derivatives, carboxamide derivatives and fatty acid derivatives.

CONCLUSION

We established up a comprehensive list of drugs potentially associated with osteoporosis and highlighted those with pharmacologically plausible mechanisms leading to bone fragility. Our results might pave the way for additional exploration of these mechanisms.

Immunoporosis: Role of Innate Immune Cells in Osteoporosis

Osteoporosis or porous bone disorder is the result of an imbalance in an otherwise highly balanced physiological process known as 'bone remodeling'. The immune system is intricately involved in bone physiology as well as pathologies. Inflammatory diseases are often correlated with osteoporosis. Inflammatory mediators such as reactive oxygen species (ROS), and pro-inflammatory cytokines and chemokines directly or indirectly act on the bone cells and play a role in the pathogenesis of osteoporosis. Recently, Srivastava et al. (Srivastava RK, Dar HY, Mishra PK. Immunoporosis: Immunology of Osteoporosis-Role of T Cells. Frontiers in immunology. 2018;9:657) have coined the term "immunoporosis" to emphasize the role of immune cells in the pathology of osteoporosis. Accumulated pieces of evidence suggest both innate and adaptive immune cells contribute to osteoporosis. However, innate cells are the major effectors of inflammation. They sense various triggers to inflammation such as pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), cellular stress, etc., thus producing pro-inflammatory mediators that play a critical role in the pathogenesis of osteoporosis. In this review, we have discussed the role of the innate immune cells in great detail and divided these cells into different sections in a systemic manner. In the beginning, we talked about cells of the myeloid lineage, including macrophages, monocytes, and dendritic cells. This group of cells explicitly influences the skeletal system by the action of production of pro-inflammatory cytokines and can transdifferentiate into osteoclast. Other cells of the myeloid lineage, such as neutrophils, eosinophils, and mast cells, largely impact osteoporosis via the production of pro-inflammatory cytokines. Further, we talked about the cells of the lymphoid lineage, including natural killer cells and innate lymphoid cells, which share innate-like properties and play a role in osteoporosis. In addition to various innate immune cells, we also discussed the impact of classical pro-inflammatory cytokines on osteoporosis. We also highlighted the studies regarding the impact of physiological and metabolic changes in the body, which results in chronic inflammatory conditions such as ageing, ultimately triggering osteoporosis.

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.

Do We Use Methylation of NFATC1 and FOS Genes As a Biomarker for Postmenopausal Osteoporosis?

Genetic and epigenetic factors have an important role during the development of osteoporosis. Receptor activator of nuclear factor-κ B (NF-κB) (RANK)/receptor activator of NF-κB ligand (RANKL) pathway is important for the bone remodeling, and NFATC1 and FOS are the downtargets of this pathway. Here, we report methylation status of NFATC1 and FOS genes in post- and premenopausal women. In this study, 30 premenopausal and 35 postmenopausal women were included. Methylation sensitive-high resolution melting (MS-HRM) analysis was used for identification of NFATC1 and FOS genes methylation. The NFATC1 gene was methylated in 11 of the 35 postmenopausal women, and the FOS gene was methylated in six of the postmenopausal women (p >0.005). Here, we found statistically significant association between unmethylation of the NFATC1 gene and postmenopausal status. This result explains the epigenetic regulation of osteoclasts during the menopausal transition, and for the first time, our results can be used for epigenetic explanation of postmenopausal osteoporosis in the literature. However, the limited number of studies in this field makes our results crucial. Our results showed great value of epigenetic profiles of postmenopausal women.

Modular genome-wide gene expression architecture shared by early traits of osteoporosis and atherosclerosis in the Young Finns Study

We analysed whole blood genome-wide expression data to identify gene co-expression modules shared by early traits of osteoporosis and atherosclerosis. Gene expression was profiled for the Young Finns Study participants. Bone mineral density and content were measured as early traits of osteoporosis. Carotid and bulbus intima media thickness were measured as early traits of atherosclerosis. Joint association of the modules, identified with weighted co-expression analysis, with early traits of the diseases was tested with multivariate analysis. Among the six modules significantly correlated with early traits of both the diseases, two had significant (adjusted p-values (p.adj) < 0.05) and another two had suggestively significant (p.adj < 0.25) joint association with the two diseases after adjusting for age, sex, body mass index, smoking habit, alcohol consumption, and physical activity. The three most significant member genes from the significant modules were NOSIP, GXYLT2, and TRIM63 (p.adj ≤ 0.18). Genes in the modules were enriched with biological processes that have separately been found to be involved in either bone metabolism or atherosclerosis. The gene modules and their most significant member genes identified in this study support the osteoporosis-atherosclerosis comorbidity hypothesis and can provide new joint biomarkers for both diseases and their dual prevention.

microRNA-935-modified bone marrow mesenchymal stem cells-derived exosomes enhance osteoblast proliferation and differentiation in osteoporotic rats

AIMS

The involvement of several microRNAs (miRNAs) in osteogenic differentiation has been indicated recently. Also, exosomes, derived from different cells, could shuttle specific miRNAs to other cell systems. Nevertheless, the effect and mechanism of microRNA-935 (miR-935)-containing exosomes in osteoblasts remain basically unclear. The current work was set to inspect the relevance of bone marrow mesenchymal stem cells (BMSCs)-derived exosomes (BMSC-exo) carrying miR-935 to osteoporotic rats.

METHODS

The extracted BMSCs and purchased osteoblasts were cultured, followed by exosome isolation and identification. After cell grouping, osteoblasts were co-cultured with BMSCs. CCK-8, alizarin red staining as well as ALP staining were performed to detect osteoblast proliferation and activity. The binding connection between miR-935 and signal transducer and activator of transcription 1 (STAT1) was measured by dual-luciferase reporter gene assays. The expression profiles of miR-935, STAT1 and osteoblast-related proteins were assessed by RT-qPCR and Western blot. A rat model with osteoporosis was induced, and the BMD, BV/TV, Tb.N, Tb.Th and Tb.Sp values in rat bone tissues were observed by Micro-CT.

RESULTS

BMSC-exo inhibited STAT1 levels by the delivery of miR-935 into osteoblasts, while STAT1 silencing promoted ALP activity in osteoblasts and mineralized nodules. STAT1 was identified as a target gene of miR-935. Moreover, in vivo experiments showed that in ovariectomized rats, silencing of miR-935 significantly reduced BMD, BV/TV, Tb.N, Tb.Th and increased Tb.Sp.

CONCLUSION

BMSC-exo carry miR-935 to promote osteoblast proliferation and differentiation through targeting STAT1.

A correlative studies between osteoporosis and blood cell composition: Implications for auxiliary diagnosis of osteoporosis

Osteoporosis is defined as a metabolic skeletal disease characterized by a decrease of the bone mass per unit volume, caused by a variety of reasons. Increasing evidence indicate that the host inflammatory response was correlated with the occurrence and development of osteoporosis, and it has been recognized that T lymphocytes and B lymphocytes play a critical role in pathogenesis of inflammatory bone disease. Between January 2018 and December 2018, retrospective analysis of 487 patients (exclusion of patients with recent infections and hematologic disorders whose leukocyte counts or classifications are markedly abnormal) who underwent bone mineral density (BMD) examinations in Huzhou Central Hospital. The patients were divided into normal bone density group, osteopenia group, and osteoporosis group according to the T score of BMD in the left femoral neck, respectively. Statistics of the lymphocyte ratio and the monocyte ratio in the blood routine examination results during the same period were performed so as to make a comparison of the differences among the groups. The correlation of the lymphocyte ratio and monocyte ratio with the T score of BMD in the left femoral neck was also analyzed. The difference between neutrocyte ratio lymphocyte ratio and the monocyte ratio was statistically significant in both males and females among the normal bone density group, osteopenia group and osteoporosis group (P < .01 or P < .05). Inflammation plays an important role in the progression of osteoporosis. By monitoring these three indicators in blood routine examination, early intervention for osteoporosis may become possible.

Evaluating the Correlations Between Osteoporosis and Lifestyle-Related Factors Using Transcriptome-Wide Association Study

Osteoporosis (OP) is a multi-factorial bone disease influenced by genetic factors, age, and lifestyles. The aim of this study is to evaluate the genetic correlations between OP and multiple lifestyle-related factors, and explore the genes underlying the detected genetic correlations. Linkage disequilibrium score regression (LDSC) analysis was applied to evaluate the genetic correlations of total body bone mineral density (TB-BMD) of different ages (including 15-30 years, 30-45 years, 45-60 years, and over 60 years) with four common lifestyle/environment-related factors (including serum 25-hydroxyvitamin D, cigarette smoking, alcohol dependence, and caffeine metabolites). Transcriptome-wide association studies (TWAS) of TB-BMD (30-45 years) and smoking were conducted in peripheral blood (PB), whole blood (WB), and adipose tissues. The identified candidate genes were also subjected to gene set enrichment analysis (GSEA). Genetic correlation was only observed between TB-BMD (30-45 years) and cigarette smoking status (P = 0.01, LD score = 0.11 ± 0.04). No significant genetic correlation was detected for other lifestyle/environmental factors, including serum 25-hydroxyvitamin D, alcohol dependence, and caffeine metabolites for TB-BMD within all of the four age groups. TWAS identified 85 genes in PB and 163 genes in WB for TB-BMD, as well as 123 genes in PB and 257 genes in WB for smoking. Multiple common candidate genes shared by both TB-BMD and smoking were detected, such as MAP1LC3B (P_TB-BMD-PB = 1.00 × 10^-3, P_smoking-PB = 9.62 × 10^-3, P_TB-BMD-WB = 2.99 × 10^-2) and SLC23A3 (P_TB-BMD-WB = 1.48 × 10^-2, P_smoking-WB = 8.76 × 10^-3). GSEA detected one GO terms for TB-BMD (cytosol) in WB, one GO term for smoking (mitochondrion) in PB, and one pathway (oocyte meiosis) for smoking in WB.

A trans-ethnic two-stage polygenetic scoring analysis detects genetic correlation between osteoporosis and schizophrenia

BACKGROUNDS

To explore the genetic correlation between schizophrenia (SCZ) and osteoporosis (OP).

DESIGN, SETTING, PARTICIPANTS, MEASUREMENTS

We conducted a trans-ethnic two-stage genetic correlation analysis of OP and SCZ, totally invoking 2286 Caucasia subjects in discovery stage and 4124 Chinese subjects in replication stage. The bone mineral density (BMD) and bone area values of ulna & radius, hip and spine were measured using Hologic 4500W dual energy X-ray absorptiometry machine. SCZ was diagnosed according to DSM-IV criteria. For the genome-wide association study (GWAS) of Caucasian OP, Chinese OP and Chinese SCZ, SNP genotyping was performed using Affymetrix SNP 6.0 array. For the GWAS of Caucasian SCZ, SNP genotyping was conducted using the Affymetrix 5.0 array, Affymetrix 6.0 array and Illumina 550 K array. Polygenetic risk scoring (PRS) analysis was conducted by PRSice software. Also, Linkage disequilibrium score regression (LD Score regression) analysis was performed to evaluate the genetic correlation between OP and SCZ. Multi-trait analysis of GWAS (MTAG) was performed to detect novel candidate genes for osteoporosis and SCZ.

RESULTS

In the Caucasia discovery samples, significant genetic correlations were observed for ulna & radius BMD vs. SCZ (P value = 0.010), ulna & radius area vs. SCZ (P value = 0.031). In the Chinese replication samples, we observed significant correlation for ulna & radius area vs. SCZ (P value = 0.019). In addition, LD Score regression also identified significant genetic correlations between SCZ and bone phenotypes in Caucasian and Chinese sample respectively. MTAG analysis identified several novel candidate genes, such as CTNNA2 (MTAG P value = 2.24 × 10-6) for SCZ and FADS2 (MTAG P value = 2.66 × 10-7) for osteoporosis.

CONCLUSIONS

Our study results support the overlapped genetic basis for osteoporosis and SCZ, and provide novel clues for elucidating the biological mechanism of increased osteoporosis risk in SCZ patients.

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.

EPS-LASSO: test for high-dimensional regression under extreme phenotype sampling of continuous traits

Motivation

Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g. the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown.

Results

We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors.

Availability and implementation

The source code is available at https://github.com/xu1912/EPSLASSO.

Supplementary information

Supplementary data are available at Bioinformatics online.

Osteoporosis in Rheumatic Diseases: Anti-rheumatic Drugs and the Skeleton

Osteoporosis in rheumatic diseases is a very well-known complication. Systemic inflammation results in both generalized and localized bone loss and erosions. Recently, increased knowledge of inflammatory process in rheumatic diseases has resulted in the development of potent inhibitors of the cytokines, the biologic DMARDs. These treatments reduce systemic inflammation and have some effect on the generalized and localized bone loss. Progression of bone erosion was slowed by TNF, IL-6 and IL-1 inhibitors, a JAK inhibitor, a CTLA4 agonist, and rituximab. Effects on bone mineral density varied between the biological DMARDs. Medications that are approved for the treatment of osteoporosis have been evaluated to prevent bone loss in rheumatic disease patients, including denosumab, cathepsin K, bisphosphonates, anti-sclerostin antibodies and parathyroid hormone (hPTH 1-34), and have some efficacy in both the prevention of systemic bone loss and reducing localized bone erosions. This article reviews the effects of biologic DMARDs on bone mass and erosions in patients with rheumatic diseases and trials of anti-osteoporotic medications in animal models and patients with rheumatic diseases.

"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.

Alendronate promotes osteoblast differentiation and bone formation in ovariectomy-induced osteoporosis through interferon-β/signal transducer and activator of transcription 1 pathway

Alendronate is commonly used for the treatment of postmenopausal osteoporosis; however, the underlying pathological molecular mechanisms of its action remain unclear. In the present study, the alendronate-treated signaling pathway in bone metabolism in rats with ovariectomy induced by osteoporosis was investigated. Rats with osteoporosis were orally administered alendronate or phosphate-buffered saline (control). In addition, the interferon-β (IFN-β)/signal transducer and activator of transcription 1 (STAT1) signaling pathway was investigated in osteoblasts following treatment with alendronate in vitro and in vivo. During the differentiation period, IFN-β (100 ng/ml) was used to treat the osteoblast cells, and the activity, viability and bone metabolism-associated gene expression levels (STAT1, p-STAT1, Fra1, TRAF6 and SOCS1) were analyzed in osteoblast cells. Histopathological changes were used to evaluate osteoblasts, osteoclasts, inflammatory phase of bone healing and osteonecrotic areas. The results demonstrated that alendronate significantly inhibited the activity of osteoporotic osteoclasts by stimulating expression of IFN-β, as well as markedly improved the viability and activity of osteoblasts compared with the control group. In addition, alendronate increased the expression and phosphorylation levels of STAT1 in osteoclasts, enhanced osteoblast differentiation, upregulated the expression levels of alkaline phosphatase and osteocalcin, and increased the expression of osteoblast differentiation-associated genes (osteocalcin, osterix and Runx2). Inhibition of IFN-β expression canceled the benefits of alendronate-mediated osteoblast differentiation. Notably, alendronate enhanced bone formation in rats with osteoporosis induced by ovariectomy. In conclusion, these findings suggest that alendronate can regulate osteoblast differentiation and bone formation in rats with osteoporosis induced by ovariectomy through upregulation of IFN-β/STAT1 signaling pathway.

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.

The Role of Monocyte Percentage in Osteoporosis in Male Rheumatic Diseases

Osteoporosis is easily overlooked in male patients, especially in the field of rheumatic diseases mostly prevalent with female patients, and its link to pathogenesis is still lacking. Attenuated monocyte apoptosis from a transcriptome-wide expression study illustrates the role of monocytes in osteoporosis. This study tested the hypothesis that the monocyte percentage among leukocytes could be a biomarker of osteoporosis in rheumatic diseases. Eighty-seven males with rheumatic diseases were evaluated in rheumatology outpatient clinics for bone mineral density (BMD) and surrogate markers, such as routine peripheral blood parameters and autoantibodies. From the total number of 87 patients included in this study, only 15 met the criteria for diagnosis of osteoporosis. Both age and monocyte percentage remained independently associated with the presence of osteoporosis. Steroid dose (equivalent prednisolone dose) was negatively associated with BMD of the hip area and platelet counts were negatively associated with BMD and T score of the spine area. Besides age, monocyte percentage meets the major requirements for osteoporosis in male rheumatic diseases. A higher monocyte percentage in male rheumatic disease patients, aged over 50 years in this study, and BMD study should be considered in order to reduce the risk of osteoporosis-related fractures.

P4 medicine and osteoporosis: a systematic review

BACKGROUND

Osteoporosis is the most frequent bone metabolic disease. In order to improve early detection, prediction, prevention, diagnosis, and treatment of the disease, a new model of P4 medicine (personalized, predictive, preventive, and participatory medicine) could be applied. The aim of this work was to systematically review the publications of four different types of "omics" studies related to osteoporosis, in order to discover novel predictive, preventive, diagnostic, and therapeutic targets for better management of the geriatric population.

METHODS

To systematically search the PubMed database, we created specific groups of criteria for four different types of "omics" information on osteoporosis: genomic, transcriptomic, proteomic, and metabolomic. We then analyzed the intersections between them in order to find correlations and common pathways or molecules with important roles in osteoporosis, and with a potential application in disease prediction, prevention, diagnosis, or treatment.

RESULTS

Altogether, 180 publications of "omics" studies in the field of osteoporosis were found and reviewed at first selection. After introducing the inclusion and exclusion criteria (the secondary selection), 46 papers were included in the systematic review.

CONCLUSIONS

The intersection of reviewed papers identified five genes (ESR1, IBSP, CTNNB1, SOX4, and IDUA) and processes like the Wnt pathway, JAK/STAT signaling, and ERK/MAPK, which should be further validated for their predictive, diagnostic, or other clinical value in osteoporosis. Such molecular insights will enable us to fit osteoporosis into the P4 strategy and could increase the effectiveness of disease prediction and prevention, with a decrease in morbidity in the geriatric population.

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.

Long non-coding RNA-DANCR in human circulating monocytes: a potential biomarker associated with postmenopausal osteoporosis

Osteoporosis is a common disease characterized by low bone mineral density (BMD) and low trauma fractures, mainly resulting from exceeding bone resorption by osteoclasts over bone formation by osteoblasts. Circulating monocytes are directly involved in osteoclastogenesis, and lncRNAs are believed to be involved in the osteoblast differentiation. However, no study has been conducted to identify the roles of lncRNA in circulating monocytes associated with human osteoporosis. In this study, we found significant upregulation of DANCR in the blood mononuclear cells (MNCs) from low-BMD patients with the qRT-PCR analyses. We further found that DANCR promoted the expression of IL6 and TNF-α at both mRNA level and protein level in MNCs. After deletion of DANCR with siRNAs, the levels of IL6 and TNF-α are decreased in the MNCs from low-BMD postmenopausal women. Moreover, DANCR level was correlated with IL6 and TNF-α in postmenopausal women with low BMD. Furthermore, we found that DANCR-induced IL6 and TNF-α in MNCs had bone-resorbing activity. These results indicate that DANCR is involved in the pathology of osteoporosis and may be as a biomarker for postmenopausal 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.

Signaling pathway STAT1 is strongly activated by IFN-β in the pathogenesis of osteoporosis

Background

Despite extensive research, the underlying pathological mechanisms of osteoporosis are not completely understood. Recent studies have indicated a distinct role for the IFN-β/STAT1 pathway in bone metabolism. An inhibitory effect of IFN-β on osteoclastogenesis has been detected and STAT1/2 has been shown to influence osteoblastic bone metabolism. So far, no data concerning the IFN-β/STAT1 pathways in osteoblasts and osteoclasts from osteoporotic and non-osteoporotic patients are available. The aim of the study was to analyze these pathways in both cell types.

Methods

Osteoblasts were isolated from the femoral heads of 12 osteoporotic and 11 non-osteoporotic patients and monocytes were differentiated into osteoclasts. After the differentiation period, cells were stimulated once with 20 and 100 ng/mL IFN-β for 4 days. Viability, activity, bone metabolism-related genes, and the proteins Fra1, SOCS1, STAT1, p-STAT1, and TRAF6 were analyzed.

Results

Viability, activity, and gene expressions were not affected by stimulating the osteoblasts. However, in osteoporotic osteoclasts, which display a significantly higher basal osteoclastic activity, the stimulation with IFN-β lead to significant inhibition. Further, an increased STAT1 activation was detected in both cell types with no significant differences between the groups. Regarding the phosphorylation of STAT1, no significant influence was detected in osteoblasts but the IFN-β stimulation led to a significant increase of p-STAT1 in osteoclasts of both groups.

Conclusions

IFN-β is a principal mediator in the pathogenesis of osteoporosis by inhibiting osteoclasts and inducing and activating STAT1. Our results also confirm this in cells from osteoporotic and non-osteoporotic patients. Strong inhibitory effects on the osteoclastogenesis of osteoporotic osteoclasts were detectable. Nevertheless, osteoblast activity was not negatively affected by IFN-β stimulation. These results may contribute to a better understanding of the underlying pathological signaling pathways of osteoporosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s40001-014-0074-4) contains supplementary material, which is available to authorized users.

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.

Key genes associated with osteoporosis revealed by genome wide gene expression analysis

Gene expression profiles of circulating monocytes were analyzed to identify key genes associated with osteoporosis. Raw microarray data were downloaded from gene expression omnibus under accession number GSE7158, including 8 microarray dataset for patients with high peak bone mass (PBM) and 8 for low PBM. Package linear models for microarray data of R was adopted to screen out differentially expressed genes (DEGs). Gene ontology enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed with plug-ins of cytoscape. Protein-protein interaction network was constructed using FunCoup. A total of 283 DEGs were identified in low-PBM group, including 135 up- and 148 down-regulated genes. A considerable part of DEGs were localized in plasma membrane. Several ion transport-related pathways were revealed, such as mineral absorption and carbohydrate digestion and absorption. A range of DEGs were identified and some of them were related to calcium transport as well as osteoporosis. These findings are helpful in disclosing the pathogenetic mechanisms of osteoporosis.

MiR-422a as a potential cellular microRNA biomarker for postmenopausal osteoporosis

Background

MicroRNAs (miRNAs) are a class of short non-coding RNA molecules that regulate gene expression by targeting mRNAs. Recently, miRNAs have been shown to play important roles in the etiology of various diseases. However, little is known about their roles in the development of osteoporosis. Circulating monocytes are osteoclast precursors that also produce various factors important for osteoclastogenesis. Previously, we have identified a potential biomarker miR-133a in circulating monocytes for postmenopausal osteoporosis. In this study, we aimed to further identify significant miRNA biomarkers in human circulating monocytes underlying postmenopausal osteoporosis.

Methodology/Principal Findings

We used ABI TaqMan miRNA array followed by qRT-PCR validation in human circulating monocytes from 10 high BMD and 10 low BMD postmenopausal Caucasian women to identify miRNA biomarkers. MiR-422a was up-regulated with marginal significance (P = 0.065) in the low compared with the high BMD group in the array analysis. However, a significant up-regulation of miR-422a was identified in the low BMD group by qRT-PCR analysis (P = 0.029). We also performed bioinformatic target gene analysis and found several potential target genes of miR-422a which are involved in osteoclastogenesis. Further qRT-PCR analyses of the target genes in the same study subjects showed that the expression of five of these genes (CBL, CD226, IGF1, PAG1, and TOB2) correlated negatively with miR-422a expression.

Conclusions/Significance

Our study suggests that miR-422a in human circulating monocytes (osteoclast precursors) is a potential miRNA biomarker underlying postmenopausal osteoporosis.

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.

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.

MiR-133a in human circulating monocytes: a potential biomarker associated with postmenopausal osteoporosis

Background

Osteoporosis mainly occurs in postmenopausal women, which is characterized by low bone mineral density (BMD) due to unbalanced bone resorption by osteoclasts and formation by osteoblasts. Circulating monocytes play important roles in osteoclastogenesis by acting as osteoclast precursors and secreting osteoclastogenic factors, such as IL-1, IL-6 and TNF-α. MicroRNAs (miRNAs) have been implicated as important biomarkers in various diseases. The present study aimed to find significant miRNA biomarkers in human circulating monocytes underlying postmenopausal osteoporosis.

Methodology/Principal Findings

We used ABI TaqMan® miRNA array followed by qRT-PCR validation in circulating monocytes to identify miRNA biomarkers in 10 high and 10 low BMD postmenopausal Caucasian women. MiR-133a was upregulated (P=0.007) in the low compared with the high BMD groups in the array analyses, which was also validated by qRT-PCR (P=0.044). We performed bioinformatic target gene analysis and found three potential osteoclast-related target genes, CXCL11, CXCR3 and SLC39A1. In addition, we performed Pearson correlation analyses between the expression levels of miR-133a and the three potential target genes in the 20 postmenopausal women. We did find negative correlations between miR-133a and all the three genes though not significant.

Conclusions/Significance

This is the first in vivo miRNA expression analysis in human circulating monocytes to identify novel miRNA biomarkers underlying postmenopausal osteoporosis. Our results suggest that miR-133a in circulating monocytes is a potential biomarker for postmenopausal osteoporosis.

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.

Pharmacogenetics of osteoporosis-related bone fractures: moving towards the harmonization and validation of polymorphism diagnostic tools

Osteoporosis is one of the most common skeletal chronic conditions in developed countries, hip fracture being one of its major healthcare outcomes. There is considerable variation in the implementation of current pharmacological treatment and prevention, despite consistent recommendations and guidelines. Many studies have reported conflicting findings of genetic associations with bone density and turnover that might predict fracture risk. Moreover, it is not clear whether genetic differences exist in relation to the morbidity and efficiency of the pharmacotherapy treatments. Clinical response, including beneficial and adverse events associated with osteoporosis treatments, is highly variable among individuals. In this context, the present article intends to summarize putative candidate genes and genome-wide association studies that have been related with BMD and fracture risk, and to draw the attention to the need for pharmacogenetic methodology that could be applicable in clinical translational research after an adequate validation process. This article mainly compiles analysis of important polymorphisms in osteoporosis documented previously, and it describes the simple molecular biology tools for routine genotype acquisition. Validation of methods for the easy, fast and accessible identification of SNPs is necessary for evolving pharmacogenetic diagnostic tools in order to contribute to the discovery of clinically relevant genetic variation with an impact on osteoporosis and its personalized treatment.

BMD regulation on mouse distal chromosome 1, candidate genes, and response to ovariectomy or dietary fat

The distal end of mouse chromosome 1 (Chr 1) harbors quantitative trait loci (QTLs) that regulate bone mineral density (BMD) and share conserved synteny with human chromosome 1q. The objective of this article was to map this mouse distal Chr 1 region and identify gene(s) responsible for BMD regulation in females. We used X-ray densitometry [ie, dual-energy X-ray Absorptiometry (DXA), micro-computed tomography (µCT), and peripheral quantitative computed tomography (pQCT)] to phenotype a set of nested congenic strains constructed from C57BL/6BmJ (B6/Bm) and C3H/HeJ (C3H) mice to map the region associated with the BMD QTL. The critical region has been reduced to an interval of 0.152 Mb that contributes to increased BMD when C3H alleles are present. Histomorphometry and osteoblast cultures indicated that increased osteoblast activity was associated with increased BMD in mouse strains with C3H alleles in this critical region. This region contains two genes, Aim2, which binds with cytoplasmic dsDNA and results in apoptosis, and AC084073.22, a predicted gene of unknown function. Ovariectomy induced bone loss in the B6/Bm progenitor and the three congenic strains regardless of the alleles present in the critical BMD region. High dietary fat treatment (thought to suppress distal Chr 1 QTL for BMD in mice) did not induce bone loss in the congenics carrying C3H alleles in the critical 0.152 Mb carrying the AIM2 and AC084073.22 genes. Gene expression studies in whole bone of key congenics showed differential expression of AC084073.22 for strains carrying B6/Bm versus C3H alleles but not for Aim2. In conclusion, our data suggest that osteoblasts are the cellular target of gene action and that AC084073.22 is the best candidate for female BMD regulation in the distal region of mouse Chr 1.

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.

Genetic determinants of osteoporosis: common bases to cardiovascular diseases?

Osteoporosis is the most common and serious age-related skeletal disorder, characterized by a low bone mass and bone microarchitectural deterioration, with a consequent increase in bone fragility and susceptibility to spontaneous fractures, and it represents a major worldwide health care problem with important implications for health care costs, morbidity and mortality. Today is well accepted that osteoporosis is a multifactorial disorder caused by the interaction between environment and genes that singularly exert modest effects on bone mass and other aspects of bone strength and fracture risk. The individuation of genetic factors responsible for osteoporosis predisposition and development is fundamental for the disease prevention and for the setting of novel therapies, before fracture occurrence. In the last decades the interest of the Scientific Community has been concentrated in the understanding the genetic bases of this disease but with controversial and/or inconclusive results. This review tries to summarize data on the most representative osteoporosis candidate genes. Moreover, since recently osteoporosis and cardiovascular diseases have shown to share common physiopathological mechanisms, this review also provides information on the current understanding of osteoporosis and cardiovascular diseases common genetic bases.

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.

How genomics has informed our understanding of the pathogenesis of osteoporosis

Osteoporosis is a skeletal disorder characterized by compromised bone strength that predisposes a person to an increased risk of fracture. Osteoporosis is a complex trait that involves multiple genes, environmental factors, and gene-gene and gene-environment interactions. Twin and family studies have indicated that between 25% and 85% of the variation in bone mass and other skeletal phenotypes is heritable, but our knowledge of the underlying genes is limited. Bone mineral density is the most common assessment for diagnosing osteoporosis and is the most often used quantitative value in the design of genetic studies. In recent years, our understanding of the pathophysiology of osteoporosis has been greatly facilitated by advances brought about by the Human Genome Project. Genetic approaches ranging from family studies of monogenic traits to association studies with candidate genes, to whole-genome scans in both humans and animals have identified a small number of genes that contribute to the heritability of bone mass. Studies with transgenic and knockout mouse models have revealed major new insights into the biology of many of these identified genes, but much more needs to be learned. Ultimately, we hope that by revealing the underlying genetics and biology driving the pathophysiology of osteoporosis, new and effective treatment can be developed to combat and possibly cure this devastating disease. Here we review the rapidly evolving field of the genomics of osteoporosis with a focus on important gene discoveries, new biological/physiological paradigms that are emerging, and many of the unanswered questions and hurdles yet to be overcome in the field.