Long Noncoding RNA Analyses for Osteoporosis Risk in Caucasian Women

Development and experimental validation of an energy metabolism-related gene signature for diagnosing of osteoporosis

Osteoporosis is usually caused by excessive bone resorption and energy metabolism plays a critical role in the development of osteoporosis. However, little is known about the role of energy metabolism-related genes in osteoporosis. This study aimed to explore the important energy metabolism-related genes involved in the development of osteoporosis and develop a diagnosis signature for osteoporosis. The GSE56814, GSE62402, and GSE7158 datasets were downloaded from the NCBI Gene Expression Omnibus. The intersection of differentially expressed genes between high and low levels of body mineral density (BMD) and genes related to energy metabolism were screened as differentially expressed energy metabolism genes (DE-EMGs). Subsequently, a DE-EMG-based diagnostic model was constructed and differential expression of genes in the model was validated by RT-qPCR. Furthermore, a receiver operating characteristic curve and nomogram model were constructed to evaluate the predictive ability of the diagnostic model. Finally, the immune cell types in the merged samples and networks associated with the selected optimal DE-EMGs were constructed. A total of 72 overlapped genes were selected as DE-EMGs, and a five DE-EMG based diagnostic model consisting B4GALT4, ADH4, ACAD11, B4GALT2, and PPP1R3C was established. The areas under the curve of the five genes in the merged training dataset and B4GALT2 in the validation dataset were 0.784 and 0.790, respectively. Moreover, good prognostic prediction ability was observed using the nomogram model (C index = 0.9201; P = 5.507e-14). Significant differences were observed in five immune cell types between the high- and low-BMD groups. These included central memory, effector memory, and activated CD8 T cells, as well as regulatory T cells and activated B cells. A network related to DE-EMGs was constructed, including hsa-miR-23b-3p, DANCR, 17 small-molecule drugs, and two Kyoto Encyclopedia of Genes and Genomes pathways, including metabolic pathways and pyruvate metabolism. Our findings highlighted the important roles of DE-EMGs in the development of osteoporosis. Furthermore, the DANCR/hsa-miR-23b-3p/B4GALT4 axis might provide novel molecular insights into the process of osteoporosis development.

Identification of potential pathogenic genes related to osteoporosis and osteoarthritis

BACKGROUND

Osteoarthritis (OA) and osteoporosis (OS) are the most common orthopedic diseases.

OBJECTIVE

To identify important genes as biomarkers for the pathogenesis of OA and OS.

METHODS

Microarray data for OA and OS were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between the OA and healthy control groups and between the OS and healthy control groups were identified using the Limma software package. Overlapping hub DEGs were selected using MCC, MNC, DEGREE, and EPC. Weighted gene co-expression network analysis (WGCNA) was used to mine OA- and OS-related modules. Shared hub DEGs were identified, human microRNA disease database was used to screen microRNAs associated with OA and OS, and an miRNA-target gene network was constructed. Finally, the expression of shared hub DEGs was evaluated.

RESULTS

A total of 104 overlapping DEGs were identified in both the OA and OS groups, which were mainly related to inflammatory biological processes, such as the Akt and TNF signaling pathways Forty-six hub DEGs were identified using MCC, MNC, DEGREE, and EPC modules using different algorithms. Seven modules with 392 genes that highly correlated with disease were identified in the WGCNA. Furthermore, 10 shared hub DEGs were identified between the OA and OS groups, including OGN, FAP, COL6A3, THBS4, IGFBP2, LRRC15, DDR2, RND3, EFNB2, and CD48. A network consisting of 8 shared hub DEGs and 55 miRNAs was constructed. Furthermore, CD48 was significantly upregulated in the OA and OS groups, whereas EFNB2, DR2, COL6A3, and RND3 were significantly downregulated in OA and OS. Other hub DEGs were significantly upregulated in OA and downregulated in OS.

CONCLUSIONS

The ten genes may be promising biomarkers for modulating the development of both OA and OS.

Identification of neutrophil extracellular traps and crosstalk genes linking inflammatory bowel disease and osteoporosis by integrated bioinformatics analysis and machine learning

Musculoskeletal deficits are among the most common extra-intestinal manifestations and complications of inflammatory bowel disease (IBD). This study aimed to identify crosstalk genes between IBD and osteoporosis (OP) and potential relationships between crosstalk and neutrophil extracellular traps (NETs)-related genes. Three common hub genes from different compared groups are actually the same, namely HDAC6, IL-8, and PPIF. ROC showed that the combined diagnostic value of HDAC6, IL-8, and PPIF was higher than each of the three key hub genes. Immune infiltration results showed that HDAC6 and IL-8 key genes negatively correlated with CD65 bright natural killer cells. USF1 was the common upstream TFs between HDAC6 and PPIF, and MYC was the common upstream TFs between IL-8 and PPIF in RegNetwork. Taken together, this study shows a linked mechanism between IBD and OP via NETs and crosstalk genes. These findings may show light on better diagnosis and treatment of IBD complicated with OP.

Identification of Known and Novel Long Noncoding RNAs Potentially Responsible for the Effects of Bone Mineral Density (BMD) Genomewide Association Study (GWAS) Loci

Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long noncoding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor single-nucleotide polymorphisms (SNPs) demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (false discovery rate [FDR] correction < 0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability [RCP] > 0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Consensus gene modules related to levels of bone mineral density (BMD) among smokers and nonsmokers

Osteoporosis, as a common metabolic disorder characterized by the decrease of bone mass, can cause fractures, thereby threatening the life quality of females, especially postmenopausal women. Thus, it is necessary to reveal the genes involved in osteoporosis and explore biomarkers for osteoporosis. In this study, two groups, smokers and nonsmokers with different bone mineral density (BMD) levels, were collected from the Gene Expression Omnibus (GEO) database GSE13850. Consensus modules of the two groups were identified; the variety of gene modules between smokers and nonsmokers with different BMD levels was observed; and a consensus module, including 390 genes significantly correlated with different BMD levels, was identified. Function analysis revealed the significantly enriched osteoporosis-related pathways, such as the PI3K-Akt signaling pathway. Hub genes analysis revealed the critical role of CXCL12 and CHRM2 in modules related to BMD levels. Based on the support vector machine recursive feature elimination (SVM-RFE) analysis, the model containing 10 genes (TNS4, IRF2, BSG, GZMM, ARRB2, COX15, RALY, TP53, RPS6KA3, and SYNPO) with good performance in identifying people with different BMD levels was constructed. Among them, the roles of RALY and SYNPO in the osteogenic differentiation of hBMSCs were verified experimentally. Overall, this study provides a strategy to explore the biomarkers for osteoporosis through analysis of consensus modules.

The potential role of lncRNAs in osteoporosis

Osteoporosis is a common bone disease characterized by low bone mass and deterioration of bone microstructure, which predisposes to higher risks of bone fragility and bone fracture. Long non-coding RNAs (lncRNAs) are a class of RNAs with a length of > 200 nucleotides without protein-coding function, which control the expression of genes and affect multiple biological processes. Accumulating evidence suggests that lncRNAs are widely involved in the molecular mechanisms of osteoporosis. This review aims to summarize the function and underlying mechanism of lncRNAs involved in the development of osteoporosis, and how it contributes to osteoblast and osteoclast function. This knowledge will shed new light on the modulation and potential treatment of osteoporosis.

Identification of Critical Functional Modules and Signaling Pathways in Osteoporosis

Background:

Osteoporosis is the most common bone metabolic disease. Abnormal osteoclast formation and resorption play a fundamental role in osteoporosis pathogenesis. Recent researches have greatly broadened our understanding of molecular mechanisms of osteoporosis. However, the molecular mechanisms leading to osteoporosis are still not entirely clear.

Objective:

The purpose of this work is to study the critical regulatory genes, functional modules, and signaling pathways.

Methods:

Differential expression analysis, network topology-based analysis, and overrepresentation enrichment analysis (ORA) were used to identify differentially expressed genes (DEGs), gene subnetworks, and signaling pathways related to osteoporosis, respectively.

Results:

Differential expression analysis identified DEGs, such as POGLUT1, DAPK3 and NFKBIA, associated with osteoclastogenesis, which highlighted Notch, apoptosis and NF-kB signaling pathways. Network topology-based analysis identified the upregulated subnetwork characterized by EXOSC8 and DIS3L from the RNA exosome complex, and the downregulated subnetwork composed of histone deacetylases and the cofactors, MORF4L1 and JDP2. Furthermore, the overrepresentation enrichment analysis highlighted that corticotrophin-releasing hormone signaling pathway might affect osteoclastogenesis through its component NR4A1, and suppressing osteoclast differentiation and osteoclast bone resorption with urocortin (UCN).

Conclusion:

Our systematic analysis not only discovered novel molecular mechanisms but also proposed potential drug targets for osteoporosis.

LncRNA RP1-85F18.6 affects osteoblast cells by regulating the cell cycle

A lncRNA RP1-85F18.6 was reported to affect cell growth by regulating the cell cycle. Here we tested whether it affects the proliferation of osteoblast cells by regulating the cell cycle. We determined the expression of RP1-85F18.6 in two osteoblast cell lines hFOB and HOB by qPCR. Then we knocked down or overexpressed RP1-85F18.6 in hFOB and tested the alteration of viability, cell cycle, and cell cycle regulatory proteins. Results showed that both hFOB and HOB expressed RP1-85F18.6. The knockdown of RP1-85F18.6 decreased the viability of hFOB, while the overexpression of it increased the viability. Higher expression of RP1-85F18.6 results in higher cell viability. The knockdown of RP1-85F18.6 caused an increase in the S phase cells and a decrease in the G2/M phase cells. The overexpression of RP1-85F18.6 caused a decrease in the S phase cells and an increase in the G2/M phase cells. The knockdown of RP1-85F18.6 decreased cyclin A, cdk1, E2F, cyclin B, p53, and p21, whereas the overexpression of RP1-85F18.6 increased cyclin A, cdk1, E2F, cyclin B, p53, and p21. This study demonstrated that RP1-85F18.6 is expressed in osteoblast cell lines hFOB and HOB. RP1-85F18.6 affects the proliferation of osteoblasts by regulating the cell cycle.

Genetic variability in noncoding RNAs: involvement of miRNAs and long noncoding RNAs in osteoporosis pathogenesis

The pathogenesis of osteoporosis is multifactorial and is the consequence of genetic, hormonal and lifestyle factors. Epigenetics, including noncoding RNA (ncRNA) deregulation, represents a link between susceptibility to develop the disease and environmental influences. The majority of studies investigated the expression of ncRNAs in osteoporosis patients; however, very little information is available on their genetic variability. In this review, we focus on two classes of ncRNAs: miRNAs and long noncoding RNAs (lncRNAs). We summarize recent findings on how polymorphisms in miRNAs and lncRNAs can perturb the lncRNA/miRNA/mRNA axis and may be involved in osteoporosis clinical outcome. We also provide a general overview on databases and bioinformatic tools useful for associating miRNAs and lncRNAs variability with complex genetic diseases.

Integrative Analysis of Genomics and Transcriptome Data to Identify Regulation Networks in Female Osteoporosis

Background: Osteoporosis is a highly heritable skeletal muscle disease. However, the genetic mechanisms mediating the pathogenesis of osteoporosis remain unclear. Accordingly, in this study, we aimed to clarify the transcriptional regulation and heritability underlying the onset of osteoporosis.

Methods: Transcriptome gene expression data were obtained from the Gene Expression Omnibus database. Microarray data from peripheral blood monocytes of 73 Caucasian women with high and low bone mineral density (BMD) were analyzed. Differentially expressed messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs) were identified. Differences in BMD were then attributed to several gene modules using weighted gene co-expression network analysis (WGCNA). LncRNA/mRNA regulatory networks were constructed based on the WGCNA and subjected to functional enrichment analysis.

Results: In total, 3,355 mRNAs and 999 lncRNAs were identified as differentially expressed genes between patients with high and low BMD. The WGCNA yielded three gene modules, including 26 lncRNAs and 55 mRNAs as hub genes in the blue module, 36 lncRNAs and 31 mRNAs as hub genes in the turquoise module, and 56 mRNAs and 30 lncRNAs as hub genes in the brown module. JUN and ACSL5 were subsequently identified in the modular gene network. After functional pathway enrichment, 40 lncRNAs and 16 mRNAs were found to be related to differences in BMD. All three modules were enriched in metabolic pathways. Finally, mRNA/lncRNA/pathway networks were constructed using the identified regulatory networks of lncRNAs/mRNAs and pathway enrichment relationships.

Conclusion: The mRNAs and lncRNAs identified in this WGCNA could be novel clinical targets in the diagnosis and management of osteoporosis. Our findings may help elucidate the complex interactions between transcripts and non-coding RNAs and provide novel perspectives on the regulatory mechanisms of osteoporosis.

The regulatory roles of long noncoding RNAs in osteoporosis

Osteoporosis is a common metabolic bone disease characterized by low bone mineral density (BMD) and microarchitectural deterioration of bone tissue, which leads to decreased bone strength and increased fracture risk. Osteoporosis mainly results from a disruption of the balance between bone formation mediated by osteoblasts and bone resorption mediated by osteoclasts. At present, the molecular mechanisms underlying osteoporosis are still not fully understood. Long noncoding RNAs (lncRNAs) are RNA molecules that exceed 200 nucleotides (nt) in length and have limited or no protein-coding capacity. Over the past decade, numerous lncRNAs have been demonstrated to participate in multiple biological processes and to play essential roles in the pathogenesis of various diseases. In this review, we summarize recent progress in research on lncRNAs in osteoporosis and mainly focus on their regulatory roles in osteogenesis and osteoclastogenesis. Moreover, we briefly discuss the potential clinical applications of lncRNAs in osteoporosis.

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.

The Role of Micro RNA and Long-Non-Coding RNA in Osteoporosis

Osteoporosis is a major concern worldwide and can be attributed to an imbalance between osteoblastic bone formation and osteoclastic bone resorption due to the natural aging process. Heritable factors account for 60-80% of optimal bone mineralization; however, the finer details of pathogenesis remain to be elucidated. Micro RNA (miRNA) and long-non-coding RNA (lncRNA) are two targets that have recently come into the spotlight due to their ability to control gene expression at the post-transcriptional level and provide epigenetic modification. miRNAs are a class of non-coding RNAs that are approximately 18-25 nucleotides long. It is thought that up to 60% of human protein-coding genes may be regulated by miRNAs. They have been found to regulate gene expression that controls osteoblast-dependent bone formation and osteoclast-related bone remodeling. lncRNAs are highly structured RNA transcripts longer than 200 nucleotides that do not translate into proteins. They have very complex secondary and tertiary structures and the same degradation processes as messenger RNAs. The fact that they have a rapid turnover is due to their sponge function in binding the miRNAs that lead to a degradation of the lncRNA itself. They can act as signaling, decoy, and framework molecules, or as primers. Current evidence suggests that lncRNAs can act as chromatin and transcriptional as well as post-transcriptional regulators. With regards to osteoporosis, lncRNA is thought to be involved in the proliferation, apoptosis, and inflammatory response of the bone. This review, which is based on a systematic appraisal of the current literature, provides current molecular and genetic opinions on the roles of miRNAs and lncRNAs in osteoporosis. Further research into the epigenetic modification and the regulatory roles of these molecules will bring us closer to potential disease-modifying treatment for osteoporosis. However, more issues regarding the detailed actions of miRNAs and lncRNAs in osteoporosis remain unknown and controversial and warrant future investigation.

Comprehensive Analysis of lncRNA and miRNA Expression Profiles and ceRNA Network Construction in Osteoporosis

Multiple profiling studies have identified a number of non-coding RNAs associated with the pathogenesis of human diseases. However, the exact regulatory mechanisms and functions of these non-coding RNAs in the development of osteoporosis have not yet been explored. Transcriptome gene expression and miRNA microarray data from peripheral blood monocytes of five high hip bone mineral density (BMD) subjects and five low hip BMD subjects were analyzed. Differentially expressed mRNAs, lncRNAs, and miRNAs were identified and subjected to functional enrichment analysis. Additionally, protein-protein interaction (PPI), lncRNA-mRNA, and mRNA-lncRNA-miRNA competing endogenous RNA (ceRNA) networks were constructed. Differential analysis revealed that 297 mRNAs, 151 lncRNAs, and 38 miRNAs were significantly differentially expressed between peripheral blood monocytes from high and low hip BMD subjects. Key genes including ACLY, HSPA5, and AKT1 were subsequently identified in the PPI network. Additionally, differentially expressed lncRNAs were primarily enriched in the citrate cycle (TCA cycle), biosynthesis of antibiotics, and carbon metabolism pathways. Finally, the mRNA-lncRNA-miRNA network revealed several key ceRNA regulatory relationships among the transcripts and non-coding RNAs. Key mRNAs and non-coding RNAs identified in the networks represent potential biomarkers or targets in the diagnosis and management of osteoporosis. Our findings represent a resource for further functional research on the ceRNA regulation mechanism of non-coding RNA in osteoporosis.

Integrative Analyses of Genes Associated With Osteoporosis in CD16+ Monocyte

BACKGROUND

Osteoporosis is a metabolic bone disease characterized by decreased bone mineral density and abnormal bone quality. Monocytes can secret cytokines for bone resorption, resulting in bone mass loss. However, the mechanism by which monocytes subpopulations lead to osteoporosis remains unclear. The aim of this study was to identify genes associated with osteoporosis in monocytes subsets.

METHODS

Three microarray datasets including GSE7158 (transcription of low/high-peak bone mass), GSE101489 (transcription of CD16+/CD16- monocyte) and GSE93883 (miRNA expression profile of primary osteoporosis) were derived from the Gene Expression Omnibus (GEO) database and analyzed with GEO2R tool to identify differentially expressed genes (DEGs). Functional enrichment was analyzed using Metascape database and GSEA software. STRING was utilized for the Protein-Protein Interaction Network construct. The hub genes were screened out using the Cytoscape software. Related miRNAs were predicted in miRWalk, miRDB, and TargetScan databases.

RESULTS

Total 368 DEGs from GSE7158 were screened out, which were mostly enriched in signaling, positive regulation of biological process and immune system process. The hub genes were clustered into two modules by PPI network analysis. We identified 15 overlapping DGEs between GSE101489 and GSE7158 microarray datasets. Moreover, all of them were up-regulated genes in both datasets. Then, nine key genes were screened out from above 15 overlapping DEGs using Cytoscape software. It is a remarkable fact that the nine genes were all in one hub gene module of GSE7158. Additionally, 183 target miRNAs were predicted according to the above nine DEGs. After cross-verification with miRNA express profile dataset for osteoporosis (GSE93883), 12 DEmiRNAs were selected. Finally, a miRNA-mRNA network was constructed with the nine key genes and 12 miRNAs, which were involved in osteoporosis.

CONCLUSION

Our analysis results constructed a gene expression framework in monocyte subsets for osteoporosis. This approach could provide a novel insight into osteoporosis.

Noncoding RNAs in Steroid-Induced Osteonecrosis of the Femoral Head

Steroid-induced osteonecrosis of the femoral head (ONFH) is a severe orthopedic disease caused by the long-term administration of glucocorticoids. The main pathological feature of ONFH is the gradually progressive necrosis of bone cells and the bone marrow, ultimately resulting in structural changes or even complete collapse of the femoral head. However, the exact pathogenic mechanism of ONFH remains unknown. Noncoding RNAs (ncRNAs) have emerged as very powerful regulators of gene expression, functioning at both transcriptional and posttranscriptional levels in the pathogenesis of ONFH. Here, we review the current knowledge of the role of ncRNAs, including microRNAs, long noncoding RNAs, and circular RNAs, in the pathogenesis of steroid-induced ONFH. Further focus and validation of these associations can provide new insight into the pathogenic mechanisms at the molecular level to suggest targets for treatment and prevention.