Network-based Transcriptome-wide Expression Study for Postmenopausal Osteoporosis

Small interfering RNAs in the management of human osteoporosis

BACKGROUND

Osteoporosis results in reduced bone mass and consequent bone fragility. Small interfering RNAs (siRNAs) can be used for therapeutic purposes, as molecular targets or as useful markers to test new therapies.

SOURCES OF DATA

A systematic search of different databases to May 2023 was performed to define the role of siRNAs in osteoporosis therapy. Fourteen suitable studies were identified.

AREAS OF AGREEMENT

SiRNAs may be useful in studying metabolic processes in osteoporosis and identify possible therapeutic targets for novel drug therapies.

AREAS OF CONTROVERSY

The metabolic processes of osteoporosis are regulated by many genes and cytokines that can be targeted by siRNAs. However, it is not easy to predict whether the in vitro responses of the studied siRNAs and drugs are applicable in vivo.

GROWING POINTS

Metabolic processes can be affected by the effect of gene dysregulation mediated by siRNAs on various growth factors.

AREAS TIMELY FOR DEVELOPING RESEARCH

Despite the predictability of pharmacological response of siRNA in vitro, similar responses cannot be expected in vivo.

Postmenopausal osteoporosis: a bioinformatics-integrated experimental study the pathogenesis

Postmenopausal osteoporosis (PMOP) is a chronic bone metabolic disease, which often causes fractures and various complications, it causes a great social and economic burden, and it is urgent to use modern research techniques to elucidate the pathogenesis of PMOP. At the same time, because of the complex physiological and pathological interaction mechanism between osteoporosis and sarcopenia, the correlation research has become a hot topic. Ovary removal is a commonly used experimental method to study the endocrine system of female animals, and it is also the best animal model to study PMOP. In this study, the preparation of the ovariectomized rat was confirmed through the detection of vaginal smear, the level of bone formation markers, and the analysis of bone tissue morphology. Transcriptome sequencing was used to analyze the molecular mechanism of PMOP in ovariectomized rats, qRT-PCR was used to verify the key targets. Results of Micro-CT and scanning electron microscopy (SEM) showed that the trabecular structure was disorganized and the symptoms of osteoporosis appeared, this indicating that the ovariectomized rats model was successfully prepared. Transcriptional sequencing results of femur tissue showed that 452 differentially expressed genes (DEGs) were screened. Bioinformatics analysis results showed that the osteoporosis caused by ovariectomized rats was mainly related to muscle contraction, calcium signaling pathway, etc. Results of qRT-PCR were consistent with transcriptome analysis. These results reveal the pathogenesis of PMOP in ovariectomized rats and also offer a possibility for elucidating the relevance of action between PMOP and sarcopenia.

NEDD4 E3 Ligases: Functions and Mechanisms in Bone and Tooth

Protein ubiquitination is a precisely controlled enzymatic cascade reaction belonging to the post-translational modification of proteins. In this process, E3 ligases catalyze the binding of ubiquitin (Ub) to protein substrates and define specificity. The neuronally expressed developmentally down-regulated 4 (NEDD4) subfamily, belonging to the homology to E6APC terminus (HECT) class of E3 ligases, has recently emerged as an essential determinant of multiple cellular processes in different tissues, including bone and tooth. Here, we place special emphasis on the regulatory role of the NEDD4 subfamily in the molecular and cell biology of osteogenesis. We elucidate in detail the specific roles, downstream substrates, and upstream regulatory mechanisms of the NEDD4 subfamily. Further, we provide an overview of the involvement of E3 ligases and deubiquitinases in the development, repair, and regeneration of another mineralized tissue—tooth.

Identification of combined biomarkers for predicting the risk of osteoporosis using machine learning

Osteoporosis is a severe chronic skeletal disorder that affects older individuals, especially postmenopausal women. However, molecular biomarkers for predicting the risk of osteoporosis are not well characterized. The aim of this study was to identify combined biomarkers for predicting the risk of osteoporosis using machine learning methods. We merged three publicly available gene expression datasets (GSE56815, GSE13850, and GSE2208) to obtain expression data for 6354 unique genes in postmenopausal women (45 with high bone mineral density and 45 with low bone mineral density). All machine learning methods were implemented in R, with the GEOquery and limma packages, for dataset download and differentially expressed gene identification, and a nomogram for predicting the risk of osteoporosis was constructed. We detected 378 significant differentially expressed genes using the limma package, representing 15 major biological pathways. The performance of the predictive models based on combined biomarkers (two or three genes) was superior to that of models based on a single gene. The best predictive gene set among two-gene sets included PLA2G2A and WRAP73. The best predictive gene set among three-gene sets included LPN1, PFDN6, and DOHH. Overall, we demonstrated the advantages of using combined versus single biomarkers for predicting the risk of osteoporosis. Further, the predictive nomogram constructed using combined biomarkers could be used by clinicians to identify high-risk individuals and in the design of efficient clinical trials to reduce the incidence of osteoporosis.

The regulative effect and repercussion of probiotics and prebiotics on osteoporosis: involvement of brain-gut-bone axis

Osteoporosis (OP) is a systemic disease characterized by decreased bone mass and degeneration of bone microstructure. In recent years, more and more researches have focused on the close relationship between gut microbiota (GM) and the occurrence and progression of OP, and the regulation of probiotics and prebiotics on bone metabolism has gradually become a research hotspot. Based on the influence of brain-gut-bone axis on bone metabolism, this review expounds the potential mechanisms of probiotics and prebiotics on OP from next perspectives: regulation of intestinal metabolites, regulation of intestinal epithelial barrier function, involvement of neuromodulation, involvement of immune regulation and involvement of endocrine regulation, so as to provide a novel and promising idea for the prevention and treatment of OP in the future.

Identification of Serum Exosome-Derived circRNA-miRNA-TF-mRNA Regulatory Network in Postmenopausal Osteoporosis Using Bioinformatics Analysis and Validation in Peripheral Blood-Derived Mononuclear Cells

BACKGROUND

Osteoporosis is one of the most common systemic metabolic bone diseases, especially in postmenopausal women. Circular RNA (circRNA) has been implicated in various human diseases. However, the potential role of circRNAs in postmenopausal osteoporosis (PMOP) remains largely unknown. The study aims to identify potential biomarkers and further understand the mechanism of PMOP by constructing a circRNA-associated ceRNA network.

METHODS

The PMOP-related datasets GSE161361, GSE64433, and GSE56116 were downloaded from the Gene Expression Omnibus (GEO) database and were used to obtain differentially expressed genes (DEGs). Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied to determine possible relevant functions of differentially expressed messenger RNAs (mRNAs). The TRRUST database was used to predict differential transcription factor (TF)-mRNA regulatory pairs. Afterwards, combined CircBank and miRTarBase, circRNA-miRNA as well as miRNA-TF pairs were constructed. Then, a circRNA-miRNA-TF-mRNA network was established. Next, the correlation of mRNAs, TFs, and PMOP was verified by the Comparative Toxicogenomics Database. And expression levels of key genes, including circRNAs, miRNAs, TFs, and mRNAs in the ceRNA network were further validated by quantitative real-time PCR (qRT-PCR). Furthermore, to screen out signaling pathways related to key mRNAs of the ceRNA network, Gene Set Enrichment Analysis (GSEA) was performed.

RESULTS

A total of 1201 DE mRNAs, 44 DE miRNAs, and 1613 DE circRNAs associated with PMOP were obtained. GO function annotation showed DE mRNAs were mainly related to inflammatory responses. KEGG analysis revealed DE mRNAs were mainly enriched in osteoclast differentiation, rheumatoid arthritis, hematopoietic cell lineage, and cytokine-cytokine receptor interaction pathways. We first identified 26 TFs and their target mRNAs. Combining DE miRNAs, miRNA-TF/mRNA pairs were obtained. Combining DE circRNAs, we constructed the ceRNA network contained 6 circRNAs, 4 miRNAs, 4 TFs, and 12 mRNAs. The expression levels of most genes detected by qRT-PCR were generally consistent with the microarray results. Combined with the qRT-PCR validation results, we eventually identified the ceRNA network that contained 4 circRNAs, 3 miRNAs, 3 TFs, and 9 mRNAs. The GSEA revealed that 9 mRNAs participate in many important signaling pathways, such as "olfactory transduction", "T cell receptor signaling pathway", and "neuroactive ligand-receptor interaction". These pathways have been reported to the occurrence and development of PMOP. To sum up, key mRNAs in the ceRNA network may participate in the development of osteoporosis by regulating related signal pathways.

CONCLUSIONS

A circRNA-associated ceRNA network containing TFs was established for PMOP. The study may help further explore the molecular mechanisms and may serve as potential biomarkers or therapeutic targets for PMOP.

The Effect of Moderate-Intensity Treadmill Exercise on Bone Mass and the Transcription of Peripheral Blood Mononuclear Cells in Ovariectomized Rats

Objective: Using RNA-sequencing technology to screen the effect of moderate-intensity treadmill exercise on the sensitive genes that affect bone mass in the peripheral blood mononuclear cells (PBMCs) of ovariectomized (OVX) rats.

Methods: Three-month-old female Sprague-Dawley rats of Specific Pathogen Free (SPF) grade were randomly divided into the sham operation (SHAM) group, OVX group, and OVX combined exercise (OVX + EX) group. The OVX + EX group performed moderate-intensity treadmill exercise for 17 weeks. Then, the body composition and bone mineral density (BMD) were measured, and the bone microstructure of the femur was observed. PBMCs were collected from the abdominal aorta, and the differential genes were analyzed by transcriptome sequencing to further screen sensitive genes.

Results: (1) In the OVX group, the body weight and body fat content were significantly higher than in the SHAM group while the muscle content and BMD were significantly lower than the SHAM group. (2) The trabecular bone parameters in the OVX group were significantly lower than in the SHAM group, and they were significantly higher in the OVX + EX group than in the OVX group. When compared with the SHAM group, the microstructure of the distal femur trabecular in the OVX group was severely damaged, suggest that the morphological structure of trabecular bone is severely damaged, the number of trabecular bones is reduced, and the thickness becomes thinner, which lead to the widening of the trabecular bone space and the appearance of osteoporosis. The number and continuity of the trabecular bones were higher in the OVX + EX group than in the OVX group. (3) A Venn diagram showed that there were 58 common differential genes, and the differential genes were mainly enriched in the PI3K-Akt signaling pathway. Five sensitive genes were screened including CCL2, Nos3, Tgfb3, ITGb4, and LpL. The expression of CCL2, Nos3, and Tgfb3 genes was closely related to multiple bone parameters.

Conclusion: Moderate-intensity treadmill exercise may improve the body composition and bone mass of the OVX group by upregulating CCL2 and other genes of the PBMC. The PBMCs in the peripheral blood can be a useful tool for monitoring the effect of exercise on bone health in postmenopausal osteoporosis.

Analysis of Molecular Mechanism of Erxian Decoction in Treating Osteoporosis Based on Formula Optimization Model

Osteoporosis (OP) is a highly prevalent orthopedic condition in postmenopausal women and the elderly. Currently, OP treatments mainly include bisphosphonates, receptor activator of nuclear factor kappa-B ligand (RANKL) antibody therapy, selective estrogen receptor modulators, teriparatide (PTH1-34), and menopausal hormone therapy. However, increasing evidence has indicated these treatments may exert serious side effects. In recent years, Traditional Chinese Medicine (TCM) has become popular for treating orthopedic disorders. Erxian Decoction (EXD) is widely used for the clinical treatment of OP, but its underlying molecular mechanisms are unclear thanks to its multiple components and multiple target features. In this research, we designed a network pharmacology method, which used a novel node importance calculation model to identify critical response networks (CRNs) and effective proteins. Based on these proteins, a target coverage contribution (TCC) model was designed to infer a core active component group (CACG). This approach decoded the mechanisms underpinning EXD's role in OP therapy. Our data indicated that the drug response network mediated by the CACG effectively retained information of the component-target (C-T) network of pathogenic genes. Functional pathway enrichment analysis showed that EXD exerted therapeutic effects toward OP by targeting PI3K-Akt signaling (hsa04151), calcium signaling (hsa04020), apoptosis (hsa04210), estrogen signaling (hsa04915), and osteoclast differentiation (hsa04380) via JNK, AKT, and ERK. Our method furnishes a feasible methodological strategy for formula optimization and mechanism analysis and also supplies a reference scheme for the secondary development of the TCM formula.