Identification of differentially expressed genes, signaling pathways and immune infiltration in postmenopausal osteoporosis by integrated bioinformatics analysis

Bioinformatic identification of important roles of COL1A1 and TNFRSF12A in cartilage injury and osteoporosis

OBJECTIVE

The aim of this study was to identify the key regulatory mechanisms of cartilage injury and osteoporosis through bioinformatics methods, and to provide a new theoretical basis and molecular targets for the diagnosis and treatment of the disease.

METHODS

Microarray data for cartilage injury (GSE129147) and osteoporosis (GSE230665) were first downloaded from the GEO database. Differential expression analysis was applied to identify genes that were significantly up-or down-regulated in the cartilage injury and osteoporosis samples. These genes were subjected to GO enrichment analysis and KEGG pathway analysis. In addition, we employed SVA and RRA methods to merge the two sets of data, eliminating batch effects and enhancing the statistical power of the analysis. Through WGCNA, we identified gene modules that were closely associated with disease phenotypes and then screened for key genes that intersected with differentially expressed genes. The diagnostic value of these genes as potential biomarkers was evaluated by ROC analysis. Moreover, we performed an immune infiltration analysis to explore the correlation between these core genes and immune cell infiltration.

RESULTS

We performed GO enrichment analysis and KEGG pathway analysis of genes significantly up-or down-regulated in cartilage injury and osteoporosis samples. Important biological processes, cellular components and molecular functions, and key metabolic or signaling pathways associated with osteoporosis and cartilage injury were identified. Through WGCNA, we identified gene modules that were closely associated with the disease phenotype, from which we then screened for key genes that intersected with differentially expressed genes. Ultimately, we focused on two identified core genes, COL1A1 and TNFRSF12A, and assessed the diagnostic value of these genes as potential biomarkers by ROC analysis. Meanwhile, GSVA provided an in-depth view of the role of these genes in disease-specific biological pathways. Immune infiltration analysis further revealed the possible key role of COL1A1 and TNFRSF12A in regulating immune cell infiltration in osteoporosis and cartilage injury.

CONCLUSION

COL1A1 and TNFRSF12A as key regulatory molecules in osteoporosis and cartilage injury.

Myocyte-Specific Enhancer Factor 2A Potentiates Osteoclastic Differentiation in Osteoporosis by Inducing Endothelin Receptor Type A

Activation of endothelin receptor type A (EDNRA) has been revealed to induce osteoclastic bone resorption during orthodontic treatment. In this study, we investigated the mechanisms by which EDNRA potentiates osteoclastic differentiation in ovariectomy (OVX)-induced mice with osteoporosis (OP)-like symptoms. The effects of knocking down EDNRA on OP in mice were observed using micro-CT, HE staining, TRAP staining, RT-qPCR, and immunoblotting. The effects of the knockdown of EDNRA in osteoclastic differentiation of bone marrow macrophages (BMs) were investigated by TRAP staining, F-actin staining, RT-qPCR, and immunoblotting. EDNRA was highly expressed in osteoporotic mice, and the knockdown of EDNRA in vivo alleviated osteoporotic phenotypes in OVX-induced mice by inhibiting osteoclast differentiation. BMs with EDNRA knockdown showed repressed MMP1, MMP8, and RANKL protein expression and Nfatc1, Ctsk, C-fos, and Trap mRNA expression. Myocyte-specific enhancer factor 2A (MEF2A) transcriptionally promoted EDNRA expression by binding to the EDNRA promoter. Silencing of MEF2A exerted the same anti-osteoporotic effects, which were reversed by overexpression of EDNRA. Altogether, our findings highlight that MEF2A knockdown alleviates loss of bone mass in the OVX-induced mice by suppressing osteoclast differentiation via inhibition of EDNRA transcription.

Crosstalk between bone and the immune system

Bone functions not only as a critical element of the musculoskeletal system but also serves as the primary lymphoid organ harboring hematopoietic stem cells (HSCs) and immune progenitor cells. The interdisciplinary field of osteoimmunology has illuminated the dynamic interactions between the skeletal and immune systems, vital for the maintenance of skeletal tissue homeostasis and the pathogenesis of immune and skeletal diseases. Aberrant immune activation stimulates bone cells such as osteoclasts and osteoblasts, disturbing the bone remodeling and leading to skeletal disorders as seen in autoimmune diseases like rheumatoid arthritis. On the other hand, intricate multicellular network within the bone marrow creates a specialized microenvironment essential for the maintenance and differentiation of HSCs and the progeny. Dysregulation of immune-bone crosstalk in the bone marrow environment can trigger tumorigenesis and exacerbated inflammation. A comprehensive deciphering of the complex "immune-bone crosstalk" leads to a deeper understanding of the pathogenesis of immune diseases as well as skeletal diseases, and might provide insight into potential therapeutic approaches.

Weighted gene co-expression network analysis reveals key biomarkers and immune infiltration characteristics for bronchial epithelial cells from asthmatic patients

BACKGROUND

Asthma ranks among the most prevalent non-communicable diseases worldwide. Previous studies have elucidated the significant role of the immune system in its pathophysiology. Nevertheless, the immune-related mechanisms underlying asthma are complex and still inadequately understood. Thus, our objective was to investigate novel key biomarkers and immune infiltration characteristics associated with asthma by employing integrated bioinformatics tools.

METHODS

In this study, we conducted a weighted gene co-expression network analysis (WGCNA) to identify key modules and genes potentially implicated in asthma. Functional annotation of these key modules and genes was carried out through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Additionally, we constructed a protein-protein interaction (PPI) network using the STRING database to identify 10 hub genes. Furthermore, we evaluated the relative proportion of immune cells in bronchial epithelial cell samples from 20 healthy individuals and 88 asthmatic patients using CIBERSORT. Finally, we validated the hub genes and explored their correlation with immune infiltration.

RESULTS

Furthermore, 20 gene expression modules and 10 hub genes were identified herein. Among them, complement component 3 (C3), prostaglandin I2 receptor (PTGIR), parathyroid hormone-like hormone (PTHLH), and C-X3-C motif chemokine ligand 1 (CX3CL1) were closely correlated with the infiltration of immune cells. They may be novel candidate biomarkers or therapeutic targets for asthma. Furthermore, B cells memory, and plasma cells might play an important role in immune cell infiltration after asthma.

CONCLUSIONS

C3, PTGIR, CX3CL1, and PTHLH have important clinical diagnostic values and are correlated with infiltration of multiple immune cell types in asthma. These hub genes, B cells memory, and plasma cells may become important biological targets for therapeutic asthma drug screening and drug design.