A total of 50 FerrDEGs were identified that intersect hypoxia, osteoporosis, and pathways.
FerrDEGs are primarily linked to biological processes involving cellular responses to chemical and oxidative stress.
Key pathway enrichment analyses indicate that these genes are significantly involved in processes such as viral carcinogenesis and Epstein-Barr virus infection.
Eight within the FerrDEGs were identified, including TP53, JUN, SQSTM1, STAT3, CDKN1A, CAV1, CD44, and TGFBR1.
ROC analysis further narrowed down five key hub genes (JUN, SQSTM1, STAT3, CD44, and TGFBR1) that may be crucial in the context of osteoporosis and hypoxia.
The microRNA hsa-miR-20a-5p was determined to be a potential key regulator of these hub genes.
AI simplified
BACKGROUND: Osteoporosis (OP) is a prevalent progressive metabolic bone disease in the middle-aged and elderly population. Previous research has indicated that physiological or pathological hypoxia may disrupt bone metabolism, ultimately contributing to OP development. However, the specific pathophysiological mechanisms remain unknown. is a novel iron-dependent non-apoptotic cell death pathway. The objective of this investigation was to use bioinformatics analysis to identify key related to ferroptosis that may be linked to hypoxia and osteoporosis. Subsequently, we utilized experimental methods to validate these findings.
METHODS: Differentially expressed genes (DEGs) in bone marrow mesenchymal stem cells (BMSCs) from primary osteoporosis patients and hypoxia-treated BMSCs were screened from the Gene Expression Omnibus (GEO) database. These DEGs were then intersected with the ferroptosis dataset (FerrDb), resulting in FerrDEGs. The potential functional roles of FerrDEGs were investigated through gene ontology (GO) and pathway enrichment analysis (e.g., KEGG, WikiPathways and Reactome). The STRING database was used to analyze protein-protein interaction networks, pinpointing hub genes within FerrDEGs. To further assess the predictive value of these hub genes, we conducted ROC analysis using the data from GSE230665 to identify key hub genes. Subsequently, NetworkAnalyst was employed to establish networks between target microRNAs(miRNAs) and key hub genes. Finally, we validated the key hub genes and miRNAs in an OVX rat model for further confirmation.
RESULTS: A total of 50 FerrDEGs were identified in the overlap of hypoxia, OP, and ferroptosis pathways. These FerrDEGs were primarily associated with biological processes related to cellular response to chemical stress and oxidative stress. Pathway enrichment analysis revealed that these FerrDEGs played significant roles in processes such as viral carcinogenesis and epstein-barr virus infection. Multiple algorithms (CytoHubba, CytoNCA and Analyze Network) were employed to identify eight hub genes within FerrDEGs, including TP53, JUNβ, SQSTM1, STAT3β, CDKN1Aβββ, CAV1, CD44 and TGFBR1. Five key hub genes (JUN, SQSTM1, STAT3, CD44 and TGFBR1) were further screened by ROC analysis. Subsequently, hsa-miR-20a-5p was identified as a potential key microRNA through the construction of the miRNA-gene network. The five key hub genes and rno-miR-20a-5p were further validated in the OVX rat model.
CONCLUSION: In summary, we first screened ferroptosis-related key hub genes linking hypoxia and osteoporosis. The findings suggest that JUN, SQSTM1β, STAT3β β, CD44ββ and TGFBR1 are significantly associated with OP and hypoxia, potentially serving as biomarkers for diseases linked to ferroptosis. Additionally, hsa-miR-20a-5p was identified as a crucial upstream regulator likely involved in the regulation of these genes simultaneously.
Key numbers
0.75
AUC Value of Key
showed AUC values for five key .
50
Total Identified
were identified from the intersection of hypoxia and osteoporosis datasets.
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