Our findings provide insight into the molecular framework of SONFH by identifying and characterising DE-ERGs. Analysis of the GSE123568 dataset revealed a large number of DE-ERGs, thereby enhancing our understanding of the cellular mechanisms triggered by steroid exposure. The study that originally generated the GSE123568 dataset focused on identifying dynamic biomarkers for different stages of non-traumatic ONFH (NONFH) using a transcriptional regulatory network17. Specifically, it highlighted the alterations in gene expression across various stages of the disease and identified key regulatory genes and pathways involved in NONFH progression. However, our study specifically investigates the role of ERS in SONFH, which was not addressed in the original study. Our research fills this gap by specifically investigating the intersection of ERS-related genes with the DEGs identified from the GSE123568 dataset. The identification of 1220 DEGs (754 upregulated and 466 downregulated) highlights the effects of steroids on gene expression in SONFH. Among these, the intersection with ERS-related genes resulting in 195 DE-ERGs suggests a significant subset of genes that may play crucial roles in the pathophysiology of SONFH through ERS mechanisms. This focused analysis provides a more detailed understanding of how ERS contributes to the cellular and molecular disruptions observed in SONFH, thereby offering new insights that were not explored in the original study.GO and KEGG enrichment analyses provided insight into the BP and pathways enriched for these DE-ERGs. The significant enrichment in BP (e.g., response to OS, peptide hormone signalling, and regulation of defence responses) aligns with pathological features of SONFH, including OS and inflammatory responses. GC-induced OS promotes apoptosis of osteocytes, primarily by increasing NOX-mediated production of ROS37. Similarly, the exacerbation of inflammatory processes by BMP-2–mediated downregulation of IL-34, contributes to osteoclast differentiation and the progression of ONFH38. Moreover, the CC enrichment in membrane microdomains and mitochondrial outer membranes suggests changes in cellular architecture that could influence signal transduction and metabolic processes crucial for cell survival and function. KEGG pathway analysis mapped DE-ERGs to pathways implicated in SONFH, such as lipid metabolism and atherosclerosis. ERS is important in this context because it can be exacerbated by intracellular lipid imbalances39. Dysfunctions in lipid metabolism can lead to the accumulation of misfolded proteins in the ER, triggering stress responses and ultimately apoptosis and bone-tissue degradation40. Moreover, the atherosclerotic processes identified by the pathway analysis indicate that lipid accumulation affects cellular health not only directly but also indirectly by impairing blood flow, thereby exacerbating the hypoxia that leads to osteonecrosis. In addition, identification of the NOD-like receptor signalling and FoxO signalling pathways underscores the roles of DE-ERGs in modulating immune responses and apoptosis41. This emphasises their potential as therapeutic targets and highlights the complex interplay between metabolic dysfunction and immune-regulatory mechanisms in SONFH.The PPI network analysis provided insight into the molecular interactions and pathways linked to the pathophysiology of SONFH. The critical clusters in the PPI network, which were related to inflammation, immune response, OS, and lipid metabolism, indicates steroids affect the activities and interactions of these pathways in SONFH. The cytoHubba plugin identified CXCL8, STAT3, IL1B, TLR4, PTGS2, TLR2, CASP1, CYBB, CAT, and HMOX1 as hub genes. These genes regulate cytokine signalling, immune responses, and stress mechanisms, which are important for maintaining cellular homeostasis and responding to external stressors including steroids. Their central positions in the network implicate them in both normal cellular functions and in pathological conditions, potentially driving the processes that lead to bone degradation in SONFH. GSEA of hub genes highlighted their effects on metabolic regulation, immune modulation, and cellular integrity in SONFH. These genes are multifunctional: CXCL8 affects metabolic and stress management processes, STAT3 influences cellular growth and response to infection, and IL1B integrates metabolic and inflammatory pathways, which are key in the pathogenesis of SONFH. TLR4 and PTGS2 modulate immune responses and apoptosis, suggesting that they have potential as therapeutic targets to reduce osteocyte damage. The involvement of CASP1 in metabolic processing and cellular clean-up, together with the functions of CYBB and TLR2 in immune homeostasis, highlight the complex interplay of responses to steroid stress. The functions of CAT and HMOX1 in metabolic pathways suggest strategies to enhance cellular resilience against SONFH.The regulation by miRNAs of the ERS-induced unfolded protein response suggests that their effects on pathways that govern cell survival or death influence cellular-stress outcomes42. Indeed, the fact that the mRNA-miRNA network centred on hub genes intersecting with ERS revealed the importance of miRNAs in SONFH. Among them, miR-23a modulates pathways critical for bone health. miR-23a inhibits osteogenesis by targeting LRP5, which is crucial for bone homeostasis, and icariin stimulates bone formation by modulating this pathway, suggesting therapeutic potential34,35. In addition, miR-23a modulates apoptosis and differentiation via LINC00473 in a PLGA hydrogel model, suggesting its importance for bone health36. Ganesan et al. found that downregulation of miR-23a led to upregulation of TLR2, enhancing the activity of autophagy-related pathways43. Lingam et al. reported that CXCL8 and miR-23a respond to inflammation and hypoxia44. Our predictions suggest that targeting miR-23a could improve SONFH outcomes by modulating TLR2 and CXCL8. These hub genes, which are significantly modulated by miRNAs, provide insight into the complex molecular mechanisms of SONFH and are potential targets for miRNA-based therapies.Next, we identified potential therapeutic agents that could modulate these hub genes. Several drugs, including dibenziodolium and N-acetyl-L-cysteine, which have anti-inflammatory and antioxidant activity, respectively, potentially interacted with key hub genes. Dibenziodolium reduces inflammation-driven exacerbation, and N-acetyl-L-cysteine alleviates OS and inflammation, which are important in the pathogenesis of SONFH37. Similarly, simvastatin shows therapeutic promise for SONFH because of its anti-inflammatory activity and inhibition of the GC receptor45. Curcumin inhibits M1-type macrophage infiltration and osteocyte apoptosis in the femoral head, which are linked to the development of SONFH46. In combination, these drugs show greater therapeutic efficacy for SONFH, and may improve patient outcomes by modulating the expression of hub genes.The significant correlations between immune cells and hub genes suggest immune modulation to be a pivotal component of therapeutic strategies. The positive correlation between activated mast cells, Tregs, and resting dendritic cells suggests that a protective regulatory mechanism is disrupted in SONFH. Therapeutic strategies that enhance Treg function or stabilise mast-cell activity could mitigate inflammatory processes in SONFH. Enhancing the function of Tregs to suppress inflammatory responses and pro-inflammatory cells (such as Th17) can restore the immune balance and reduce tissue damage, thereby promoting the repair and regeneration of bone tissue47. Conversely, the reduction in dendritic cells suggests impairment of immune priming, indicating that therapies boosting dendritic cell function could restore effective immune responses. He et al. showed that resting dendritic cells reduce osteonecrosis inflammation and promote bone repair by modulating antigen presentation and cytokine signalling, particularly by inhibiting the IL-17 pathway48.Macrophage polarisation into the pro-inflammatory M1 or anti-inflammatory M2 phenotype in response to environmental cues is pivotal for bone homeostasis, and its dysregulation can lead to inflammatory responses that disrupt bone metabolism49. Furthermore, activated NK cells and CD8+ T cells are components of the cell-mediated cytotoxic immune response, and are important for clearing damaged cells. However, their overactivation may lead to detrimental effects on bone tissue, indicating the need for a balanced immune response to maintain skeletal integrity and prevent exacerbation of osteonecrosis50,51. The positive correlations of TLR4, CYBB, and CASP1 with M1 macrophages suggest a pro-inflammatory phenotype that could exacerbate bone loss and turnover. Targeting these genes to modulate M1 macrophage activity may attenuate this pro-inflammatory state and induce a shift towards bone preservation and repair. Conversely, the negative correlations of TLR4, TLR2, IL1B, HMOX1, CYBB, and CASP1 with activated NK cells suggest a protective mechanism against the cytotoxicity typically induced by these immune cells. Similarly, the negative correlations of these hub genes, together with STAT3 and PTGS2, with CD8 T cells suggest a dampening of cytotoxic T-cell activity, which could reduce bone tissue damage in SONFH. Therefore, adjusting hub gene activity could correct the immune imbalance in SONFH, reducing pro-inflammatory effects and fortifying defences against overactive immune responses, a promising direction for targeted therapy development.Finally, we validated the expression levels of 10 hub genes using the GSE74089 dataset, confirming the accuracy of our findings from GSE123568. To further substantiate these findings and directly link them to our study’s focus on ERS-related genes in SONFH, we conducted qRT-PCR analysis on peripheral blood samples collected from three patients with SONFH and three healthy adults following steroid administration. This experimental design aimed to measure the expression levels of these hub genes in a clinical context, providing a more accurate reflection of their roles in SONFH and their association with ERS.The qRT-PCR process involved several critical steps: isolating total RNA from the blood samples, converting it into cDNA using reverse transcription, and then amplifying specific gene targets using quantitative PCR to measure their expression levels. This rigorous approach ensured that our results were both reliable and relevant to the pathophysiological conditions of SONFH, particularly concerning ERS. The qRT-PCR analysis yielded consistent results for four hub genes: STAT3, IL1B, TLR2, and CASP1. These genes were identified as significantly altered in SONFH patients compared to healthy controls, underscoring their potential as biomarkers and therapeutic targets. Researches have reported that, STAT3 exacerbates SONFH by promoting osteoclast differentiation52, IL1B polymorphisms affect genetic susceptibility53, TLR2 enhances BMSC-mediated angiogenesis and osteogenesis54, and CASP1 affects osteogenic functions via the ROS/NLRP3 pathway55. In an ROC curve analysis, the 10 genes had AUC values > 0.6, underscoring their diagnostic potential. This indicates that the other hub genes might still be involved in the pathophysiology of SONFH, even though their qRT-PCR results were not consistent.This validation step, by bridging bioinformatics predictions with clinical sample analysis, strengthens our findings and confirms the relevance of these hub genes in the pathophysiology of SONFH, specifically in the context of ERS. Thus, our qRT-PCR results not only support the bioinformatic data but also provide a tangible link to clinical outcomes and the role of ERS in SONFH, making them crucial for developing targeted therapies for this condition.
