Objective: The purpose of the present study was to explore the signalling pathway in the development of early SONFH(Steroid-induced steonecrosis of femoral head) and to predict diagnostic biomarkers in peripheral blood of patients with SONFH. Method: Relevant transcriptome data was downloaded and the DEGs（Differently Expressed Genes） were screened by R software. ClusterProfiler was used for enrichment analysis of GO(Gene Ontology) and KEGG(Kyoto Encyclopaedia of Genes and Genomes), and STRING database was used for PPI(Protein Protein Interaction) analysis. Network X was used to visualize the network in Python. Result: In the study, 584 differential genes were found, including 294 up-regulated genes and 290 down-regulated genes. The main functions of DEG enrichment includered blood cell differentiation, cell protein catabolism, gas transportation, activation of myeloid leukocytes, phagocytosis, and inflammatory response. The main pathways involved in DEGs includemitophagy-animal, HTLV-1(Human T cell leukemia virus-1) infection, FOXO(Forkhead box O), phagocytosis, osteoclast differentiation, and cytokine–cytokine receptor interaction.The qRT-PCR results were consistent with the PPI networkanalysis results.Conclusion: It was found that DEGs related to SONFH, such as PRDX2(Peroxiredoxin 2), HP(Haptoglobin), MMP8, FPR2(Formyl Peptide Receptor 2), ITGAX(Integrin Subunit Alpha X), may promote the occurrence of SONFH by affecting factors such as redox pathway, inflammatory response, osteoblast and osteoclast structure and function, and whether it can become the key gene for early diagnosis and treatment of the disease needs further study.

The present study aimed to explore the signaling pathways involved in development of early steroid-induced osteonecrosis of the femoral head (SONFH) and identify diagnostic biomarkers regulating peripheral blood in SONFH patients. We downloaded transcriptome data and identified differentially expressed genes (DEGs) using the R software. We used ClusterProfiler to perform enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and analyzed protein–protein interactions using the STRING database. Network X was used to visualize the networks in Python. A total of 584 DEGs were identified, of which 294 and 290 were upregulated and downregulated, respectively. Enrichment analysis showed that the DEGs were mainly involved in red blood cell differentiation, cell protein catabolism, gas transportation, activation of myeloid leukocytes, phagocytosis, and inflammatory response. Pathway analysis revealed that these DEGs were involved in regulation of mitophagy-animal, human T-cell leukemia virus-1 infection, Forkhead box O, phagocytosis, osteoclast differentiation, and cytokine–cytokine receptor interaction. Quantitative real-time polymerase chain reaction results were consistent with findings from protein–protein interaction network analysis. Several genes, including peroxiredoxin 2, haptoglobin, matrix metallopeptidase 8, formyl peptide receptor 2, and integrin subunit alpha X, promote SONFH occurrence by regulating the redox, inflammatory response, and osteoblast and osteoclast structure and function pathways. They may be important targets for designing approaches for early diagnosis and treatment of SONFH.

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