Identification of Candidate Genes Associated with Steroid-Induced Osteonecrosis of The Femoral Head by Bioinformatics Based on GEO Database

Abstract

BACKGROUNDː Steroid-induced osteonecrosis of the femoral head (SONFH) is a progressive bone disorder and its characterized by femoral head collapse and hip joint dysfunction and the biomarkers of SONFH remain unclear. The purposes of this study are to identify the significant biological function and pathway involved in SONFH, and further to search the underlying mechanism of this pathway in SONFH. METHODSː The GSE123568 dataset obtained from the Gene Expression Omnibus (GEO) database and normalized using Robust Multiarray Averaging (RMA) methods. And the Gene set enrichment analysis (GSEA), Ingenuity pathway analysis (IPA), VarElect online tool, MalaCards database, miRWalk online tool, DIANA too, and Cytoscape were integrated for bioinformatics analyses.RESULTSː 6 biological processes and 4 KEGG pathways were enriched by GSEA, and 68 candidate genes were involved in these pathways. Besides, the canonical pathway and molecule function analysis by IPA, the results revealed that 10 canonical pathways and 12 candidate genes were identified, and 20 modules and 101 candidate genes were enriched by molecule function analysis. The above candidate genes were combined and filtered using the VarElect online tool. The filtered candidate genes were overlapped with another cluster of candidate genes from the MalaCards database to identify hub genes ACP5, TNF, MMP8. Based on the hub genes, the miRNAs were screened and overlapped to predict the lncRNAs. Total 7 miRNAs of ACP5, TNF, MMP8 were targeted 956 candidate lncRNAs.CONCLUSIONSː In summary, this study identified the hub candidate genes and pathways associated with SONFH progress, and constructed the ceRNA network based on the hub candidate genes. Our findings might provide the potential biomarkers of SONFH diagnosis and treatment.

ARG2, MAP4K5 and TSTA3 as Diagnostic Markers of Steroid-Induced Osteonecrosis of the Femoral Head and Their Correlation With Immune Infiltration

“…In order to reduce the number of key genes (choosing 91 hub genes form the brown module with 1258 genes), Wu et al (2021) set an overcritical cut-off value, which might indicate the possibility that some important candidate genes were missed. The results of Shile et al (2021) were different from our results due to them using different algorithms (Shile et al, 2021). However, ARG2 was also identified as a key gene for SONFH through ingenuity pathway analysis, which also indicates that our prediction was feasible by the integration strategy.…”

“…The main reason for the differences is that different values were applied as cut-off thresholds. Wu et al (2021) selected | log 2 (fold change)| > 1.5, while Shile et al (2021) set with a threshold false discovery rate < 0.25. These factors are bound to result in differences in conclusion.…”