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Identification of potential autophagy-related genes in steroid-induced osteonecrosis of the femoral head via bioinformatics analysis and experimental verification.
- Source :
- Journal of Orthopaedic Surgery & Research; 2/12/2022, Vol. 17 Issue 1, p1-13, 13p
- Publication Year :
- 2022
-
Abstract
- Purpose: Steroid-induced osteonecrosis of the femoral head (SONFH) is a refractory orthopaedic hip joint disease that occurs in young- and middle-aged people. Previous experimental studies have shown that autophagy might be involved in the pathological process of SONFH, but the pathogenesis of autophagy in SONFH remains unclear. We aimed to identify and validate the key potential autophagy-related genes involved in SONFH to further illustrate the mechanism of autophagy in SONFH through bioinformatics analysis. Methods: The GSE123568 mRNA expression profile dataset, including 10 non-SONFH (following steroid administration) samples and 30 SONFH samples, was downloaded from the Gene Expression Omnibus (GEO) database. Autophagy-related genes were obtained from the Human Autophagy Database (HADb). The autophagy-related genes involved in SONFH were screened by intersecting the GSE123568 dataset with the set of autophagy genes. The differentially expressed autophagy-related genes involved in SONFH were identified with R software. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially expressed autophagy-related genes involved in SONFH were conducted by using R software. Then, the correlations between the expression levels of the differentially expressed autophagy-related genes involved in SONFH were confirmed with R software. Moreover, the protein–protein interaction (PPI) network was analysed by using the Search Tool for the Retrieval of Interacting Genes (STRING), significant gene cluster modules were identified with the MCODE Cytoscape plugin, and hub genes among the differentially expressed autophagy-related genes involved in SONFH were screened by using the CytoHubba Cytoscape plugin. Finally, the expression levels of the hub genes of the differentially expressed autophagy-related genes involved in SONFH were validated in hip articular cartilage specimens from necrotic femur heads (NFHs) by using the GSE74089 dataset and further verification by qRT-PCR. Results: A total of 34 differentially expressed autophagy-related genes were identified between the peripheral blood samples of SONFH patients and non-SONFH patients based on the defined criteria, including 25 upregulated genes and 9 downregulated genes. The GO and KEGG pathway enrichment analyses revealed that these 34 differentially expressed autophagy-related genes involved in SONFH were particularly enriched in death domain receptors, the FOXO signalling pathway and apoptosis. Correlation analysis revealed significant correlations among the 34 differentially expressed autophagy-related genes involved in SONFH. The PPI results demonstrated that the 34 differentially expressed autophagy-related genes interacted with each other. Ten hub genes were identified by using the MCC algorithms of CytoHubba. The GSE74089 dataset showed that TNFSF10, PTEN and CFLAR were significantly upregulated while BCL2L1 was significantly downregulated in the hip cartilage specimens, which was consistent with the GSE123568 dataset. TNFSF10, PTEN and BCL2L1 were detected with consistent expression by qRT-PCR. Conclusions: Thirty-four potential autophagy-related genes involved in SONFH were identified via bioinformatics analysis. TNFSF10, PTEN and BCL2L1 might serve as potential drug targets and biomarkers because they regulate autophagy. These results expand the autophagy-related understanding of SONFH and might be useful in the diagnosis and prognosis of SONFH. [ABSTRACT FROM AUTHOR]
- Subjects :
- PROTEIN metabolism
EXPERIMENTAL design
REVERSE transcriptase polymerase chain reaction
OSTEONECROSIS
AUTOPHAGY
STEROIDS
HIP joint
FEMUR head
BIOINFORMATICS
GENE expression
CELLULAR signal transduction
MESSENGER RNA
DESCRIPTIVE statistics
DATA analysis software
ONTOLOGIES (Information retrieval)
STATISTICAL correlation
POLYMERASE chain reaction
ALGORITHMS
DISEASE risk factors
Subjects
Details
- Language :
- English
- ISSN :
- 1749799X
- Volume :
- 17
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Journal of Orthopaedic Surgery & Research
- Publication Type :
- Academic Journal
- Accession number :
- 155180776
- Full Text :
- https://doi.org/10.1186/s13018-022-02977-x