Bioinformatics analysis and experimental validation of mitochondrial autophagy genes in knee osteoarthritis

Abstract

Abstract Background Mitochondrial autophagy is closely related to the pathogenesis of osteoarthritis, In order to explore the role of mitochondrial autophagy related genes in Knee Osteoarthritis (KOA) and its molecular mechanism. Methods KOA-related transcriptome data were extracted from the Gene Expression Omnibus (GEO) database, and the differences were analyzed. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were implemented to explore the function of differentially expressed mitochondrial autophagy genes (DEMGs). The STRING website was used to construct a protein-protein interaction (PPI) network among DEMGs to identify hub DEMGs. Support vector machine recursive feature elimination (SVM-RFE) method was used to construct the hub DEMG diagnosis model. Receiver operating characteristic (ROC) curve was painted to access the diagnostic value of hub DEMGs. After the immune infiltration analysis was completed, biomarkers were obtained through correlation analysis of differential immune cells and hub DEMGs. Results In total, fifteen DEMGs were screened in patients with KOA. Subsequent enrichment analyses showed that these DEMG strains were mainly enriched in the mitophagy-animal, shigellosis, autophagy-animal and FoxO signal pathways. In addition, 5 hub DEMGs (BNIP3L, BNIP3, MAP1LC3B, ULK1 and FOXO3) were identified by SVM-RFE. The area under the curve (AUC) value of BNIP3 and FOXO3 was greater than 0.75 in the training and validation sets, indicating the decent diagnostic value for KOA. Immune-infiltration and correlation analysis showed that BNIP3 and FOXO3 were significantly correlated with three different immune cells, including primary B cells, M0 macrophage, and M2 macrophage. Thus, BNIP3 and FOXO3 were treated as biomarkers for the diagnosis of KOA. Conclusion In conclusion, two biomarkers (BNIP3 and FOXO3) related to mitochondrial autophagy were acquired between KOA and nomal samples by bioinformatics analysis, which might supply a new insight for the treatment and evaluation of KOA.