Transcriptome combined with single cell to explore hypoxia-related biomarkers in osteoarthritis

Abstract

Osteoarthritis (OA) is a prevalent degenerative condition among the elderly on a global scale. Research has demonstrated that hypoxia can promote chondrocyte apoptosis and autophagy leading to OA. Hence, it was vital to screen the hypoxia related biomarkers in OA. We introduced transcriptome data to screen out differentially expressed genes (DEGs) in GSE114007 and GSE57218 (OA samples vs control samples). We performed differential expression analysis in key annotated cell to obtain differentially expressed marker genes at the single-cell level (GSE169454). Venn diagram was executed to identify hypoxia related differentially expressed genes (HR-DEGs) associated with OA. Further, feature genes were obtained through the application of least absolute shrinkage and selection operator (LASSO) regression and the Random Forest (RF) algorithm. Receiver operating characteristic (ROC) and expression level analysis were used to identify hypoxia related biomarkers in OA. We further performed immune infiltration and gene set enrichment analysis (GSEA) based on hypoxia related biomarkers. Finally, we analyzed the expression of biomarkers in single-cell level. We identified 2351 DEGs associated with OA. At the single-cell level, 242 differentially expressed marker genes were obtained. 12 HR-DEGs were retained venn diagram. Subsequently, three hypoxia related biomarkers (ADM, DDIT3 and MAFF) were identified. Moreover, we got 15 significantly different immune cells. Finally, we found a lower expression of ADM, DDIT3 and MAFF in OA group compared to the control group in ECs. Overall, we obtained three hypoxia related biomarkers (ADM, DDIT3 and MAFF) associated with OA, which established a theoretical basis for addressing OA.