The pathophysiological mechanisms of intermittent claudication (IC) progression to chronic limb-threatening ischemia (CLTI) are still vague and which of patients with IC will become CLTI are unknown. This study aimed to investigate the key molecules and pathways mediating IC progression to CLTI by a quantitative bioinformatic analysis of a public RNA-sequencing database of patients with peripheral artery disease (PAD) to screen biomarkers discriminating IC and CLTI.
The GSE120642 dataset was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between IC and CLTI tissues were analyzed using the “edgeR” packages of R. The Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to explore the functions of DEGs. Protein–protein interaction (PPI) networks were established by the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized by Cytoscape software. Hub genes were selected by plugin cytoHubba. Gene set enrichment analysis was performed and the receiver operating characteristic curves were used to evaluate the predictive values of hub genes.
A total of 137 upregulated and 21 downregulated DEGs were identified. Functional enrichment clustering analysis revealed a significant association between DEGs and the complement and coagulation cascade pathways. The PPI network was constructed with 155 nodes and 105 interactions. The most significantly enriched pathway was complement activation. C1QB, C1QA, C1QC, C4A, and C1R were identified and validated as hub genes due to the high degree of connectivity. The area under the curve values for the five hub genes were greater than 0.95, indicating high accuracy for discriminating IC and CLTI.
The complement activation pathway is associated with IC progression to CLTI. C1QB, C1QA, C1QC, C4A, and C1R might serve as potential early biomarkers of CLTI.