A comprehensive bioinformatics algorithm and experiment-based analysis illustrates the role of PANoptosis-based subtypes in atherosclerosis and new diagnostic biomarkers

Abstract

Abstract As a chronic inflammatory disease, atherogenesis and ischemia events are primarily affected by inflammation in atherosclerosis (AS). PANoptosis has been implicated in many human systemic disorders, including infection, cancer, neurodegeneration, and inflammation. On the other hand, little is understood about PANoptosis's function in atherosclerosis. The GSE100927 dataset has been divided using a consensus clustering approach into two PANoptosis-related subtypes based on the expression of PANoptosis-related genes (PRGs). We screened 36 PANoptosis-associated genes using the limma package and weighted gene co-expression network analysis (WGCNA), and then we enriched the PANoptosis-associated genes using ClueGO software. The PPI network was built using the STRING database and Cytoscape software, and the enriched genes were identified using LASSO regression. As atherosclerosis diagnostic markers, CCL3, ACP5, and HMOX1 have been identified and verified in the GSE43292 dataset. The variations in immune infiltration between AS and control samples and the gene clusters connected to PANoptosis were compared using the "CIBERSORT" package. The three diagnostic genes' expression levels were noticeably greater in the AS group. The three diagnostic genes were predominantly connected to macrophages, according to correlation analysis and single-cell analysis. The high expression of ACP5 and HMOX1 in RAW264.7 macrophages treated with OX-LDL was confirmed by PCR. Our study identified ACP5 and HMOX1 as diagnostic genes for AS that may be associated with PANoptosis.ACP5 and HMOX1 may be involved in the pathogenesis of AS by regulating macrophage PANoptosis.