ABSTRACT This study aims to screen potential regulatory targets for atherosclerosis (AS) through bioinformatics and explore the mechanism of these targets in ox‐LDL‐induced injury in HUVECs, thereby providing novel therapeutic targets for AS. The GEO dataset GSE43292 was obtained. Differentially expressed genes were screened using the limma package. AS‐related genes were identified via LASSO regression and SVM algorithms. ssGSEA was performed to detect relative immune cell expression, followed by correlation analysis between AS‐related genes and immune cells. MPP6 and NEGR1 were screened as AS‐related genes. MPP6 and NEGR1 showed negative correlations with most immune cells. After 100 μg/mL ox‐LDL treatment, HUVECs showed reduced HUVEC viability, increased apoptosis, enhanced LDH release, and upregulated TNF‐α, IL‐6, and IL‐1β. Protein–protein interaction networks of predicted transcription factors were constructed, and scores were assigned via the maximal clique centrality method. The results identified EP300 as the transcription factor with the highest score. MPP6, NEGR1, and EP300 were detected by RT‐qPCR and Western blot. Overexpression of MPP6/NEGR1 alleviated ox‐LDL‐induced HUVEC injury. EP300 bound to MPP6/NEGR1 promoters to suppress their expression, and EP300 knockdown alleviated ox‐LDL‐induced HUVEC injury. In conclusion, EP300 exacerbates ox‐LDL‐induced HUVEC injury by binding to MPP6/NEGR1 promoters and suppressing their expression.
Yan et al. (Wed,) studied this question.