Atherosclerosis is a common and significant cardiovascular condition that frequently goes undiagnosed by conventional diagnostic and treatment techniques until it reaches a more advanced stage. This challenge impedes the capacity to apply early detection and intervention measures. As a result, the creation of innovative and more accurate biomarkers is critically important. The study first recognizes genes associated with macrophages through single‐cell analysis, investigating their functions. Subsequently, various machine learning approaches are utilized to identify significant regulatory genes related to macrophages. In addition, molecular docking studies are performed to evaluate the binding affinity of these crucial markers with therapeutics targeting atherosclerosis. The ImmuCellAI platform is also utilized to assess immune cell scores in atherosclerotic samples, aiding in the examination of connections between vital diagnostic markers and immune cells. Finally, the expression changes of the selected key genes are confirmed using qRT‐PCR and Western blot methods. Through analyses at the single‐cell level and differential assessments, we discovered 58 genes related to macrophages that exhibited differential expression. Functional evaluations indicated a strong correlation between these genes and the immune microenvironment. By conducting cluster analysis, we assessed how different subgroups of patients with atherosclerosis respond to immunotherapy. Utilizing techniques such as XGBoost, random forest, and the GOsemsim algorithm, we pinpointed five crucial diagnostic markers. Studies on molecular docking validated that these important markers could act as potential drug targets for atherosclerosis. Finally, our experimental analysis revealed a significant overexpression of these five diagnostic markers in tissues affected by atherosclerosis. This research introduces novel diagnostic indicators associated with macrophages in atherosclerosis and emphasizes their potential as targets for therapies related to the immune system.
Yu et al. (Wed,) studied this question.