Yu Chenchen, Wang Haoran, Xu Huiting, Kang Peipei, Shao Jingjing, Zhang Hui
Department of Clinical Laboratory Medicine, Affiliated Tumor Hospital of Nantong University, Nantong, Jiangsu, China.
Department of Immunology, School of Basic Medical Sciences, Nantong University, Nantong, Jiangsu, China.
Hum Mutat. 2025 Aug 20;2025:9034896. doi: 10.1155/humu/9034896. eCollection 2025.
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.
动脉粥样硬化是一种常见且严重的心血管疾病，在传统诊断和治疗技术下，它常常在病情发展到更晚期时才被诊断出来。这一挑战阻碍了早期检测和干预措施的实施能力。因此，创建创新且更准确的生物标志物至关重要。该研究首先通过单细胞分析识别与巨噬细胞相关的基因，并研究它们的功能。随后，利用各种机器学习方法来识别与巨噬细胞相关的重要调控基因。此外，进行分子对接研究以评估这些关键标志物与针对动脉粥样硬化的治疗药物的结合亲和力。ImmuCellAI平台也被用于评估动脉粥样硬化样本中的免疫细胞评分，有助于检查重要诊断标志物与免疫细胞之间的联系。最后，使用qRT-PCR和蛋白质印迹方法确认所选关键基因的表达变化。通过单细胞水平分析和差异评估，我们发现了58个与巨噬细胞相关且表现出差异表达的基因。功能评估表明这些基因与免疫微环境之间存在很强的相关性。通过进行聚类分析，我们评估了动脉粥样硬化患者的不同亚组对免疫疗法的反应。利用XGBoost、随机森林和GOsemsim算法等技术，我们确定了五个关键诊断标志物。分子对接研究证实这些重要标志物可作为动脉粥样硬化的潜在药物靶点。最后，我们的实验分析显示这五个诊断标志物在受动脉粥样硬化影响的组织中显著过表达。这项研究引入了与动脉粥样硬化中巨噬细胞相关的新型诊断指标，并强调了它们作为免疫系统相关治疗靶点的潜力。
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