Ye Chaowen, Zhao Yunli, Yu Wei, Huang Rongzhong, Hu Tianyang
Precision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Chongqing Municipality Clinical Research Center for Geriatrics and Gerontology, Chongqing, China.
Hum Genomics. 2024 Dec 21;18(1):139. doi: 10.1186/s40246-024-00708-3.
Atherosclerosis (AS) is a major cause of cardiovascular diseases and neutrophil extracellular traps (NETs) may be actively involved in the development of atherosclerosis. Identifying key biomarkers in this process is essential for developing targeted treatments for AS.
We performed bioinformatics analysis using a NETosis-related gene (NRGs) set and three AS datasets (GSE100927, GSE21545, and GSE159677). Differential expression analysis and machine learning techniques (random forest and SVM-RFE) were used to screen for key NRGs. Functional enrichment analysis was conducted using GO and KEGG pathways. The expression and role of PTAFR and NETs in the mouse AS model were validated through histology, immunofluorescence, flow cytometry, and Western blot analysis. The regulatory relationship between PTAFR and NETs was confirmed by siRNA and antagonist intervention targeting PTAFR.
We identified 24 differentially expressed NRGs in AS. Random Forest and SVM-RFE analyses highlighted PTAFR as a key gene. Prognostic analysis revealed PTAFR significantly impacts ischemic events in AS patients. WB and immunofluorescence confirmed increased levels of NETs and PTAFR in the mouse AS model. Single-cell analysis, flow cytometry, and immunofluorescence revealed that PTAFR is primarily distributed in macrophages and neutrophils. Cellular experiments further confirmed that PTAFR regulates NETs formation.
PTAFR is an important regulatory factor for NET formation in AS, influencing the progression and prognosis of atherosclerosis. Targeting PTAFR may provide new therapeutic strategies for AS.
动脉粥样硬化(AS)是心血管疾病的主要病因,中性粒细胞胞外陷阱(NETs)可能积极参与动脉粥样硬化的发展。识别这一过程中的关键生物标志物对于开发AS的靶向治疗至关重要。
我们使用与NETosis相关的基因(NRGs)集和三个AS数据集(GSE100927、GSE21545和GSE159677)进行生物信息学分析。使用差异表达分析和机器学习技术(随机森林和支持向量机递归特征消除法)筛选关键NRGs。使用GO和KEGG通路进行功能富集分析。通过组织学、免疫荧光、流式细胞术和蛋白质印迹分析验证了PTAFR和NETs在小鼠AS模型中的表达及作用。通过靶向PTAFR的小干扰RNA(siRNA)和拮抗剂干预证实了PTAFR与NETs之间的调控关系。
我们在AS中鉴定出24个差异表达的NRGs。随机森林和支持向量机递归特征消除法分析突出了PTAFR作为关键基因。预后分析显示PTAFR显著影响AS患者的缺血事件。蛋白质印迹和免疫荧光证实小鼠AS模型中NETs和PTAFR水平升高。单细胞分析、流式细胞术和免疫荧光显示PTAFR主要分布在巨噬细胞和中性粒细胞中。细胞实验进一步证实PTAFR调节NETs的形成。
PTAFR是AS中NET形成的重要调节因子,影响动脉粥样硬化的进展和预后。靶向PTAFR可能为AS提供新的治疗策略。