基于自噬相关基因构建动脉粥样硬化诊断模型及潜在中药预测OA

The purpose of study is to construct a diagnostic model for atherosclerosis and predict its potential therapeutic Traditional Chinese Medicine based on single-cell and bulk transcriptomic data.his study utilized the GSE159677 dataset from the GEO database,containing single-cell transcriptomic profiles of 51,981 cells from atherosclerotic core plaques and matched proximal adjacent carotid tissues of three patients.Differential gene expression analysis was performed using the limma package in R.The intersection of DEGs and autophagy-related genes was used to obtain atherosclerosis-related autophagy-associated DEGs.GO and KEGG enrichment analyses were performed on the DEGs using R software.Based on the transcriptomic data from GSE100927 dataset,which includes 69 atherosclerosis samples and 35 controls,comprising 69 atherosclerosis samples and 35 controls was analyzed,LASSO regression was used to further select key DEGs and construct a diagnostic model.The intersection of DEGs and autophagy-related genes resulted in 25 genes.From this,FOS,HIF1A,HSPA5,HSPA8,P4HB,RAB11A,RGS19,TNFSF10,and VAMP were selected.The diagnostic model based on these 9 genes demonstrated excellent predictive performance,achieving an area under the curve(AUC)of 0.99(95%CI:0.976-1.0).Additionally,182 potential traditional Chinese medicine(TCM)candidates targeting these core genes were predicted.In conclusion,the results of this study provide novel insights into the diagnosis and treatment of atherosclerosis.