Immune-Associated Gene Signatures and Subtypes to Predict the Progression of Atherosclerotic Plaques Based on Machine Learning - Yang, Yujia; Yi, Xu; Cai, Yue; Zhang, Yuan; Xu, Zhiqiang (Frontiers in Pharmacology, 2022)
Objective: Experimental and clinical evidence suggests that atherosclerosis is a chronic inflammatory disease. Our study was conducted for uncovering the roles of immune-associated genes during atherosclerotic plaque progression. Methods: Gene expression profiling of GSE28829, GSE43292, GSE41571 and GSE120521 datasets was retrieved from the GEO database. Three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine-recursive feature elimination (SVM-RFE) were utilized for screening characteristic genes among atherosclerotic plaque progression- and immune-associated genes. ROC curves were conducted for estimating the diagnostic efficacy. Immune cell infiltrations were estimated via ssGSEA and immune checkpoints were quantified. CMap analysis was implemented to screen potential small molecule compounds. Atherosclerotic plaque specimens were classified with consensus clustering approach. Results: Seven characteristic genes (TNFSF13B, CCL5, CCL19, ITGAL, CD14, GZMB, and BTK) were identified, which enabled to predict the progression of atherosclerotic plaques. Higher immune cell infiltrations and immune checkpoint expression were found in advanced-stage than early-stage atherosclerotic plaques, and were positively linked to characteristic genes. Patients could clinically benefit from the characteristic gene-based nomogram. Several small molecular compounds were predicted based on the characteristic genes. Two subtypes of C1 immune subtype and C2 non-immune subtype were classified across atherosclerotic plaques. Characteristic genes presented higher expression in C1 than C2 subtypes. Conclusion: Our findings provide several promising atherosclerotic plaque progression- and immune-associated genes as well as immune subtypes, which might enable to assist the design of more accurately tailored cardiovascular immunotherapy.