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Updated: Mar 12, 2026

Quantitative Analysis of Cellular Composition in Advanced Atherosclerotic Lesions of Smooth Muscle Cell Lineage-Tracing Mice
Published on: February 20, 2019
Comprehensive Analysis of Bulk RNA-seq, Machine Learning, Mendelian Randomization, and Single-Cell Sequencing
Yongchao Yu1, Lan Wang1, Tianhui Wang1
1Comprehensive Ward, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China.
Abstract:
Growing evidence implicates solute carrier (SLC) superfamily in atherosclerosis (AS) pathogenesis. This study identified SLC22A3 as a novel AS biomarker and therapeutic target using multi-omics analysis. Integrating WGCNA and machine learning (LASSO, SVM-RFE, XGBoost, Random Forest) on bulk RNA-seq (GSE43292) pinpointed SLC22A3. External datasets (GSE28829, GSE163154) confirmed significant SLC22A3 downregulation in AS (P < 0.001) and high diagnostic accuracy (AUC > 0.9). SMR analysis revealed a causal genetic link between SLC22A3 expression and reduced AS risk (P < 0.05, OR = 0.512 (95% CI: 0.280-0.939))). scRNA-seq showed SLC22A3 specifically expressed in smooth muscle cells (SMCs), significantly reduced in symptomatic patients. Molecular docking and molecular dynamics simulation nominated six FDA-approved drugs as potential SLC22A3-targeting therapeutics. Experimental validation further confirmed the significant downregulation of SLC22A3 at both mRNA and protein levels. SLC22A3 is a promising diagnostic biomarker and therapeutic target for AS, functionally linked to SMCs.
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