ArticleCardiovascular therapeutics2020
Six-Gene Signature Associated with Immune Cells in the Progression of Atherosclerosis Discovered by Comprehensive Bioinformatics Analyses.
Article in Cardiovascular therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 44 citations in OpenAlex.
- Early diagnostic biomarkers for acute myocardial infarction unveiled by metabolomics, Mendelian randomization, and machine learning.Molecular biomedicine · 2026Article
- Predicting the ferroptosis-associated gene targets in atherosclerosis by integrating GWAS and eQTL studies summary data.Medicine · 2025Article
- Ecdysterone Alleviates Atherosclerosis by Inhibiting NCF2 and Inhibiting Ferroptosis Mediated by the PI3K/Akt/Nrf2 Pathway.Journal of cellular and molecular medicine · 2025Article
- Integrative multi-omics analysis of IFNγ-induced macrophages and atherosclerotic plaques reveals macrophage-dependent STAT1-driven transcription in atherosclerosis.Frontiers in immunology · 2025Article
- Searching for Hub Genes of Quince-Basil Co-Administration Against Atherosclerosis Using Bioinformatics Analysis and Experimental Validation.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Correlation between Complement C1q A Chain (Iranian journal of public health · 2024Article
- Costimulatory and Coinhibitory Immune Checkpoints in Atherosclerosis: Therapeutic Targets in Atherosclerosis?JACC. Basic to translational science · 2024Review
- T cell expressions of aberrant gene signatures and Co-inhibitory receptors (Co-IRs) as predictors of renal damage and lupus disease activity.Journal of biomedical science · 2024Article
- Article
- ITGB2 is a central hub-gene associated with inflammation and early fibro-atheroma development in a swine model of atherosclerosis.Atherosclerosis plus · 2023Article
- Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID-19: Insights from bioinformatic analyses.Immunity, inflammation and disease · 2023Article
- Identification of key genes and pathways in atherosclerosis using integrated bioinformatics analysis.BMC medical genomics · 2023Article
- The tetraspanin transmembrane protein CD53 mediates dyslipidemia and integrates inflammatory and metabolic signaling in hepatocytes.The Journal of biological chemistry · 2023Article
- Transcriptome-wide analysis reveals the coregulation of RNA-binding proteins and alternative splicing genes in the development of atherosclerosis.Scientific reports · 2023Article
- Diversity of arterial cell and phenotypic heterogeneity induced by high-fat and high-cholesterol diet.Frontiers in cell and developmental biology · 2023Article
- Integrated analysis of miRNA-mRNA regulatory network and functional verification of miR-338-3p in coronary heart disease.Functional & integrative genomics · 2022Article
- Article
- Single-cell transcriptomic, transcriptomic, and metabolomic characterization of human atherosclerosis.Annals of translational medicine · 2022Article
- Identification of diagnostic biomarkers and therapeutic targets in peripheral immune landscape from coronary artery disease.Journal of translational medicine · 2022Article
- Identifying potential signatures for atherosclerosis in the context of predictive, preventive, and personalized medicine using integrative bioinformatics approaches and machine-learning strategies.The EPMA journal · 2022Article
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs a multifaceted disease, atherosclerosis is often characterized by the formation and accumulation of plaque anchored to the inner wall of the arteries and causes some cardiovascular diseases and vascular embolism. Numerous studies have reported on the pathogenesis of atherosclerosis. However, fewer studies focused on both genes and immune cells, and the correlation of genes and immune cells was evaluated via comprehensive bioinformatics analyses.
methods29 samples of atherosclerosis-related gene expression profiling, including 16 human advanced atherosclerosis plaque (AA) and 13 human early atherosclerosis plaque (EA) samples from the Gene Expression Omnibus (GEO) database, were analyzed to get differentially expressed genes (DEGs) and the construction of protein and protein interaction (PPI) networks. Besides, we detected the relative fraction of 22 immune cell types in atherosclerosis by using the deconvolution algorithm of "cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)." Ultimately, based on the significantly changed types of immune cells, we executed the correlation analysis between DEGs and immune cells to discover the potential genes and pathways associated with immune cells.
resultsWe identified 17 module genes and 6 types of significantly changed immune cells. Correlation analysis showed that the relative percentage of T cell CD8 has negative correlation with the
conclusionsIn this study, we suggested that the progression of atherosclerosis might be related to
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