ArticleComputational and mathematical methods in medicine2021
The Identification of Candidate Biomarkers and Pathways in Atherosclerosis by Integrated Bioinformatics Analysis.
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 18 citations in OpenAlex.
- Identification of atherosclerosis biomarkers through metabolic signatures and immune microenvironment analysis.Journal of cardiothoracic surgery · 2026Article
- Isoorientin Ameliorates Macrophage Pyroptosis and Atherogenesis by Reducing KDM4A Levels and Promoting SKP1-Cullin1-F-box E3 Ligase-mediated NLRP3 Ubiquitination.Inflammation · 2025Article
- Identifying PTAFR as a hub gene in atherosclerosis: implications for NETosis and disease progression.Human genomics · 2024Article
- Unveiling Atherosclerotic Plaque Heterogeneity and SPP1Journal of inflammation research · 2024Article
- In silico based analysis to explore genetic linkage between atherosclerosis and its potential risk factors.Biochemistry and biophysics reports · 2023Article
- Associations of genetic markers of diabetes mellitus with carotid atherosclerosis: a community-based case-control study.Cardiovascular diabetology · 2023Article
- Identification of immune-related genes in diagnosing atherosclerosis with rheumatoid arthritis through bioinformatics analysis and machine learning.Frontiers in immunology · 2023Article
- Genome-wide associated variants of subclinical atherosclerosis among young people with HIV and gene-environment interactions.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
- Proteomics-based evaluation of the mechanism underlying vascular injury via DNA interstrand crosslinks, glutathione perturbation, mitogen-activated protein kinase, and Wnt and ErbB signaling pathways induced by crotonaldehyde.Clinical proteomics · 2022Article
- Multifaceted Roles of the E3 Ubiquitin Ligase RING Finger Protein 115 in Immunity and Diseases.Frontiers in immunology · 2022Review
- Integrated Bioinformatic Analysis of the Shared Molecular Mechanisms Between Osteoporosis and Atherosclerosis.Frontiers in endocrinology · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAtherosclerosis (AS) is a type of yellow substance containing cholesterol in the intima of large and middle arteries, which is mostly caused by fat metabolism disorders and neurovascular dysfunction. MATERIALS AND
methodsThe GSE100927 data got analyzed to find out the differentially expressed genes (DEGs) using the limma package in R software. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the DEGs were assessed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) visualized the Protein-Protein Interaction (PPI) network of the aggregated DEGs. GSEA software was used to verify the biological process.
resultWe screened 1574 DEGs from 69 groups of atherosclerotic carotid artery and 35 groups of control carotid artery, including 1033 upregulated DEGs and 541 downregulated DEGs. DEGs of AS were chiefly related to immune response, Epstein-Barr virus infection, vascular smooth muscle contraction, and cGMP-PKG signaling pathway. Through PPI networks, we found that the hub genes of AS were PTAFR, VAMP8, RNF19A, VPRBP, RNF217, KLHL42, NEDD4, SH3RF1, UBE2N, PJA2, RNF115, ITCH, SKP1, FBXW4, and UBE2H. GSEA analysis showed that GSE100927 was concentrated in RIPK1-mediated regulated necrosis, FC epsilon receptor fceri signaling, Fceri-mediated NF KB activation, TBC rabgaps, TRAF6-mediated induction of TAK1 complex within TLR4 complex, and RAB regulation of trafficking.
conclusionOur analysis reveals that immune response, Epstein-Barr virus infection, and so on were major signatures of AS. PTAFR, VAMP8, VPRBP, RNF217, KLHL42, and NEDD4 might facilitate the AS tumorigenesis, which could be new biomarkers for diagnosis and therapy of AS.
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