ArticleBioMed research international2017
Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis.
Article in BioMed research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 56 citations in OpenAlex.
- The Role of miRNA-146a and Proinflammatory Cytokines in Carotid Atherosclerosis.BioMed research international · 2020Trial
- Coordinated inflammatory macrophage and vascular smooth muscle cell remodeling signatures in human atherosclerosis: An integrative single-cell and bulk transcriptomic analysis.Journal of cell communication and signaling · 2026Article
- Evaluation of Suitable Reference Gene During the Development of Paired or Unpaired FemalePathogens (Basel, Switzerland) · 2025Article
- Identification of Hub Genes and Immune Infiltration in Coronary Artery Disease: A Risk Prediction Model.Journal of inflammation research · 2024Article
- Incidence of microvascular dysfunction is increased in hyperlipidemic mice, reducing cerebral blood flow and impairing remote memory.Frontiers in endocrinology · 2024Article
- Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review.Applied bionics and biomechanics · 2024Article
- ITGB2 is a central hub-gene associated with inflammation and early fibro-atheroma development in a swine model of atherosclerosis.Atherosclerosis plus · 2023Article
- Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis.BMC bioinformatics · 2023Article
- Exploring the molecular underpinning of psoriasis and its associated comorbidities through network approach: cross talks of genes and pathways.3 Biotech · 2023Article
- Article
- Identification of hub genes and regulatory networks in histologically unstable carotid atherosclerotic plaque by bioinformatics analysis.BMC medical genomics · 2022Article
- Protein-Protein Interaction (PPI) Network of Zebrafish Oestrogen Receptors: A Bioinformatics Workflow.Life (Basel, Switzerland) · 2022Review
- Construction of genetic classification model for coronary atherosclerosis heart disease using three machine learning methods.BMC cardiovascular disorders · 2022Article
- miR-22-3p as a potential biomarker for coronary artery disease based on integrated bioinformatics analysis.Frontiers in genetics · 2022Article
- Exploration of the Crucial Genes and Molecular Mechanisms Mediating Atherosclerosis and Abnormal Endothelial Shear Stress.Disease markers · 2022Article
- Potential Biomarkers of Acute Ischemic Stroke Etiology Revealed by Mass Spectrometry-Based Proteomic Characterization of Formalin-Fixed Paraffin-Embedded Blood Clots.Frontiers in neurology · 2022Article
- Regulatory T Cell-Related Gene Biomarkers in the Deterioration of Atherosclerosis.Frontiers in cardiovascular medicine · 2021Article
- Transcriptomic landscaping of core genes and pathways of mild and severe psoriasis vulgaris.International journal of molecular medicine · 2021Article
- Weighted Gene Co-expression Network Analysis Identifies Crucial Genes Mediating Progression of Carotid Plaque.Frontiers in physiology · 2021Article
- Network Pharmacology to Explore the Molecular Mechanisms ofFrontiers in pharmacology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCoronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human.
methodsGene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO), including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs) were analyzed.
results42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI) networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton.
conclusionThe present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.