ArticleAmerican journal of translational research2021
Identification of candidate targets for the diagnosis and treatment of atherosclerosis by bioinformatics analysis.
Article in American journal of translational research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 16 citations in OpenAlex.
- NEDD4L-mediated Gasdermin D and E ubiquitination regulates cell death and tissue injury.Cell death and differentiation · 2026Article
- Comprehensive landscape and future perspectives of exosomal circular RNAs in cardiovascular disease.Frontiers in pharmacology · 2026Review
- Review
- Circ_0026218 ameliorates oxidized low-density lipoprotein-induced vascular endothelial cell dysfunction by regulating miR-188-3p/TLR4/NF-κB pathway.Cardiovascular drugs and therapy · 2024Article
- Clinical value of retinol binding protein, C-reactive protein and urine microalbumin in patients with chronic renal disease and ischemic cerebrovascular disease.American journal of translational research · 2024Article
- The role of splicing events in the inflammatory response of atherosclerosis: molecular mechanisms and modulation.Frontiers in immunology · 2024Review
- The F-box-only protein 44 regulates pregnane X receptor protein level by ubiquitination and degradation.Acta pharmaceutica Sinica. B · 2023Article
- Expression Profiles of Long Non-Coding RNAs in the Articular Cartilage of Rats Exposed to T-2 Toxin.International journal of molecular sciences · 2023Article
- Identification of potential diagnostic biomarkers of atherosclerosis based on bioinformatics strategy.BMC medical genomics · 2023Article
- Circular RNA circ_0008896 contributes to oxidized low-density lipoprotein-induced aortic endothelial cell injury via targeting miR-188-3p/NOD2 axis.Cell stress & chaperones · 2023Article
- Extracellular vesicles in atherosclerosis and vascular calcification: the versatile non-coding RNAs from endothelial cells and vascular smooth muscle cells.Frontiers in medicine · 2023Review
- Analysis of expression profiles and bioinformatics suggests that plasma exosomal circular RNAs may be involved in ischemic stroke in the Chinese Han population.Metabolic brain disease · 2022Article
- miR-22-3p as a potential biomarker for coronary artery disease based on integrated bioinformatics analysis.Frontiers in genetics · 2022Article
- Gene Differential Expression and Interaction Networks Illustrate the Biomarkers and Molecular Mechanisms of Atherosclerotic Cerebral Infarction.Journal of healthcare engineering · 2022Article
- Comprehensive Analysis to Identify Key Genes Involved in Advanced Atherosclerosis.Disease markers · 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 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Atherosclerosis, a chronic inflammatory disease, is the primary cause of most cardiovascular diseases. Circular RNAs (circRNAs) were reported to serve as post-transcriptional regulators and diagnostic markers in various diseases, but the underlying correlation between circRNAs and atherosclerosis remains elusive. In this study, we downloaded the microarray dataset GSE107522 from the Gene Expression Omnibus (GEO) and identified nine differentially expressed circRNAs (DECs). DECs expression in exosomes were investigated, and hsa_circ_0005699 was selected for subsequent analysis. We then identified 14 RNA-binding proteins (RBPs) and 71 possible hsa_circ_0005699-interacting microRNAs. Subsequently, target gene prediction and enrichment analyses were performed. The enriched pathways of RBP eIF4AIII include spliceosome, cell cycle, and pathways in cancer. We constructed a protein-protein interaction network, and 20 hub genes were identified using Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. Hub gene analysis revealed significant enrichment in mRNA splicing via the spliceosome, RNA splicing, protein binding, neurotrophin signaling pathway, and Ras signaling pathway. Using DrugMatrix of the Enrichr database, we identified 16 most significant small-molecule compounds that interacted with hub genes. Finally, seven hub genes (NEDD4L, FBXO44, FBXO27, WSB1, FBXW8, UBE2F, and ASB1) in cluster 1 were considered key targets associated with atherosclerosis according to MCODE analysis and the intersection between the module and hub genes. Thus, hsa_circ_0005699, RBP eIF4AIII, and the seven identified hub genes (NEDD4L, FBXO44, FBXO27, WSB1, FBXW8, UBE2F, and ASB1) could help to elucidate the pathogenesis and progression of atherosclerosis. This work may contribute to providing candidate targets for the diagnosis and treatment of atherosclerosis.
Indexed as
Identifiers
34150004PMC8205787W3173238276What 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.