ArticleBMC cardiovascular disorders2021
A ten-genes-based diagnostic signature for atherosclerosis.
Article in BMC cardiovascular disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 17 citations in OpenAlex.
- Identification and evaluation of glutamine-related gene characteristics based on multi-omics to predict the prognosis of patients with colorectal cancer.Journal of translational medicine · 2026Article
- TLR2, CCR1, IRF8, and CCL4 as biomarkers for atherosclerosis progression and therapy response: A multi-omics study.Medicine · 2025Article
- Identification of co-expressed genes and immune infiltration features related to the progression of atherosclerosis.Journal of applied genetics · 2024Article
- Transcriptional profiles associated with coronary artery disease in type 2 diabetes mellitus.Frontiers in endocrinology · 2024Article
- Article
- [Validation and comparison of diabetic retinopathy-based diagnostic models for diabetic nephropathy].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Article
- PseU-ST: A new stacked ensemble-learning method for identifying RNA pseudouridine sites.Frontiers in genetics · 2023Article
- Diagnostic and prognostic significance of lncRNA SOX2-OT in patients with carotid atherosclerosis.BMC cardiovascular disorders · 2022Article
- Analyzing the pathogenesis of systemic lupus erythematosus complicated by atherosclerosis using transcriptome data.Frontiers in immunology · 2022Article
- The Integrated Analysis Identifies Three Critical Genes as Novel Diagnostic Biomarkers Involved in Immune Infiltration in Atherosclerosis.Frontiers in immunology · 2022Article
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Authors and funding
7 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAtherosclerosis is the leading cause of cardiovascular disease with a high mortality worldwide. Understanding the atherosclerosis pathogenesis and identification of efficient diagnostic signatures remain major problems of modern medicine. This study aims to screen the potential diagnostic genes for atherosclerosis.
methodsWe downloaded the gene chip data of 135 peripheral blood samples, including 57 samples with atherosclerosis and 78 healthy subjects from GEO database (Accession Number: GSE20129). The weighted gene co-expression network analysis was applied to identify atherosclerosis-related genes. Functional enrichment analysis was conducted by using the clusterProfiler R package. The interaction pairs of proteins encoded by atherosclerosis-related genes were screened using STRING database, and the interaction network was further optimized with the cytoHubba plug-in of Cytoscape software.
resultsThe logistic regression diagnostic model was constructed to predict normal and atherosclerosis samples. A gene module which included 532 genes related to the occurrence of atherosclerosis were screened. Functional enrichment analysis basing on the 532 genes identified 235 significantly enriched GO terms and 44 significantly enriched KEGG pathways. The top 50 hub genes of the protein-protein interaction network were identified. The final logistic regression diagnostic model was established by the optimal 10 key genes, which could distinguish atherosclerosis samples from normal samples.
conclusionsA predictive model based on 10 potential atherosclerosis-related genes was obtained, which should shed light on the diagnostic research of atherosclerosis.
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