ArticleLipids in health and disease2022
Lipid metabolism patterns and relevant clinical and molecular features of coronary artery disease patients: an integrated bioinformatic analysis.
Article in Lipids in health and disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed, 21 citations in OpenAlex.
- Elucidating the role of SF3B3 in coronary atherosclerosis: integrating bioinformatics and machine learning for advanced insights.Journal of cardiothoracic surgery · 2026Article
- Identification and validation of mitochondrial metabolism-ralated biomarkers in coronary heart disease.Medicine · 2026Article
- Metabolomic Biomarkers for Non-Invasive Diagnosis of Coronary Artery Disease and Obstructive Sleep Apnea Co-Occurrence.Nature and science of sleep · 2026Article
- Single-cell and spatially resolved omics reveal transcriptional and metabolic signatures of ovarian endometriomas.Nature communications · 2025Article
- Jianpi-Huogu Prescription Repairs Nontraumatic Osteonecrosis of the Femoral Head by Inhibiting NAMPT/STK11/HMGCR/ACAT1 Axis-Mediated Lipid Production.Journal of cellular and molecular medicine · 2025Article
- Elucidating the role of LGALS3BP in coronary atherosclerosis: integrating bioinformatics and machine learning for advanced insights.Journal of cardiothoracic surgery · 2025Article
- Therapeutic Potential of Bioactive Compounds from Traditional Chinese Medicine in Modulating Macrophage Cholesterol Metabolism for Atherosclerosis Treatment.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Exploring the causal links between inflammation-related genes and atherosclerosis through Mendelian randomization analysis.Medicine · 2025Article
- Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding.Journal of cardiothoracic surgery · 2025Article
- Current Knowledge of the Impact of Vitamin D in Coronary Artery Disease.International journal of molecular sciences · 2025Review
- Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding.Scientific reports · 2025Article
- Predicting low density lipoprotein cholesterol target attainment using machine learning in patients with coronary artery disease receiving moderate-dose statin therapy.Scientific reports · 2025Article
- Integrative bioinformatics and machine learning approach unveils potential biomarkers linking coronary atherosclerosis and fatty acid metabolism-associated gene.Journal of cardiothoracic surgery · 2025Article
- Comprehensive Analysis Based on Genes Associated With Cuproptosis, Ferroptosis, and Pyroptosis for the Prediction of Diagnosis and Therapies in Coronary Artery Disease.Cardiovascular therapeutics · 2025Article
- Unlocking potential biomarkers bridging coronary atherosclerosis and pyrimidine metabolism-associated genes through an integrated bioinformatics and machine learning approach.BMC cardiovascular disorders · 2024Article
- Genetically predicted HLA-DR+ natural killer cells as potential mediators in the lipid-coronary artery disease/ calcification (CAD/CAC) causal pathway.Frontiers in immunology · 2024Article
- Transcriptome data analysis of primary cardiomyopathies reveals perturbations in arachidonic acid metabolism.Frontiers in cardiovascular medicine · 2023Article
- Identification and validation of hub genes involved in foam cell formation and atherosclerosis developmentPeerJ · 2023Article
- Risk prediction model for major adverse cardiovascular events (MACE) during hospitalization in patients with coronary heart disease based on myocardial energy metabolic substrate.Frontiers in cardiovascular medicine · 2023Article
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundHyperlipidaemia is an important factor that induces coronary artery disease (CAD). This study aimed to explore the lipid metabolism patterns and relevant clinical and molecular features of coronary artery disease patients.
methodsIn the current study, datasets were fetched from the Gene Expression Omnibus (GEO) database and nonnegative matrix factorization clustering was used to establish a new CAD classification based on the gene expression profile of lipid metabolism genes. In addition, this study carried out bioinformatics analysis to explore intrinsic biological and clinical characteristics of the subgroups.
resultsData for a total of 615 samples were extracted from the Gene Expression Omnibus database and were associated with clinical information. Then, this study used nonnegative matrix factorization clustering for RNA sequencing data of 581 lipid metabolism relevant genes, and the 296 patients with CAD were classified into three subgroups (NMF1, NMF2, and NMF3). Subjects in subgroup NMF2 tended to have an increased severity of CAD. The CAD index and age of group NMF1 were similar to those of group NMF3, but their intrinsic biological characteristics exhibited significant differences. In addition, weighted gene coexpression network analysis (WGCNA) was used to determine the most important modules and screen lipid metabolism related genes, followed by further analysis of the DEGs in which the significant genes were identified based on clinical information. The progression of coronary atherosclerosis may be influenced by genes such as PTGDS and DGKE.
conclusionDifferent CAD subgroups have their own intrinsic biological characteristics, indicating that more personalized treatment should be provided to patients in each subgroup, and some lipid metabolism related genes (PDGTS, DGKE and so on) were related significantly with clinical characteristics.
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