ArticleJournal of inflammation research2025
Inflammatory Gene Signature Identified by Machine Algorithms Reveals Novel Biomarkers of Coronary Artery Disease.
Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The cGAS-STING pathway in acute myocardial infarction: Biomarker discovery and mechanistic insights.PloS one · 2026Article
- Bioinformatic analyses and validated experiments reveal an aging hallmark gene set and protective miR of coronary artery disease.Scientific reports · 2025Article
- Identification and validation of inflammatory response genes linking chronic kidney disease with coronary artery disease based on bioinformatics and machine learning.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Inflammatory activation of immune cells plays a pivotal role in the development of coronary artery diseases (CAD). This study aims to investigate the immune responses of peripheral blood mononuclear cells (PBMCs) in CAD and to identify novel signature genes and biomarkers using machine learning algorithms. Methods: The GSE113079 dataset was analyzed and differentially expressed genes (DEGs) were identified between CAD and normal samples. The intersection of DEGs with inflammation-related genes was used to identify the differentially expressed inflammation-related genes (DIRGs). Then, the receiver operating characteristic (ROC) curves were plotted for each DIRG, and those with an area under the curve (AUC) greater than 0.9 were selected for subsequent analysis. Furthermore, machine learning algorithms were employed to identify biomarkers. A nomogram was developed based on these biomarkers. The CIBERSORT algorithm and Wilcoxon test method were used to analyze the differences in immune cells between the CAD and normal samples. The identified biomarkers were validated in PBMCs from patients with CAD and in atherosclerotic aortas from ApoE Results: A total of 574 DEGs were identified between CAD and normal samples. From this intersection, 29 DIRGs were identified, of which 14 DIRGs ( Conclusion: Our findings revealed novel inflammatory gene signatures of CAD that could be potential biomarkers for the early diagnosis of CAD.
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Registered trials
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