⚡ Quick Summary
This study utilized machine learning and bioinformatic analyses to identify eleven hub biomarkers in patients with coronary artery disease (CAD). Notably, ITM2B emerged as a significant biomarker, highlighting its potential role in the inflammatory pathogenesis of CAD.
🔍 Key Details
- 📊 Dataset: RNA-seq datasets from the Gene Expression Omnibus database
- ⚙️ Technologies used: Machine learning algorithms including LASSO, RF, and SVM-RFE
- 🔬 In vivo experiment: Conducted to verify the identified hub biomarkers
- 🏆 Key biomarkers identified: ITM2B, GNA15, PLAU, GNG11, HIST1H2BH, SLC11A1, RPS7, DDIT4, CD83, GNLY, S100A12
🔑 Key Takeaways
- 🧬 Eleven hub biomarkers were identified in CAD patients, linked to immune responses and cardiac functions.
- 💡 ITM2B was highlighted as the most significant biomarker for CAD.
- 🛡️ Immune cell involvement: The biomarkers were associated with CD8+ T cells and NK cells.
- ⚡ Pathways affected: Key pathways include oxidative phosphorylation and apoptotic signaling.
- 🔍 Bioinformatic analyses provided insights into the roles of these biomarkers in CAD.
- 🌱 Potential for therapeutic intervention: Findings suggest new avenues for treatment strategies.
📚 Background
Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Understanding its molecular mechanisms is crucial for developing effective therapies. Recent advancements in machine learning and bioinformatics have opened new pathways for identifying biomarkers that can enhance our understanding of CAD and improve patient outcomes.
🗒️ Study
The study aimed to identify differentially expressed hub biomarkers in the peripheral blood of CAD patients. Researchers utilized RNA-seq datasets from the Gene Expression Omnibus database and applied various machine learning algorithms, including LASSO, RF, and SVM-RFE, to analyze the data. An in vivo experiment was also conducted to validate the findings.
📈 Results
The analysis revealed eleven hub biomarkers that play significant roles in immune responses and cardiac functions. Among these, ITM2B stood out as the most important biomarker, indicating its potential relevance in the inflammatory processes associated with CAD. The study also highlighted the involvement of these biomarkers in various signaling pathways, including oxidative phosphorylation and apoptotic signaling.
🌍 Impact and Implications
The identification of these hub biomarkers could significantly impact the understanding and treatment of CAD. By focusing on ITM2B and its associated pathways, researchers may pave the way for innovative therapeutic strategies that target the inflammatory aspects of CAD. This study underscores the importance of integrating machine learning with clinical research to uncover new insights into complex diseases.
🔮 Conclusion
This research highlights the transformative potential of machine learning in identifying biomarkers for coronary artery disease. The findings suggest that ITM2B could serve as a critical biomarker for understanding the inflammatory mechanisms underlying CAD, opening new avenues for therapeutic interventions. Continued exploration in this field is essential for advancing CAD treatment strategies.
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Identification of hub biomarkers in coronary artery disease patients using machine learning and bioinformatic analyses.
Abstract
Understanding the molecular underpinnings of CAD is essential for developing effective therapeutic strategies. This study aims to identify and analyze differentially expressed hub biomarkers in the peripheral blood of CAD patients. Based on RNA-seq datasets from the Gene Expression Omnibus database, machine learning algorithms including LASSO, RF, and SVM-RFE were applied. Furthermore, the hub biomarkers were enriched to ascertain their roles in immune cell expression and signaling pathways through GO, KEGG, GSVE, and GSVA. An in vivo experiment was conducted to verify the hub biomarkers. Eleven hub biomarkers (ITM2B, GNA15, PLAU, GNG11, HIST1H2BH, SLC11A1, RPS7, DDIT4, CD83, GNLY, and S100A12) were identified and associated with CD8 + T cells and NK cells. They were mainly involved in immune responses, cardiac muscle contraction, oxidative phosphorylation, and apoptotic signaling pathways. Moreover, ITM2B had the most importance and significance to be the biomarker of CAD patients. In conclusion, these findings point to the possibility of ITM2B as a biomarker on the inflammatory pathogenesis of CAD and suggest new options for therapeutic intervention.
Author: [‘Chang X’, ‘Tao L’, ‘Tian L’, ‘Zhao Y’, ‘Niku W’, ‘Zheng W’, ‘Liu P’, ‘Wang Y’]
Journal: Sci Rep
Citation: Chang X, et al. Identification of hub biomarkers in coronary artery disease patients using machine learning and bioinformatic analyses. Identification of hub biomarkers in coronary artery disease patients using machine learning and bioinformatic analyses. 2025; 15:17244. doi: 10.1038/s41598-025-02123-7