Identification of diagnostic biomarkers and immune cell infiltration in coronary artery disease by machine learning, nomogram, and molecular docking

Xinyi Jiang ^1,2,3, Yuanxi Luo ^1,2,3, Zeshi Li ^1,2,3

⁰Department of Cardio-Thoracic surgery, Nanjing Drum Tower Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Peking Union Medical College Graduate School, Nanjing, China.

Frontiers in Immunology +

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April 17, 2024

View abstract on PubMed

Summary

This study identifies four key genes (CSF3R, EED, HSPA1B, IL17RA) as potential diagnostic biomarkers for coronary artery disease (CAD). These findings also highlight the role of immune cell infiltration in CAD and suggest potential drug targets for treatment.

Area Of Science

Biomedical research
Genomics
Immunology

Background

Coronary artery disease (CAD) remains a significant global health challenge.
Identifying reliable diagnostic biomarkers and therapeutic targets for CAD is crucial.

Purpose Of The Study

To identify novel diagnostic biomarkers for CAD.
To explore potential therapeutic medications targeting identified biomarkers.
To investigate the role of immune cell infiltration in CAD pathogenesis.

Main Methods

Weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed on gene expression datasets.
Machine learning algorithms, including random forest and eXtreme Gradient Boosting, were used to identify candidate biomarkers.
Hub genes were validated using nomogram and receiver operating characteristic (ROC) curve analyses.
CIBERSORTx was employed to analyze immune cell infiltration, and drug screening with molecular docking was conducted.

Main Results

Four hub genes (CSF3R, EED, HSPA1B, IL17RA) were identified as potential diagnostic biomarkers for CAD.
The diagnostic model based on these hub genes demonstrated high accuracy and usefulness.
Significant associations were found between hub gene expression, immune cell infiltration patterns, and CAD.
Potential therapeutic drugs targeting the identified hub genes were discovered through molecular docking.

Conclusions

CSF3R, EED, HSPA1B, and IL17RA serve as promising diagnostic biomarkers for CAD.
Immune cell infiltration patterns are critical factors in CAD development and progression.
The identified potential drugs offer new therapeutic avenues for CAD treatment.

Keywords:

coronary artery disease diagnostic biomarkers immune cell infiltration machine learning molecular docking nomogram