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Identification of Potential Crucial Biomarkers in STEMI Through Integrated Bioinformatic Analysis
Li-Zhi Zhao1,2, Yi Liang3, Ting Yin4
1The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou - China.
Insights
This study identified key genes involved in ST-segment elevation myocardial infarction (STEMI) progression. Six genes, including MS4A3 and CD14, show potential as diagnostic biomarkers for STEMI, aiding early detection and treatment.
Area of Science:
- Cardiovascular biology
- Bioinformatics
- Molecular diagnostics
Background:
- ST-segment elevation myocardial infarction (STEMI) is a leading cause of global mortality.
- Early diagnosis of STEMI is crucial for intervention and prognosis.
- Biomarker discovery for STEMI remains an active area of research.
Purpose of the Study:
- To identify potential crucial biomarkers for ST-segment elevation myocardial infarction (STEMI) using bioinformatics analysis.
- To explore the molecular mechanisms underlying STEMI progression.
Main Methods:
- Utilized gene expression data (GSE59867) to identify differentially expressed genes (DEGs) between STEMI and stable coronary artery disease (SCAD) patients.
- Performed enrichment analysis, constructed protein-protein interaction networks, and identified hub genes.
- Analyzed related microRNAs (miRNAs) and transcription factors, and validated candidate biomarkers using a separate dataset (GSE62646).
Main Results:
- Identified 133 DEGs between SCAD and STEMI, with pathways related to inflammation, metabolism, and immunity being pivotal.
- Predicted key regulatory miRNAs (has-miR-124, has-miR-130a/b, has-miR-301a/b) and transcription factors (EVI1, AML1, GATA1, PPARG).
- MS4A3, KLRC4, KLRD1, AQP9, and CD14 demonstrated high sensitivity and specificity (AUC > 75%) as potential STEMI biomarkers.
Conclusions:
- Immunity, metabolism, and inflammation are key processes in STEMI development from SCAD.
- Six genes (MS4A3, KLRC4, KLRD1, AQP9, CD14, and CCR1) are identified as promising candidate biomarkers for STEMI diagnosis.
Background:
ST-segment elevation myocardial infarction (STEMI) is one of the leading causes of fatal cardiovascular diseases, which have been the prime cause of mortality worldwide. Diagnosis in the early phase would benefit clinical intervention and prognosis, but the exploration of the biomarkers of STEMI is still lacking.
Objectives:
In this study, we conducted a bioinformatics analysis to identify potential crucial biomarkers in the progress of STEMI.
Methods:
We obtained GSE59867 for STEMI and stable coronary artery disease (SCAD) patients. Differentially expressed genes (DEGs) were screened with the threshold of |log2fold change| > 0.5 and p <0.05. Based on these genes, we conducted enrichment analysis to explore the potential relevance between genes and to screen hub genes. Subsequently, hub genes were analyzed to detect related miRNAs and DAVID to detect transcription factors for further analysis. Finally, GSE62646 was utilized to assess DEGs specificity, with genes demonstrating AUC results exceeding 75%, indicating their potential as candidate biomarkers.
Results:
133 DEGs between SCAD and STEMI were obtained. Then, the PPI network of DEGs was constructed using String and Cytoscape, and further analysis determined hub genes and 6 molecular complexes. Functional enrichment analysis of the DEGs suggests that pathways related to inflammation, metabolism, and immunity play a pivotal role in the progression from SCAD to STEMI. Besides, related-miRNAs were predicted, has-miR-124, has-miR-130a/b, and has-miR-301a/b regulated the expression of the largest number of genes. Meanwhile, Transcription factors analysis indicate that EVI1, AML1, GATA1, and PPARG are the most enriched gene. Finally, ROC curves demonstrate that MS4A3, KLRC4, KLRD1, AQP9, and CD14 exhibit both high sensitivity and specificity in predicting STEMI.
Conclusions:
This study revealed that immunity, metabolism, and inflammation are involved in the development of STEMI derived from SCAD, and 6 genes, including MS4A3, KLRC4, KLRD1, AQP9, CD14, and CCR1, could be employed as candidate biomarkers to STEMI.
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