Identification of Key Genes and Biological Pathways Related to Myocardial Infarction through Integrated Bioinformatics Analysis

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EBADI NADER; Arefizadeh Reza; Nasrollahzadeh Sabet Mehrdad; GOODARZI NASER

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Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF MEDICAL SCIENCES (IJMS) Year:2023 | Volume:48 | Issue:1 Page(s): 35-42

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Title

Identification of Key Genes and Biological Pathways Related to Myocardial Infarction through Integrated Bioinformatics Analysis

Author(s)

EBADI NADER | Arefizadeh Reza | Nasrollahzadeh Sabet Mehrdad | GOODARZI NASER | Issue Writer Certificate

Keywords

Myocardial infarction

Coronary disease

Bioinformatics

Abstract

Background: Coronary heart disease is the leading cause of death worldwide. Myocardial infarction (MI) is a fatal manifestation of coronary heart disease, which can present as sudden death. Although the molecular mechanisms of coronary heart disease are still unknown, global gene expression profiling is regarded as a useful approach for deciphering the pathophysiology of this disease and subsequent diseases. This study used a Bioinformatics analysis approach to better understand the molecular mechanisms underlying coronary heart disease. Methods: This experimental study was conducted in the department of cardiology, Aja University of Medical Sciences (2021-2022), Tehran, Iran. To identify the key deregulated genes and pathways in coronary heart disease, an integrative approach was used by merging three gene expression datasets, including GSE19339, GSE66360, and GSE29111, into a single matrix. The t test was used for the statistical analysis, with a significance level of P<0. 05. Results: The limma package in R was used to identify a total of 133 DEGs, consisting of 124 upregulated and nine downregulated genes. KDM5D, EIF1AY, and CCL20 are among the top upregulated genes. Moreover, the interleukin 17 (IL-17) signaling pathway and four other signaling pathways were identified as the potent underlying pathogenesis of both coronary artery disease (CAD) and MI using a systems biology approach. Accordingly, these findings can provide expression signatures and potential biomarkers in CAD and MI pathophysiology, which can contribute to both diagnosis and therapeutic purposes. Conclusion: Five signaling pathways were introduced in MI and CAD that were primarily involved in inflammation, including the IL-17 signaling pathway, TNF signaling pathway, toll-like receptor signaling pathway, C-type lectin receptor signaling pathway, and rheumatoid arthritis signaling pathway.

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APA: Copy

EBADI, NADER, Arefizadeh, Reza, Nasrollahzadeh Sabet, Mehrdad, & GOODARZI, NASER. (2023). Identification of Key Genes and Biological Pathways Related to Myocardial Infarction through Integrated Bioinformatics Analysis. IRANIAN JOURNAL OF MEDICAL SCIENCES (IJMS), 48(1), 35-42. SID. https://sid.ir/paper/1091613/en

Vancouver: Copy

EBADI NADER, Arefizadeh Reza, Nasrollahzadeh Sabet Mehrdad, GOODARZI NASER. Identification of Key Genes and Biological Pathways Related to Myocardial Infarction through Integrated Bioinformatics Analysis. IRANIAN JOURNAL OF MEDICAL SCIENCES (IJMS)[Internet]. 2023;48(1):35-42. Available from: https://sid.ir/paper/1091613/en

IEEE: Copy

NADER EBADI, Reza Arefizadeh, Mehrdad Nasrollahzadeh Sabet, and NASER GOODARZI, “Identification of Key Genes and Biological Pathways Related to Myocardial Infarction through Integrated Bioinformatics Analysis,” IRANIAN JOURNAL OF MEDICAL SCIENCES (IJMS), vol. 48, no. 1, pp. 35–42, 2023, [Online]. Available: https://sid.ir/paper/1091613/en

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