4.4 Article

Identification of Differentially Expressed Genes and Pathways in Human Atrial Fibrillation by Bioinformatics Analysis

期刊

INTERNATIONAL JOURNAL OF GENERAL MEDICINE
卷 15, 期 -, 页码 103-114

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DOVE MEDICAL PRESS LTD
DOI: 10.2147/IJGM.S334122

关键词

atrial fibrillation; bioinformatics analysis; differentially expressed genes; pathways; protein-protein interaction network

资金

  1. Xuzhou Science and Technology Bureau [KC20097]

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This study aimed to explore the molecular mechanisms of atrial fibrillation (AF) and identified several key genes and pathways involved in AF pathogenesis. The results indicated that macrophage migration inhibitory factor (MIF), MYC proto-oncogene, bHLH transcription factor (MYC), and inhibitor of differentiation 1 (ID1) may participate in the progression of AF through the TGF-beta and Hippo signaling pathways.
Introduction: Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, but the molecular mechanisms underlying AF are not known. We aimed to identify the pivotal genes and pathways involved in AF pathogenesis because they could become potential biomarkers and therapeutic targets of AF. Methods: The microarray datasets of GSE31821 and GSE41177 were downloaded from the Gene Expression Omnibus database. After combining the two datasets, differentially expressed genes (DEGs) were screened by the Limma package. MicroRNAs (miRNAs) confirmed experimentally to have an interaction with AF were screened through the miRTarBase database. Target genes of miRNAs were predicted using the miRNet database, and the intersection between DEGs and target genes of miRNAs, which were defined as common genes (CGs), were analyzed. Functional and pathway-enrichment analyses of DEGs and CGs were performed using the databases DAVID and KOBAS. Protein-protein interaction (PPI) network, miRNA- messenger(m) RNA network, and drug-gene network was visualized. Finally, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was used to validate the expression of hub genes in the miRNA-mRNA network. Results: Thirty-three CGs were acquired from the intersection of 65 DEGs from the integrated dataset and 9777 target genes of miRNAs. Fifteen hub genes were selected from the PPI network, and the miRNA-mRNA network, including 82 miRNAs and 9 target mRNAs, was constructed. Furthermore, with the validation by RT-qPCR, macrophage migration inhibitory factor (MIF), MYC proto-oncogene, bHLH transcription factor (MYC), inhibitor of differentiation 1 (ID1), and C-X-C Motif Chemokine Receptor 4 (CXCR4) were upregulated and superoxide Dismutase 2 (SOD2) was downregulated in patients with AF compared with healthy controls. We also found MIF, MYC, and ID1 were enriched in the transforming growth factor (TGF)-beta and Hippo signaling pathway. Conclusion: We identified several pivotal genes and pathways involved in AF pathogenesis. MIF, MYC, and ID1 might participate in AF progression through the TGF-beta and Hippo signaling pathways. Our study provided new insights into the mechanisms of action of AF.

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