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Submitted: 19 Sep 2024
Revision: 01 Mar 2025
Accepted: 19 Apr 2025
ePublished: 28 Jun 2025
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J Cardiovasc Thorac Res. 2025;17(2): 109-120.
doi: 10.34172/jcvtr.025.33347
PMID: 40862099
PMCID: PMC12375429
  Abstract View: 535
  PDF Download: 471
  Full Text View: 156

Original Article

An integrated bioinformatics approach for identification of key modulators and biomarkers involved in atrial fibrillation

Summan Thahiem 1 ORCID logo, Ayesha Ishtiaq 1 ORCID logo, Faisal Iftekhar 2 ORCID logo, Muhammad Ishtiaq Jan 3 ORCID logo, Iram Murtaza 1* ORCID logo

1 Department of Biochemistry, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan
2 Department of Cardiovascular Surgery, Lady Reading Hospital Peshawar, Peshawar, Pakistan
3 Department of Chemistry, Faculty of Chemical & Pharmaceutical Sciences, Kohat University of Science and Technology, Kohat, Pakistan
*Corresponding Author: Iram Murtaza, Email: irambch@qau.edu.pk

Abstract

Introduction: Atrial fibrillation (AFib) is a sustained form of cardiac arrythmia that occurs due to sympathetic overdrive, neurohumoral and electrophysiological changes. Sympatho-renal modulatory approach via miRNA-based therapeutics is likely to be an important treatment option for AFib. The study was aimed to unravel the common miRNAs as therapeutic targets involved in sympatho- renovascular axis to combat AFib.

Methods: We employed the bioinformatics approach to discover differentially expressed genes (DEGs) from microarray gene expression datasets GSE41177 and GSE79768 of AFib patients. Concomitantly, genes associated with sympathetic cardio-renal axis, from Genetic Testing Registry (GTR) of National Center for Biotechnology Information (NCBI) were also analyzed. Overlapping miRNAs that target the maximum number of genes across all three pathological conditions perpetuating AFib were shortlisted. To confirm the reliability of the identified miRNAs, differential expression analysis was performed on miRNA expression profiles GSE190898, GSE68475, GSE70887 and GSE28954 derived from AFib patient samples.

Results: ShinyGO analysis revealed enrichment in beta-adrenergic signaling, calcium signaling, as well as G protein-coupled receptor (GPCR) signaling involved in post synaptic membrane potential. The intersection of top 10 modules in miRNA-mRNA network revealed hub miRNAs having highest node degree, maximum neighborhood component (MNC), and maximal clique centrality (MCC) scores. Differential expression analysis revealed hub miRNAs identified through integrated approach were found to be significantly dysregulated in AFib patients.

Conclusion: This integrated approach identified 6 hub miRNAs, 4 reported (miR-101-3p, miR-23-3p, miR-27-3p, miR-25-3p) and 2 novel (miR-32-5p, miR-92-3p) miRNAs that might act as putative biomarkers for AFib.


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