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Review

Transcriptomics, Proteomics and Bioinformatics in Atrial Fibrillation: A Descriptive Review

1
School of Medicine and Surgery, Università degli Studi di Milano-Bicocca, 20126 Milano, Italy
2
Bristol Veterinary School, University of Bristol, Langford House, Langford, Bristol BS40 5DU, UK
3
Bristol Heart Institute, Translational Health Sciences, University of Bristol, Bristol BS2 8HW, UK
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Bioengineering 2025, 12(2), 149; https://doi.org/10.3390/bioengineering12020149
Submission received: 10 January 2025 / Revised: 28 January 2025 / Accepted: 2 February 2025 / Published: 4 February 2025
(This article belongs to the Special Issue New Strategies for Cardiac Tissue Repair and Regeneration)

Abstract

Atrial fibrillation (AF) is the most frequent cardiac arrhythmia, with an estimated five million cases globally. This condition increases the likelihood of developing cardiovascular complications such as thromboembolic events, with a fivefold increase in risk of both heart failure and stroke. Contemporary challenges include a better understanding AF pathophysiology and optimizing therapeutical options due to the current lack of efficacy and adverse effects of antiarrhythmic drug therapy. Hence, the identification of novel biomarkers in biological samples would greatly impact the diagnostic and therapeutic opportunities offered to AF patients. Long noncoding RNAs, micro RNAs, circular RNAs, and genes involved in heart cell differentiation are particularly relevant to understanding gene regulatory effects on AF pathophysiology. Proteomic remodeling may also play an important role in the structural, electrical, ion channel, and interactome dysfunctions associated with AF pathogenesis. Different devices for processing RNA and proteomic samples vary from RNA sequencing and microarray to a wide range of mass spectrometry techniques such as Orbitrap, Quadrupole, LC-MS, and hybrid systems. Since AF atrial tissue samples require a more invasive approach to be retrieved and analyzed, blood plasma biomarkers were also considered. A range of different sample preprocessing techniques and bioinformatic methods across studies were examined. The objective of this descriptive review is to examine the most recent developments of transcriptomics, proteomics, and bioinformatics in atrial fibrillation.
Keywords: bioinformatics; transcriptomics; proteomics; atrial fibrillation; machine learning bioinformatics; transcriptomics; proteomics; atrial fibrillation; machine learning

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MDPI and ACS Style

Belfiori, M.; Lazzari, L.; Hezzell, M.; Angelini, G.D.; Dong, T. Transcriptomics, Proteomics and Bioinformatics in Atrial Fibrillation: A Descriptive Review. Bioengineering 2025, 12, 149. https://doi.org/10.3390/bioengineering12020149

AMA Style

Belfiori M, Lazzari L, Hezzell M, Angelini GD, Dong T. Transcriptomics, Proteomics and Bioinformatics in Atrial Fibrillation: A Descriptive Review. Bioengineering. 2025; 12(2):149. https://doi.org/10.3390/bioengineering12020149

Chicago/Turabian Style

Belfiori, Martina, Lisa Lazzari, Melanie Hezzell, Gianni D. Angelini, and Tim Dong. 2025. "Transcriptomics, Proteomics and Bioinformatics in Atrial Fibrillation: A Descriptive Review" Bioengineering 12, no. 2: 149. https://doi.org/10.3390/bioengineering12020149

APA Style

Belfiori, M., Lazzari, L., Hezzell, M., Angelini, G. D., & Dong, T. (2025). Transcriptomics, Proteomics and Bioinformatics in Atrial Fibrillation: A Descriptive Review. Bioengineering, 12(2), 149. https://doi.org/10.3390/bioengineering12020149

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