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Neural Circuits-Adjusted Diagnostic Approach to Predict Recurrence of Atrial Fibrillation

  • Conference paper
  • First Online:
6th International Conference on Nanotechnologies and Biomedical Engineering (ICNBME 2023)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 91))

  • 169 Accesses

Abstract

Recently the high informational input on individuals of modern society is a real challenge for the capacity of the central nervous system. It has to overcome not just the big data amount, but also a state of permanent hyperactivity due to informationally-induced neuronal circuits, including artificially-induced neural circuits, originating from advertising and directed informational streams. Pathologically hyperactivated interconnectivity of the neural circuits leads to a permanently increased central component of heart rhythm modulation leading to favorable conditions for atrial fibrillation recurrence in patients with paroxysmal atrial fibrillation. Two new parameters of cardiorhythmogram analysis – low-frequency (LF) drops and high-frequency (HF) counter-regulation are dynamic indicators for the intensity of affection of the heart rhythm regulation by the pathological hyperactivity of the central nervous system. Here we show in the case-series study of 350 cardiorhythmograms of patients with paroxysmal atrial fibrillation, that the LF drops and HF counter-regulation are sensitive biomarkers to predict the onset of recurrence of atrial fibrillation. The hyperactivity of the central nervous system leads to atrial fibrillation onset. The increased centrally-driven heart rhythm modulation can be visualized on cardiorhythmograms by the feature LF drops. The capacity of the vegetative nervous system the compensate for this state in order to maintain normal sinus heart rhythm can be assessed by the HF counter-regulation. The features HF counter-regulation and LF drops reflect the answer of the heart regulation to the neuronal circuits-induced central hyperactivation and can be evaluated in the cardiorhythmograms for the prediction of atrial fibrillation recurrence in patients with paroxysmal atrial fibrillation.

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References

  1. Krönke, K.M., et al.: Functional connectivity in a triple-network saliency model is associated with real-life self-control. Neuropsychologia 149, 107667 (2020). https://doi.org/10.1016/j.neuropsychologia.2020.107667. Epub 2020 Oct 31 PMID: 33130158

    Article  Google Scholar 

  2. Smith, R., Sanova, A., Alkozei, A., Lane, R.D., Killgore, W.D.S.: Higher levels of trait emotional awareness are associated with more efficient global information integration throughout the brain: a graph-theoretic analysis of resting state functional connectivity. Soc. Cogn. Affect. Neurosci. 13(7), 665–675 (2018). https://doi.org/10.1093/scan/nsy047.PMID:29931125;PMCID:PMC6121141

    Article  Google Scholar 

  3. Gifford, G, Crossley, N.: M68. functional network small world and efficiency characteristics in a sample at ultra high risk of Psychosis. Schizophr Bull. 43(Suppl 1), S235 (2017).  https://doi.org/10.1093/schbul/sbx022.063. Epub 2017 Mar 20. PMCID: PMC5475821

  4. Van Battum, E.Y., Brignani, S., Pasterkamp, R.J.: Axon guidance proteins in neurological disorders.  The Lancet Neurol. 14(5), 532–546 (2015).  https://doi.org/10.1016/S1474-4422(14)70257-1

  5. Schnabel, R.B., et al.: Relations of biomarkers of distinct pathophysiological pathways and atrial fibrillation incidence in the community. Circulation. 121(2), 200–207 (2010).  https://doi.org/10.1161/CIRCULATIONAHA.109.882241. Epub 2010 Jan 4. PMID: 20048208; PMCID: PMC3224826

  6. Kornej, J., Benjamin, E.J, Magnani, J.W.: Atrial fibrillation: global burdens and global opportunities. Heart. heartjnl-2020–318480 (2021).  https://doi.org/10.1136/heartjnl-2020-318480. Epub ahead of print. PMID: 33509978

  7. Vilallongue, N., et al.: Guidance landscapes unveiled by quantitative proteomics to control reinnervation in adult visual system. Nat. Commun. 13(1), 6040 (2022). https://doi.org/10.1038/s41467-022-33799-4.PMID:36229455;PMCID:PMC9561644

    Article  Google Scholar 

  8. Südhof, T.C.: Molecular neuroscience in the 21st century: a personal perspective. Neuron 96(3), 536–541 (2017). https://doi.org/10.1016/j.neuron.2017.10.005.PMID:29096071;PMCID:PMC5689449

    Article  Google Scholar 

  9. Cohen, D., Nakai, T., Nishimoto, S.: Brain networks are decoupled from external stimuli during internal cognition. Neuroimage 256, 119230 (2022). https://doi.org/10.1016/j.neuroimage.2022.119230. Epub 2022 Apr 20 PMID: 35460919

    Article  Google Scholar 

  10. Abi-Dargham, A., Horga, G.: The search for imaging biomarkers in psychiatric disorders. Nat. Med. 22(11), 1248–1255 (2016). https://doi.org/10.1038/nm.4190. (Epub 2016 Oct 26 PMID: 27783066)

  11. Varadarajan, S.G., Hunyara, J.L., Hamilton, N.R., Kolodkin, A.L., Huberman, A.D.: Central nervous system regeneration. Cell 185(1), 77–94 (2022). https://doi.org/10.1016/j.cell.2021.10.029. PMID: 34995518

    Article  Google Scholar 

  12. Yao, Z., Hu, B., Xie, Y., Moore, P., Zheng, J.: A review of structural and functional brain networks: small world and atlas. Brain Inform. 2(1), 45–52 (2015).  https://doi.org/10.1007/s40708-015-0009-z. Epub 2015 Feb 14. PMID: 27747502; PMCID: PMC4883160

  13. Calkins, H., et al.: 2012 HRS/EHRA/ECAS Expert Consensus Statement on Catheter and Surgical Ablation of Atrial Fibrillation: recommendations for patient selection, procedural techniques, patient management and follow-up, definitions, endpoints, and research trial design. Europace 14(4), 528–606 (2012). https://doi.org/10.1093/europace/eus027

    Article  Google Scholar 

  14. Geurts, S., et al.:Heart rate variability and atrial fibrillation in the general population: a longitudinal and Mendelian randomization study. Clin. Res. Cardiol. 112(6), 747–758 (2023).  https://doi.org/10.1007/s00392-022-02072-5. Epub 2022 Aug 13. PMID: 35962833; PMCID: PMC10241681

  15. Agarwal, S.K., et al.: Cardiac Autonomic Dysfunction and Incidence of Atrial Fibrillation: Results From 20 Years Follow-Up. J Am Coll Cardiol. 69(3), 291–299 (2017). https://doi.org/10.1016/j.jacc.2016.10.059.PMID:28104071;PMCID:PMC5260487

    Article  Google Scholar 

  16. Sidorenko, L., Diaz-Ramirez, I., Vovc, V., Baumann, G.: Fundamental aspects of cardiovascular regulation in predisposition to atrial fibrillation. Moldovan Med. J. 61(4), 42–45 (2018). https://doi.org/10.5281/zenodo.2222313

    Article  Google Scholar 

  17. Sidorenko, L., Sidorenko, I., Gapelyuk, A., Wessel, N.: Pathological heart rate regulation in apparently healthy individuals. Entropy 25(7), 1023 (2023). https://doi.org/10.3390/e25071023

    Article  Google Scholar 

  18. Sidorenko, L., Diaz-Ramirez, I., Vovc, V., Baumann, G.: New approach to heart rate variability analysis based on cardiac physiological biomarkers. Moldovan Med. J. 61(3), 39–46 (2018). https://doi.org/10.5281/zenodo.14659264

    Article  Google Scholar 

  19. Billman, G.E., Huikuri, H.V., Sacha, J., Trimmel, K.: An introduction to heart rate variability: methodological considerations and clinical applications. Front Physiol. 6, 55 (2015). https://doi.org/10.3389/fphys.2015.00055.PMID:25762937;PMCID:PMC4340167

    Article  Google Scholar 

  20. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 93(5), 1043–65 (1996). PMID: 8598068

    Google Scholar 

  21. Sassi, R., et al.: Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC working group and the european heart rhythm association co-endorsed by the asia pacific heart rhythm society. Europace 17(9), 1341–1353 (2015). https://doi.org/10.1093/europace/euv015

    Article  Google Scholar 

  22. Farahani, F.V., Karwowski, W., Lighthall, N.R.: Application of graph theory for identifying connectivity patterns in human brain networks: a systematic review. Front. Neurosci. 13, 585 (2019). https://doi.org/10.3389/fnins.2019.00585.PMID:31249501;PMCID:PMC6582769

    Article  Google Scholar 

  23. Krupnik, R., Yovel, Y., Assaf, Y.: inner hemispheric and interhemispheric connectivity balance in the human brain. J. Neurosci. 41(40), 8351–8361 (2021).  https://doi.org/10.1523/JNEUROSCI.1074-21.2021. Epub 2021 Aug 31. PMID: 34465598; PMCID: PMC8496194

  24. Alenina, N., et al.: Growth retardation and altered autonomic control in mice lacking brain serotonin. Proc. Natl. Acad. Sci. USA 106(25), 10332–10337 (2009). doi: https://doi.org/10.1073/pnas.0810793106. Epub 2009 Jun 11. PMID: 19520831; PMCID: PMC2700938

  25. Da Costa-Goncalves, A.C., et al.: Role of the multidomain protein spinophilin in blood pressure and cardiac function regulation. Hypertension 52(4), 702–707 (2008). https://doi.org/10.1161/HYPERTENSIONAHA.108.114355. Epub 2008 Aug 18 PMID: 18711009

    Article  Google Scholar 

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Acknowledgments

The authors are grateful for the support of this study by the project “Synthesis of steroids containing the azole fragment in the cycle D and/or in the side chain as the basis for creating medicines for the treatment of prostate cancer”. № 22.80013.8007.1BL.

Funding

The Authors Declare that They Have no Conflict of Interest.

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Authors and Affiliations

  1. Department of Molecular Biology and Human Genetics, Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau, Moldova

    Ludmila Sidorenko, Igor Cemortan, Svetlana Capcelea, Ludmila Rotaru & Liliana Badan

  2. Medical Center “Gesundheit”, Chisinau, Moldova

    Irina Sidorenko

  3. Department of General Surgery, National Pirogov Memorial Medical University, Vinnytsya, Ukraine

    Roman Chornopyshchuk

  4. Institute of Chemistry, Moldova State University, Chisinau, Moldova

    Fliur Macaev

  5. Department of Non-Linear Dynamics, Cardiovascular Physics, Humboldt Universitaet zu Berlin, Berlin, Germany

    Niels Wessel

  6. MSB Medical School Berlin GmbH, Berlin, Germany

    Niels Wessel & Niels Wessel

Authors
  1. Ludmila Sidorenko
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  2. Irina Sidorenko
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  3. Roman Chornopyshchuk
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  4. Igor Cemortan
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  5. Svetlana Capcelea
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  6. Fliur Macaev
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  7. Ludmila Rotaru
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  8. Liliana Badan
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  9. Niels Wessel
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Corresponding author

Correspondence to Ludmila Sidorenko .

Editor information

Editors and Affiliations

  1. Department of Microelectronics and Biomedical Engineering, Technical University of Moldova, Chisinau, Moldova

    Victor Sontea

  2. Academy of Sciences of Moldova, Chisinau, Moldova

    Ion Tiginyanu

  3. Department of Microelectronics and Biomedical Engineering, Technical University of Moldova, Chisinau, Moldova

    Serghei Railean

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Sidorenko, L. et al. (2024). Neural Circuits-Adjusted Diagnostic Approach to Predict Recurrence of Atrial Fibrillation. In: Sontea, V., Tiginyanu, I., Railean, S. (eds) 6th International Conference on Nanotechnologies and Biomedical Engineering. ICNBME 2023. IFMBE Proceedings, vol 91. Springer, Cham. https://doi.org/10.1007/978-3-031-42775-6_60

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  • DOI: https://doi.org/10.1007/978-3-031-42775-6_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42774-9

  • Online ISBN: 978-3-031-42775-6

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