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Müller P, Leow MKS, Dietrich JW. Minor perturbations of thyroid homeostasis and major cardiovascular endpoints—Physiological mechanisms and clinical evidence. Front Cardiovasc Med 2022; 9:942971. [PMID: 36046184 PMCID: PMC9420854 DOI: 10.3389/fcvm.2022.942971] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 07/22/2022] [Indexed: 11/13/2022] Open
Abstract
It is well established that thyroid dysfunction is linked to an increased risk of cardiovascular morbidity and mortality. The pleiotropic action of thyroid hormones strongly impacts the cardiovascular system and affects both the generation of the normal heart rhythm and arrhythmia. A meta-analysis of published evidence suggests a positive association of FT4 concentration with major adverse cardiovascular end points (MACE), but this association only partially extends to TSH. The risk for cardiovascular death is increased in both subclinical hypothyroidism and subclinical thyrotoxicosis. Several published studies found associations of TSH and FT4 concentrations, respectively, with major cardiovascular endpoints. Both reduced and elevated TSH concentrations predict the cardiovascular risk, and this association extends to TSH gradients within the reference range. Likewise, increased FT4 concentrations, but high-normal FT4 within its reference range as well, herald a poor outcome. These observations translate to a monotonic and sensitive effect of FT4 and a U-shaped relationship between TSH and cardiovascular risk. Up to now, the pathophysiological mechanism of this complex pattern of association is poorly understood. Integrating the available evidence suggests a dual etiology of elevated FT4 concentration, comprising both ensuing primary hypothyroidism and a raised set point of thyroid function, e. g. in the context of psychiatric disease, chronic stress and type 2 allostatic load. Addressing the association between thyroid homeostasis and cardiovascular diseases from a systems perspective could pave the way to new directions of research and a more personalized approach to the treatment of patients with cardiovascular risk.
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Affiliation(s)
- Patrick Müller
- Department for Electrophysiology, Medical Hospital I, Klinikum Vest, Recklinghausen, NRW, Germany
| | - Melvin Khee-Shing Leow
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore
- Department of Endocrinology, Tan Tock Seng Hospital, Singapore, Singapore
- Metabolic Disorders Research Programme, Lee Kong Chian School of Medicine, Singapore, Singapore
- Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Singapore
| | - Johannes W. Dietrich
- Diabetes, Endocrinology and Metabolism Section, Department of Internal Medicine I, St. Josef Hospital, Ruhr University Bochum, Bochum, NRW, Germany
- Diabetes Centre Bochum/Hattingen, St. Elisabeth-Hospital Blankenstein, Hattingen, NRW, Germany
- Centre for Rare Endocrine Diseases, Ruhr Centre for Rare Diseases (CeSER), Ruhr University Bochum and Witten/Herdecke University, Bochum, NRW, Germany
- Centre for Diabetes Technology, Catholic Hospitals Bochum, Ruhr University Bochum, Bochum, NRW, Germany
- *Correspondence: Johannes W. Dietrich
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Whittaker DG, Clerx M, Lei CL, Christini DJ, Mirams GR. Calibration of ionic and cellular cardiac electrophysiology models. WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE 2020; 12:e1482. [PMID: 32084308 PMCID: PMC8614115 DOI: 10.1002/wsbm.1482] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/17/2020] [Accepted: 01/18/2020] [Indexed: 12/30/2022]
Abstract
Cardiac electrophysiology models are among the most mature and well-studied mathematical models of biological systems. This maturity is bringing new challenges as models are being used increasingly to make quantitative rather than qualitative predictions. As such, calibrating the parameters within ion current and action potential (AP) models to experimental data sets is a crucial step in constructing a predictive model. This review highlights some of the fundamental concepts in cardiac model calibration and is intended to be readily understood by computational and mathematical modelers working in other fields of biology. We discuss the classic and latest approaches to calibration in the electrophysiology field, at both the ion channel and cellular AP scales. We end with a discussion of the many challenges that work to date has raised and the need for reproducible descriptions of the calibration process to enable models to be recalibrated to new data sets and built upon for new studies. This article is categorized under: Analytical and Computational Methods > Computational Methods Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models.
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Affiliation(s)
- Dominic G. Whittaker
- Centre for Mathematical Medicine & Biology, School of Mathematical SciencesUniversity of NottinghamNottinghamUK
| | - Michael Clerx
- Computational Biology & Health Informatics, Department of Computer ScienceUniversity of OxfordOxfordUK
| | - Chon Lok Lei
- Computational Biology & Health Informatics, Department of Computer ScienceUniversity of OxfordOxfordUK
| | | | - Gary R. Mirams
- Centre for Mathematical Medicine & Biology, School of Mathematical SciencesUniversity of NottinghamNottinghamUK
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Abstract
Determining optimal treatment strategies for complex arrhythmogenesis in AF is confounded by the lack of consensus regarding the mechanisms causing AF. Studies report different mechanisms for AF, ranging from hierarchical drivers to anarchical multiple activation wavelets. Differences in the assessment of AF mechanisms are likely due to AF being recorded across diverse models using different investigational tools, spatial scales and clinical populations. The authors review different AF mechanisms, including anatomical and functional re-entry, hierarchical drivers and anarchical multiple wavelets. They then describe different cardiac mapping techniques and analysis tools, including activation mapping, phase mapping and fibrosis identification. They explain and review different data challenges, including differences between recording devices in spatial and temporal resolutions, spatial coverage and recording surface, and report clinical outcomes using different data modalities. They suggest future research directions for investigating the mechanisms underlying human AF.
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Affiliation(s)
- Caroline H Roney
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Imperial Centre for Cardiac Engineering, Imperial College London, London, UK
| | - Andrew L Wit
- Imperial Centre for Cardiac Engineering, Imperial College London, London, UK.,Department of Pharmacology, Columbia University College of Physicians and Surgeons, New York, NY, US
| | - Nicholas S Peters
- Imperial Centre for Cardiac Engineering, Imperial College London, London, UK.,National Heart and Lung Institute, Imperial College London, London, UK
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Aronis KN, Ali RL, Liang JA, Zhou S, Trayanova NA. Understanding AF Mechanisms Through Computational Modelling and Simulations. Arrhythm Electrophysiol Rev 2019; 8:210-219. [PMID: 31463059 PMCID: PMC6702471 DOI: 10.15420/aer.2019.28.2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 06/17/2019] [Indexed: 12/21/2022] Open
Abstract
AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF.
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Affiliation(s)
- Konstantinos N Aronis
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
- Division of Cardiology, Johns Hopkins HospitalBaltimore, MD, US
| | - Rheeda L Ali
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
| | - Jialiu A Liang
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
| | - Shijie Zhou
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
| | - Natalia A Trayanova
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
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Rajagopal K, Parastesh F, Azarnoush H, Hatef B, Jafari S, Berec V. Spiral waves in externally excited neuronal network: Solvable model with a monotonically differentiable magnetic flux. CHAOS (WOODBURY, N.Y.) 2019; 29:043109. [PMID: 31042930 DOI: 10.1063/1.5088654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2019] [Accepted: 03/21/2019] [Indexed: 06/09/2023]
Abstract
Spiral waves are particular spatiotemporal patterns connected to specific phase singularities representing topological wave dislocations or nodes of zero amplitude, witnessed in a wide range of complex systems such as neuronal networks. The appearance of these waves is linked to the network structure as well as the diffusion dynamics of its blocks. We report a novel form of the Hindmarsh-Rose neuron model utilized as a square neuronal network, showing the remarkable multistructure of dynamical patterns ranging from characteristic spiral wave domains of spatiotemporal phase coherence to regions of hyperchaos. The proposed model comprises a hyperbolic memductance function as the monotone differentiable magnetic flux. Hindmarsh-Rose neurons with an external electromagnetic excitation are considered in three different cases: no excitation, periodic excitation, and quasiperiodic excitation. We performed an extensive study of the neuronal dynamics including calculation of equilibrium points, bifurcation analysis, and Lyapunov spectrum. We have found the property of antimonotonicity in bifurcation scenarios with no excitation or periodic excitation and identified wide regions of hyperchaos in the case of quasiperiodic excitation. Furthermore, the formation and elimination of the spiral waves in each case of external excitation with respect to stimuli parameters are investigated. We have identified novel forms of Hindmarsh-Rose bursting dynamics. Our findings reveal multipartite spiral wave formations and symmetry breaking spatiotemporal dynamics of the neuronal model that may find broad practical applications.
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Affiliation(s)
| | - Fatemeh Parastesh
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Ave., Tehran 15875-4413, Iran
| | - Hamed Azarnoush
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Ave., Tehran 15875-4413, Iran
| | - Boshra Hatef
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran 14359-16471, Iran
| | - Sajad Jafari
- Nonlinear Systems and Applications, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Vesna Berec
- Institute of Nuclear Sciences, Vinca, PO Box 522, 11001 Belgrade, Serbia
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Modeling specific action potentials in the human atria based on a minimal single-cell model. PLoS One 2018; 13:e0190448. [PMID: 29360837 PMCID: PMC5779667 DOI: 10.1371/journal.pone.0190448] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 12/14/2017] [Indexed: 12/01/2022] Open
Abstract
We present an effective method to model empirical action potentials of specific patients in the human atria based on the minimal model of Bueno-Orovio, Cherry and Fenton adapted to atrial electrophysiology. In this model, three ionic are currents introduced, where each of it is governed by a characteristic time scale. By applying a nonlinear optimization procedure, a best combination of the respective time scales is determined, which allows one to reproduce specific action potentials with a given amplitude, width and shape. Possible applications for supporting clinical diagnosis are pointed out.
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Campana C, Akar FG. Commentary: Atrial Fibrillation Dynamics and Ionic Block Effects in Six Heterogeneous Human 3D Virtual Atria with Distinct Repolarization Dynamics. Front Bioeng Biotechnol 2017; 5:59. [PMID: 29057224 PMCID: PMC5635327 DOI: 10.3389/fbioe.2017.00059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 09/20/2017] [Indexed: 11/26/2022] Open
Affiliation(s)
- Chiara Campana
- Icahn School of Medicine at Mount Sinai, The Cardiovascular Institute, New York, NY, United States
| | - Fadi G Akar
- Icahn School of Medicine at Mount Sinai, The Cardiovascular Institute, New York, NY, United States
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