Modeling Human Atrial Patho-Electrophysiology from Ion Channels to ECG - Substrates, Pharmacology, Vulnerability, and P-Waves

Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This thesis presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF

Modeling Human Atrial Patho-Electrophysiology from Ion Channels to ECG - Substrates, Pharmacology, Vulnerability, and P-Waves

Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This book presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF

Modeling Human Atrial Patho-Electrophysiology from Ion Channels to ECG - Substrates, Pharmacology, Vulnerability, and P-Waves

Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This book presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF

Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction

心房細動の遺伝的基盤を解明 --大規模ゲノムデータによる病態解明と遺伝的リスクスコア構築--. 京都大学プレスリリース. 2023-01-20.Atrial fibrillation (AF) is a common cardiac arrhythmia resulting in increased risk of stroke. Despite highly heritable etiology, our understanding of the genetic architecture of AF remains incomplete. Here we performed a genome-wide association study in the Japanese population comprising 9, 826 cases among 150, 272 individuals and identified East Asian-specific rare variants associated with AF. A cross-ancestry meta-analysis of >1 million individuals, including 77, 690 cases, identified 35 new susceptibility loci. Transcriptome-wide association analysis identified IL6R as a putative causal gene, suggesting the involvement of immune responses. Integrative analysis with ChIP-seq data and functional assessment using human induced pluripotent stem cell-derived cardiomyocytes demonstrated ERRg as having a key role in the transcriptional regulation of AF-associated genes. A polygenic risk score derived from the cross-ancestry meta-analysis predicted increased risks of cardiovascular and stroke mortalities and segregated individuals with cardioembolic stroke in undiagnosed AF patients. Our results provide new biological and clinical insights into AF genetics and suggest their potential for clinical applications

The Molecular Anatomy of Mitochondrial Disease: Identification and Characterisation of Novel Nuclear-Encoded Mitochondrial Disease Genes

Mitochondrial diseases are a group of clinically and genetically heterogeneous disorders typically associated with abnormal oxidative phosphorylation (OXPHOS). In recent years, next generation sequencing technologies have allowed for accurate genetic diagnoses of inherited mitochondrial diseases directly from patient DNA by facilitating the identification of potential candidate genetic defects in either nuclear or mitochondrial genomes. In such a manner, two compound heterozygous sequence variants in COA7, which encodes a putative cytochrome c oxidase (Complex IV, COX) assembly factor, and homozygous recessive sequence variants in TMCO6, which encodes an uncharacterised protein, were identified in patients presenting with classical clinical and biochemical hallmarks of mitochondrial disease. The aim of this work was to 1) assess the pathogenicity of the COA7 and TMCO6 mutant variants in causing mitochondrial disease, and 2) to investigate the association of the resulting proteins in the assembly pathways of complexes of the mitochondrial respiratory chain: Complex IV (CIV, COX) for COA7 and Complex I (CI) for TMCO6. Compound heterozygous mutant variants in COA7 (NM_023077.3:c.410A>G;c.287+1G>T) led to total disappearance of its gene product in patient skin fibroblasts, owing to two aberrant mRNA transcripts. Loss of COA7 steady-state level correlated with low abundance of certain COX subunits, intermediates, monomeric and supercomplex COX species, as well as isolated COX enzymatic deficiency. Stable expression of COA7WT in patient fibroblasts by lentivirus-mediated complementation rescued COX abundance, the quantities of its affected subunits, subassembly and supercomplex species, and its activity, to normal levels, confirming the pathogenicity of the compound heterozygous COA7 mutant variants. A combination of super-resolution microscopy and subcellular fractionation and protease digestion studies confirmed the intracellular localisation of COA7 to be the mitochondrial intermembrane space. Secondly, a novel homozygous recessive variant in TMCO6 (NM_018502.5: c.271C>T) was identified in a paediatric proband presenting with severe developmental delay, generalised hypotonia and progressive cerebral and cerebellar atrophy. Biochemical measurement of a skeletal muscle biopsy revealed CI enzymatic deficiency, and patient-derived skin fibroblasts showed destabilisation of CI-containing supercomplexes. TMCO6 was found to co-localise with the CI holocomplex by 2D-BNGE, and this result was further corroborated by immunoprecipitation experiments. Additionally, cellular models for TMCO6 gene silencing and overexpression were characterised, and an attempted generation of a knockout cellular model is described. Subcellular fractionation and protease treatment experiments determined TMCO6 to localise to the mitochondrial inner membrane. A Tmco6-knockout murine model was characterised, which exhibited several neurological, physiological and motor debilities, isolated CI deficiency in heart and skeletal muscle, and abnormal cardiac electrophysiology. Recombinant AAV-mediated expression of wildtype, human TMCO6 rescued the CI deficiency and electrophysiological function of 3 month-old knockout mice hearts. In contrast, stable expression of the patient mutant protein variant failed to recover the isolated CI deficiency, and additionally resulted in severe cardiac fibrosis. Together, these findings causally link ablation of, or mutations in, TMCO6 with mitochondrial dysfunction and disease.Medical Research Counci

Deep Learning in Cardiology

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

Interpretable Mechanistic and Machine Learning Models for Pre-dicting Cardiac Remodeling from Biochemical and Biomechanical Features

Biochemical and biomechanical signals drive cardiac remodeling, resulting in altered heart physiology and the precursor for several cardiac diseases, the leading cause of death for most racial groups in the USA. Reversing cardiac remodeling requires medication and device-assisted treatment such as Cardiac Resynchronization Therapy (CRT), but current interventions produce highly variable responses from patient to patient. Mechanistic modeling and Machine learning (ML) approaches have the functionality to aid diagnosis and therapy selection using various input features. Moreover, \u27Interpretable\u27 machine learning methods have helped make machine learning models fairer and more suited for clinical application. The overarching objective of this doctoral work is to develop computational models that combine an extensive array of clinically measured biochemical and biomechanical variables to enable more accurate identification of heart failure patients prone to respond positively to therapeutic interventions. In the first aim, we built an ensemble ML classification algorithm using previously acquired data from the SMART-AV CRT clinical trial. Our classification algorithm incorporated 26 patient demographic and medical history variables, 12 biomarker variables, and 18 LV functional variables, yielding correct CRT response prediction in 71% of patients. In the second aim, we employed a machine learning-based method to infer the fibrosis-related gene regulatory network from RNA-seq data from the MAGNet cohort of heart failure patients. This network identified significant interactions between transcription factors and cell synthesis outputs related to cardiac fibrosis - a critical driver of heart failure. Novel filtering methods helped us prioritize the most critical regulatory interactions of mechanistic forward simulations. In the third aim, we developed a logic-based model for the mechanistic network of cardiac fibrosis, integrating the gene regulatory network derived from aim two into a previously constructed cardiac fibrosis signaling network model. This integrated model implemented biochemical and biomechanical reactions as ordinary differential equations based on normalized Hill functions. The model elucidated the semi-quantitative behavior of cardiac fibrosis signaling complexity by capturing multi-pathway crosstalk and feedback loops. Perturbation analysis predicted the most critical nodes in the mechanistic model. Patient-specific simulations helped identify which biochemical species highly correlate with clinical measures of patient cardiac function

The contact electrogram and its architectural determinants in atrial fibrillation

The electrogram is the sine qua non of excitable tissues, yet classification in atrial fibrillation (AF) remains poorly related to substrate factors. The objective of this thesis was to establish the relationship between electrograms and two commonly implicated substrate factors, connexin 43 and fibrosis in AF. The substrates and methods chosen to achieve this ranged from human acutely induced AF using open chest surgical mapping (Chapter 6), ex vivo whole heart Langendorff (Chapter 7) with in vivo telemetry confirming spontaneous AF in a new species of rat, the Brown Norway and finally isolated atrial preparations from an older cohort of rats using orthogonal pacing and novel co-localisation methods at sub-millimetre resolution and in some atria, optical mapping (Chapter 8). In rodents, electrode size and spacing was varied (Chapters 5, 10) to study its effects on structure function correlations (Chapter 9). Novel indices of AF organisation and automated electrogram morphology were used to quantify function (Chapter 4). Key results include the discoveries that humans without any history of prior AF have sinus rhythm electrograms with high spectral frequency content, that wavefront propagation velocities correlated with fibrosis and connexin phosphorylation ratios, that AF heterogeneity of conduction correlates to fibrosis and that orthogonal pacing in heavily fibrosed atria causes anisotropy in electrogram-fibrosis correlations. Furthermore, fibrosis and connexin 43 have differing and distinct spatial resolutions in their relationship with AF organisational indices. In conclusion a new model of AF has been found, and structure function correlations shown on an unprecedented scale, but with caveats of electrode size and direction dependence. These findings impact structure function methods and prove the effect of substrate on AF organisation.Open Acces

Applying computational approaches to the understanding of the consequences and opportunities of ion channel properties in atrial fibrillation

Cardiac arrhythmias are disorders of the electrical system of the heart and an often clinically-challenging group of disorders. Atrial fibrillation (AF) is the most common cardiac arrhythmia in the general population; it is associated with significant morbidity and mortality. Available antiarrhythmic drugs (AADs) for the treatment of AF are older molecules with sub- optimal efficacy and safety profiles. Recent advances in basic electrophysiology and the development of sophisticated mathematical modeling approaches could help in expanding our understanding of the basic mechanisms of AF and assist in the development of novel AF- selective AADs. The purpose of this thesis was to utilize computational approaches to the understanding of the consequences and opportunities of ion channel properties, with a special emphasis on AF. The cardiac action potential is the basic functional unit of the electrical system of the heart and is the manifestation of coordinated current fluxes through specialized proteins known as ion channels. Antiarrhythmic drugs act through modulation of ion channel properties. We hypothesized that mathematical modeling could be used to study and optimize the pharmacodynamic properties of AADs for the treatment of AF. We demonstrated that the pharmacodynamic properties (binding/unbinding characteristics) of a state-dependent Na+- channel blocker modulate the drug’s anti-/proarrhythmic actions with inactivated-state blockers being optimally AF-selective. The optimized drug’s selectivity for AF was the result of its rate- selectivity (stronger effects at fast vs slow cardiomyocyte activation rates) with relatively mild atrial-selective (stronger effects in atrial vs ventricular cardiomyocytes) actions. We found that the optimally AF-selective Na+-channel blocker had sub-optimal anti-AF efficacy, but that slightly less selective drugs had favorable AF-termination rates. We then sought to explore potential current-block combinations with synergistic AF- selective properties. Using mathematical modeling and laboratory experiments, we demonstrated that the combination of optimized state-dependent Na+-channel block and K+- channel block had synergistic effects, significantly augmenting AF termination rates for any level of AF-selectivity vs pure Na+-channel block. The mechanisms of these synergistic effects were found to be mediated by the functional interaction between the action potential prolonging- v effects of K+-channel block, the Na+-channel blocker’s voltage-dependent binding/unbinding properties and the Na+ channel’s inactivation characteristics, highlighting the non-linear nature of the cardiac action potential’s dynamics. Traditional K+ currents targeted by AADs have significant ventricular proarrhythmic liabilities. Using recent experimental observations, we updated the mathematic formulation for the inactivation dynamics of the ultra-rapid delayed-rectifier K+ current (IKur), an atrial-specific current. Using this model, we showed that, contrary to what had been proposed in the published literature, IKur rate-dependent properties are mediated by its activation properties with minimal contribution from inactivation, under physiological conditions. We also demonstrated that the contribution of IKur to action potential repolarization is preserved, or even increased, in the setting of electrical remodeling-induced IKur downregulation. Finally, we described the mechanisms of the forward rate-dependent of IKur block, mediated by functional non-linear interactions with the rapid delayed inward-rectifier K+ current (IKr), the only K+ current with such properties. Until recently, fibroblasts were considered to be electrically inactive. More recently, experimental work demonstrated the presence of functional ionic current on the fibroblast and possible cardiomyocyte-fibroblast coupling. Here, we described a novel kind of heart failure- induced electrical remodeling involving the fibroblasts ion channels. This was characterized by downregulation of the fibroblast voltage-dependent K+ current (IKv,fb) and upregulation of the fibroblast inward-rectifier K+ current (IKir,fb). We then implemented our experimental findings into a mathematical model of cardiomyocyte-fibroblast coupling and found fibroblast electrical remodeling to have significant effects on the cardiomyocyte’s electrophysiological properties. In a 2-dimension model of simulated AF, downregulation of IKv,fb had an antiarrhythmic effect whereas IKir,fb upregulation was found to be proarrhythmic. The studies presented here utilized mathematical modeling to study non-linear systems in cardiac electrophysiology to tackle questions that would have been difficult to approach with traditional laboratory-based experimentation. They also showcased how theoretical results can help orient and receive confirmation with subsequent experimental work or, conversely, novel experimental findings results be implemented into a mathematical model to investigate potential consequences. Mathematical modeling is a promising tool to help in studying the complex and vi non-linear effects of pharmacological modulation of ion channel properties and assist in the development of optimized antiarrhythmics for the treatment of AF, a major unmet need in clinical medicine. As models increase in sophistication to better represent the cardiomyocyte’s electrophysiology, they will almost certainly play an ever-growing role in expanding our understanding of the mechanisms of complex arrhythmias.Les arythmies cardiaques représentent une famille de pathologies du système électrique cardiaque. La fibrillation auriculaire (FA), est l’arythmie cardiaque la plus fréquente dans la population générale et est associée à un fardeau de morbidité et mortalité cardiovasculaire important. Les médicaments antiarythmiques utilisées dans le traitement de la FA sont de vieilles molécules avec une efficacité sous-optimale et des effets secondaires importants. Les avancées récentes en électrophysiologie cardiaque fondamentale et le développement d’outils de modélisation mathématique ont le potentiel d’élargir notre compréhension des mécanismes pathophysiologiques en FA et contribuer au développement de nouveaux médicaments antiarythmiques optimisés pour le traitement de la FA. L’objectif global de cette thèse est d’utiliser les méthodes de modélisation mathématique pour étudier les conséquences et opportunités thérapeutiques de la modulation des canaux ioniques cardiaques, avec une emphase sur la FA. Le potentiel d’action cardiaque est l’unité fonctionnelle de base du système électrique cardiaque ; il est le résultat du flux coordonné de courants électriques à travers de protéines spécialisées, les canaux ioniques. Les molécules antiarythmiques agissent à travers la modulation des canaux ioniques cardiaques. Nous avons posé l’hypothèse que des modèles mathématiques pourraient être utilisés pour étudier et optimiser les propriétés pharmacodynamiques d’un médicament antiarythmique pour le traitement de la FA. Nous avons démontré que les propriétés pharmacodynamiques (propriétés de liage et déliage) d’un bloqueur des canaux Na+ état-dépendant modulent les effets anti- et pro-arythmiques de la molécule ; un bloqueur Na+ sélectif pour l’état inactivé du canal serait maximalement FA-sélectif. Cette sélectivité pour la FA est la conséquence de la sélectivité pour la fréquence (effet thérapeutique plus important à des fréquences d’activation du cardiomyocyte élevées vs basses) avec une contribution relativement faible de la sélectivité auriculaire (effet thérapeutique plus important sur les cardiomyocytes auriculaires vs ventriculaires). Par la suite, nous avons exploré des combinaisons de bloqueurs ioniques ayant des propriétés anti-FA synergiques. En utilisant des modèles mathématiques et des expériences en laboratoire, nous avons démontré que la combinaison d’un bloqueur des canaux Na+ et d’un iii bloqueur des canaux K+ a des effets synergiques, augmentant de façon importante l’efficacité anti-FA pour un même degré de sélectivité vs un bloqueur des canaux Na+ seul. Le mécanisme de synergie a été élucidé et consiste d’effets fonctionnels médiés par l’interaction du prolongement de la durée du potentiel d’action causé par le bloque des canaux K+, les propriétés voltage-dépendantes du liage et déliage du bloqueur des canaux Na+ ainsi que des propriétés d’inactivation des canaux Na+, démontrant la nature hautement non-linéaire des dynamiques du potentiel d’action cardiaque. Les courants K+ ciblés par les médicaments antiarythmiques ont des effets proarythmiques ventriculaires importants. En utilisant des données expérimentales récentes, nous avons proposé une formulation mise à jour des dynamiques d’inactivation du courant K+ IKur, un courant auriculo-sélectif. En utilisant ce modèle, nous avons démontré que, contrairement à ce qui avait été précédemment proposé, les propriétés fréquence-dépendantes du courant IKur dépendent de ses caractéristiques d’activation avec une contribution négligeable de ses propriétés d’inactivation, sous conditions physiologiques normales. Nous avons également démontré que la contribution de IKur à la repolarisation du potentiel d’action est maintenue, voir augmentée, dans le contexte de la diminution de IKur en situation de remodelage électrique induit par la FA. Finalement, nous avons décrit le mécanisme qui sous-tend les propriétés fréquence-dépendantes du bloque de IKur, l’unique courant K+ avec de telles caractéristiques. Jusqu’à très récemment, les fibroblastes cardiaques étaient considérés comme électriquement inactifs. Des travaux expérimentaux ont démontré la présence de canaux ioniques sur la surface de ces fibroblastes ainsi que la possibilité de couplage électrique entre cardiomyocytes et fibroblastes. Nous avons décrit un nouveau type de remodelage électrique en situation d’insuffisance cardiaque, le remodelage des courants ioniques des fibroblastes cardiaques. Ce remodelage est caractérisé par une diminution du courant K+ voltage-dépendant IKv,fb et une augmentation du courant K+ IKir,fb. Nous avons par la suite incorporé ces trouvailles expérimentales dans un modèle mathématique simulant l’interaction électrique entre cardiomyocytes et fibroblastes et montré que le remodelage électrique des fibroblastes peut avoir un impact important sur les propriétés électrophysiologiques des cardiomyocytes. Dans iv un modèle 2-dimensionel de FA, nous avons trouvé que la diminution de IKv,fb a un effet antiarythmique alors que l’augmentation de IKir,fb a des effets proarythmiques. Les études ici présentées utilisent les méthodes de modélisation mathématique pour l’étude de systèmes non-linéaires en électrophysiologie cardiaque et aborder des avenues de recherche difficilement accessibles aux méthodes de laboratoire traditionnelles. Elles démontrent également comment des résultats théoriques peuvent orienter et trouver confirmation dans des travaux expérimentaux subséquents ou, à l’inverse, des trouvailles expérimentales peuvent être implémentées dans les modèles mathématiques pour investiguer les conséquences de celles-ci. La modélisation mathématique est un outil prometteur pour l’étude des effets complexes et non-linéaires de la modulation pharmacologique des canaux ioniques et ainsi contribuer au développement de médicaments antiarythmiques optimisés pour le traitement de la FA, un besoin clinique majeur