Transcriptomic Approaches to Modelling Long Term Changes in Human Cardiac Electrophysiology

Slow changes in the activity of the heart occur with time scales from days through to decades, and may in part result from changes in cardiomyocyte properties. The cellular mechanisms of the cardiomyocyte action potential have time scales from < ms to hundreds of ms. Although the quantitative dynamic relations between mRNA transcription, protein synthesis, trafficking, recycling, and membrane protein activity are unclear, mRNA-Seq can be used to inform parameters in cell excitation equations. We use such transcriptomic data from a non-human primate to scale maximal conductances in the O’Hara-Rudy (2011) family of human ventricular cell models, and to predict diurnal changes in human ventricular action potential durations. These are related to circadian changes in the incidence of sudden cardiac deaths. Transcriptomic analysis of human fetal hearts between 9 and 16 weeks gestational age is beginning to be used to inform ventricular cell and tissue models of the electrophysiology of the developing fetal heart

In silico methods for the prediction of drug-induced cardiotoxicity

Unexpected adverse reactions, especially unsafe cardiac effects, are a major concern of pharmaceutical companies that can prompt them to both discontinue drugs currently in development and withdraw drugs already on the market. Therefore, the safety assessment is a key stage of both the drug development process and the current regulatory framework of clinical trials. Given the importance of unforeseen acute electrophysiological effects in precipitating potentially lethal arrhythmias, the current preclinical testing stages of drug development are largely focused on their detection. However, a substantial number of drugs also affect cardiac function on many other levels, including contractility, mitochondria function and cell signalling. A number of in vitro, in vivo and in silico approaches capable of detecting different types of possible cardiovascular side effects have been proposed recently. Among those, human-based computational methods hold a great potential to increase the productivity of drug discovery pipelines, drive a more rational drug design and replace costly animal experiments that have limited translational ability for humans. Therefore, the goal of this thesis is to propose a computational approach to predict drug-induced cardiotoxicity. A multi-label machine learning classification approach is used to simultaneously predict multiple forms of clinical cardiac side effects and take into account relationships between those forms of toxicity. In the last part of this thesis, the effects of trafficking impairment, as one of the cardiotoxicity mechanisms, are then investigated using simulations of action potential models

Patient and Disease-Specific Induced Pluripotent Stem Cells for Discovery of Personalized Cardiovascular Drugs and Therapeutics.

Human induced pluripotent stem cells (iPSCs) have emerged as an effective platform for regenerative therapy, disease modeling, and drug discovery. iPSCs allow for the production of limitless supply of patient-specific somatic cells that enable advancement in cardiovascular precision medicine. Over the past decade, researchers have developed protocols to differentiate iPSCs to multiple cardiovascular lineages, as well as to enhance the maturity and functionality of these cells. Despite significant advances, drug therapy and discovery for cardiovascular disease have lagged behind other fields such as oncology. We speculate that this paucity of drug discovery is due to a previous lack of efficient, reproducible, and translational model systems. Notably, existing drug discovery and testing platforms rely on animal studies and clinical trials, but investigations in animal models have inherent limitations due to interspecies differences. Moreover, clinical trials are inherently flawed by assuming that all individuals with a disease will respond identically to a therapy, ignoring the genetic and epigenomic variations that define our individuality. With ever-improving differentiation and phenotyping methods, patient-specific iPSC-derived cardiovascular cells allow unprecedented opportunities to discover new drug targets and screen compounds for cardiovascular disease. Imbued with the genetic information of an individual, iPSCs will vastly improve our ability to test drugs efficiently, as well as tailor and titrate drug therapy for each patient

Generation of cardiomyocytes from human-induced pluripotent stem cells resembling atrial cells with ability to respond to adrenoceptor agonists

Atrial fibrillation (AF) is the most common chronic arrhythmia presenting a heavy disease burden. We report a new approach for generating cardiomyocytes (CMs) resembling atrial cells from human-induced pluripotent stem cells (hiPSCs) using a combination of Gremlin 2 and retinoic acid treatment. More than 40% of myocytes showed rod-shaped morphology, expression of CM proteins (including ryanodine receptor 2, α-actinin-2 and F-actin) and striated appearance, all of which were broadly similar to the characteristics of adult atrial myocytes (AMs). Isolated myocytes were electrically quiescent until stimulated to fire action potentials with an AM profile and an amplitude of approximately 100 mV, arising from a resting potential of approximately −70 mV. Single-cell RNA sequence analysis showed a high level of expression of several atrial-specific transcripts including NPPA, MYL7, HOXA3, SLN, KCNJ4, KCNJ5 and KCNA5. Amplitudes of calcium transients recorded from spontaneously beating cultures were increased by the stimulation of α-adrenoceptors (activated by phenylephrine and blocked by prazosin) or β-adrenoceptors (activated by isoproterenol and blocked by CGP20712A). Our new approach provides human AMs with mature characteristics from hiPSCs which will facilitate drug discovery by enabling the study of human atrial cell signalling pathways and AF. This article is part of the theme issue ‘The heartbeat: its molecular basis and physiological mechanisms’

Chamber-specific transcriptional responses in atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia, yet the molecular signature of the vulnerable atrial substrate is not well understood. Here, we delineated a distinct transcriptional signature in right versus left atrial cardiomyocytes (CMs) at baseline and identified chamber-specific gene expression changes in patients with a history of AF in the setting of end-stage heart failure (AF+HF) that are not present in heart failure alone (HF). We observed that human left atrial (LA) CMs exhibited Notch pathway activation and increased ploidy in AF+HF but not in HF alone. Transient activation of Notch signaling within adult CMs in a murine genetic model is sufficient to increase ploidy in both atrial chambers. Notch activation within LA CMs generated a transcriptomic fingerprint resembling AF, with dysregulation of transcription factor and ion channel genes, including Pitx2, Tbx5, Kcnh2, Kcnq1, and Kcnip2. Notch activation also produced distinct cellular electrophysiologic responses in LA versus right atrial CMs, prolonging the action potential duration (APD) without altering the upstroke velocity in the left atrium and reducing the maximal upstroke velocity without altering the APD in the right atrium. Our results support a shared human/murine model of increased Notch pathway activity predisposing to AF

Induced pluripotent stem cell-based organ-on-a-chip as personalized drug screening tools: A focus on neurodegenerative disorders

The Organ-on-a-Chip (OoC) technology shows great potential to revolutionize the drugs development pipeline by mimicking the physiological environment and functions of human organs. The translational value of OoC is further enhanced when combined with patient-specific induced pluripotent stem cells (iPSCs) to develop more realistic disease models, paving the way for the development of a new generation of patient-on-a-chip devices. iPSCs differentiation capacity leads to invaluable improvements in personalized medicine. Moreover, the connection of single-OoC into multi-OoC or body-on-a-chip allows to investigate drug pharmacodynamic and pharmacokinetics through the study of multi-organs cross-talks. The need of a breakthrough thanks to this technology is particularly relevant within the field of neurodegenerative diseases, where the number of patients is increasing and the successful rate in drug discovery is worryingly low. In this review we discuss current iPSC-based OoC as drug screening models and their implication in development of new therapies for neurodegenerative disorders

Preclinical Models of Cardiac Disease:A Comprehensive Overview for Clinical Scientists

For recent decades, cardiac diseases have been the leading cause of death and morbidity worldwide. Despite significant achievements in their management, profound understanding of disease progression is limited. The lack of biologically relevant and robust preclinical disease models that truly grasp the molecular underpinnings of cardiac disease and its pathophysiology attributes to this stagnation, as well as the insufficiency of platforms that effectively explore novel therapeutic avenues. The area of fundamental and translational cardiac research has therefore gained wide interest of scientists in the clinical field, while the landscape has rapidly evolved towards an elaborate array of research modalities, characterized by diverse and distinctive traits. As a consequence, current literature lacks an intelligible and complete overview aimed at clinical scientists that focuses on selecting the optimal platform for translational research questions. In this review, we present an elaborate overview of current in vitro, ex vivo, in vivo and in silico platforms that model cardiac health and disease, delineating their main benefits and drawbacks, innovative prospects, and foremost fields of application in the scope of clinical research incentives.</p

Addressing variability in iPSC-derived models of human disease: guidelines to promote reproducibility

Induced pluripotent stem cell (iPSC) technologies have provided in vitro models of inaccessible human cell types, yielding new insights into disease mechanisms especially for neurological disorders. However, without due consideration, the thousands of new human iPSC lines generated in the past decade will inevitably affect the reproducibility of iPSC-based experiments. Differences between donor individuals, genetic stability and experimental variability contribute to iPSC model variation by impacting differentiation potency, cellular heterogeneity, morphology, and transcript and protein abundance. Such effects will confound reproducible disease modelling in the absence of appropriate strategies. In this Review, we explore the causes and effects of iPSC heterogeneity, and propose approaches to detect and account for experimental variation between studies, or even exploit it for deeper biological insight

Modeling hypertrophic cardiomyopathy: Mechanistic insights and pharmacological intervention

Hypertrophic cardiomyopathy (HCM) is a prevalent and complex cardiovascular disease where cardiac dysfunction often associates with mutations in sarcomeric genes. Various models based on tissue explants, isolated cardiomyocytes, skinned myofibrils, and purified actin/myosin preparations have uncovered disease hallmarks, enabling the development of putative therapeutics, with some reaching clinical trials. Newly developed human pluripotent stem cell (hPSC)-based models could be complementary by overcoming some of the inconsistencies of earlier systems, whilst challenging and/or clarifying previous findings. In this article we compare recent progress in unveiling multiple HCM mechanisms in different models, highlighting similarities and discrepancies. We explore how insight is facilitating the design of new HCM therapeutics, including those that regulate metabolism, contraction and heart rhythm, providing a future perspective for treatment of HCM