Deep Learning-Based Proarrhythmia Analysis Using Field Potentials Recorded From Human Pluripotent Stem Cells Derived Cardiomyocytes
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PROVIDER: S-EPMC6570462 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
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Project description:Drug-induced cardiotoxicity and hepatotoxicity are major causes of drug attrition. To decrease late-stage drug attrition, pharmaceutical and biotechnology industries need to establish biologically relevant models that use phenotypic screening to detect drug-induced toxicity in vitro. In this study, we sought to rapidly detect patterns of cardiotoxicity using high-content image analysis with deep learning and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). We screened a library of 1280 bioactive compounds and identified those with potential cardiotoxic liabilities in iPSC-CMs using a single-parameter score based on deep learning. Compounds demonstrating cardiotoxicity in iPSC-CMs included DNA intercalators, ion channel blockers, epidermal growth factor receptor, cyclin-dependent kinase, and multi-kinase inhibitors. We also screened a diverse library of molecules with unknown targets and identified chemical frameworks that show cardiotoxic signal in iPSC-CMs. By using this screening approach during target discovery and lead optimization, we can de-risk early-stage drug discovery. We show that the broad applicability of combining deep learning with iPSC technology is an effective way to interrogate cellular phenotypes and identify drugs that may protect against diseased phenotypes and deleterious mutations.
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Project description:Among various cardiac safety concerns, proarrhythmia risks, including QT prolongation leading to Torsade de Pointes, is one of major cause for drugs being withdrawn (~45% 1975-2007). Preclinical study requires the evaluation of proarrhythmia using in silico, in vitro, and/or animal models. Considering that the primary consumers of prescription drugs are elderly patients, applications of "aging-in-a-dish" models would be appropriate for screening proarrhythmia risks. However, acquiring such models, including cardiomyocytes (CMs) derived from induced pluripotent stem cells (iPSCs), presents extensive challenges. We proposed the hypothesis that CMs differentiated from iPSCs derived from Hutchinson-Gilford progeria syndrome (HGPS, progeria) patients, an ultra-rare premature aging syndrome, can mimic the phenotypes of aging CMs. Our objective, therefore, was to examine this hypothesis by analyzing the response of 11 reference compounds utilized by the Food and Drug Administration (FDA)'s Comprehensive in vitro Proarrhythmia Assay (CiPA) using progeria and control CMs. As a sensitive surrogate marker of modulating cardiac excitation-contraction coupling, we evaluated drug-induced changes in calcium transient (CaT). We observed that the 80% CaT peak duration in the progeria CMs (0.98 ± 0.04 s) was significantly longer than that of control CMs (0.70 ± 0.05 s). Furthermore, when the progeria CMs were subjected to four doses of 11 compounds from low-, intermediate-, and high-risk categories, they demonstrated greater arrhythmia susceptibility than control cells, as shown through six-parameter CaT profile analyses. We also employed the regression analysis established by CiPA to classify the 11 reference compounds and compared proarrhythmia susceptibilities between the progeria and control CMs. This analysis revealed a greater proarrhythmia susceptibility in the progeria CMs compared to the control CMs. Interestingly, in both CMs, the compounds categorized as low risk did not exceed the safety risk threshold of 0.8. In conclusion, our study demonstrates increased proarrhythmia sensitivity in progeria CMs when tested with reference compounds. Future studies are needed to analyze underlying mechanisms and further validate our findings using a larger array of reference compounds.
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Project description:The detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological evaluation of induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs). We report that deep learning with a dataset that combines magnetic signals estimated using numerical simulation and actual noise data is effective in the detection of weak biomagnetic signals. To verify the feasibility of this method, we measured artificially generated magnetic signals that mimic cellular magnetic fields using a superconducting quantum interference device and attempted peak detection using a long short-term memory network. We correctly detected 80.0% of the peaks and the method achieved superior detection performance compared with conventional methods. Next, we attempted peak detection for magnetic signals measured from mouse iPS-CMs. The number of detected peaks was consistent with the spontaneous beats counted using microscopic observation and the average peak waveform achieved good similarity with the prediction. We also observed the synchronization of peak positions between simultaneously measured field potentials and magnetic signals. Furthermore, the magnetic measurements of cell samples treated with isoproterenol showed potential for the detection of chronotropic effects. These results suggest that the proposed method is effective and has potential application in the safety assessment of regenerative medicine and drug screening.
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Project description:Multi electrode arrays (MEAs) are increasingly used to detect external field potentials in electrically active cells. Recently, in combination with cardiomyocytes derived from human (induced) pluripotent stem cells they have started to become a preferred tool to examine newly developed drugs for potential cardiac toxicity in pre-clinical safety pharmacology. The most important risk parameter is proarrhythmic activity in cardiomyocytes which can cause sudden cardiac death. Whilst MEAs can provide medium- to high- throughput noninvasive assay platform, the translation of a field potential to cardiac action potential (normally measured by low-throughput patch clamp) is complex so that accurate assessment of drug risk to the heart is in practice still challenging. To address this, we used computational simulation to study the theoretical relationship between aspects of the field potential and the underlying cardiac action potential. We then validated the model in both primary mouse- and human pluripotent (embryonic) stem cell-derived cardiomyocytes showing that field potentials measured in MEAs could be converted to action potentials that were essentially identical to those determined directly by electrophysiological patch clamp. The method significantly increased the amount of information that could be extracted from MEA measurements and thus combined the advantages of medium/high throughput with more informative readouts. We believe that this will benefit the analysis of drug toxicity screening of cardiomyocytes using in time and accuracy.
| S-EPMC5854265 | biostudies-literature
Project description:Generation of homogeneous populations of subtype-specific cardiomyocytes (CMs) derived from human induced pluripotent stem cells (iPSCs) and their comprehensive phenotyping is crucial for a better understanding of the subtype-related disease mechanisms and as tools for the development of chamber-specific drugs. The goals of this study were to apply a simple and efficient method for differentiation of iPSCs into defined functional CM subtypes in feeder-free conditions and to obtain a comprehensive understanding of the molecular, cell biological, and functional properties of atrial and ventricular iPSC-CMs on both the single-cell and engineered heart muscle (EHM) level. By a stage-specific activation of retinoic acid signaling in monolayer-based and well-defined culture, we showed that cardiac progenitors can be directed towards a highly homogeneous population of atrial CMs. By combining the transcriptome and proteome profiling of the iPSC-CM subtypes with functional characterizations via optical action potential and calcium imaging, and with contractile analyses in EHM, we demonstrated that atrial and ventricular iPSC-CMs and -EHM highly correspond to the atrial and ventricular heart muscle, respectively. This study provides a comprehensive understanding of the molecular and functional identities characteristic of atrial and ventricular iPSC-CMs and -EHM and supports their suitability in disease modeling and chamber-specific drug screening.
| S-EPMC6124434 | biostudies-literature
Project description:BackgroundEssential tremor (ET) is one of the most common movement disorders, and continuous deep brain stimulation (DBS) is an established treatment for medication-refractory cases. However, the need for increasing stimulation intensities, with unpleasant side effects, and DBS tolerance over time can be problematic. The advent of novel DBS devices now provides the opportunity to longitudinally record LFPs using the implanted pulse generator, which opens up possibilities to implement adaptive DBS algorithms in a real-life setting.MethodsHere we report a case of thalamic LFP activity recorded using a commercially available sensing-enabled DBS pulse generator (Medtronic Percept PC).ResultsIn the OFF-stimulation condition, a peak tremor frequency of 3.8 Hz was identified during tremor evoking movements as assessed by video and accelerometers. Activity at the same and supraharmonic frequency was seen in the frequency spectrum of the LFP data from the left vim nucleus during motor tasks. Coherence analysis showed that peripherally recorded tremor was coherent with the LFP signal at the tremor frequency and supraharmonic frequency.ConclusionThis is the first report of recorded tremor-related thalamic activity using the electrodes and pulse generator of an implanted DBS system. Larger studies are needed to evaluate the clinical potential of these fully implantable systems, and ultimately pulse generators with sensing-coupled algorithms driving stimulation, to really close the loop.
| S-EPMC8956842 | biostudies-literature
Project description:Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) offer a unique in vitro platform to study cardiac diseases, as they recapitulate many disease phenotypes. The membrane potential (Vm) and intracellular calcium (Ca2+) transient (CaT) are usually investigated separately, because incorporating different techniques to acquire both aspects concurrently is challenging. In this study, we recorded Vm and CaT simultaneously to understand the interrelation between these parameters in hiPSC-CMs. For this, we used a conventional patch clamp technique to record Vm, and synchronized this with a Ca2+ imaging system to acquire CaT from same hiPSC-CMs. Our results revealed that the CaT at 90% decay (CaT90) was longer than action potential (AP) duration at 90% repolarization (APD90). In addition, there was also a strong positive correlation between the different parameters of CaT and AP. The majority of delayed after depolarizations (DADs) observed in the Vm recording were also characterized by elevations in the intracellular Ca2+ level, but in some cases no abnormalities were observed in CaT. However, simultaneous fluctuations in CaT were always observed during early after depolarizations (EADs) in Vm In summary, simultaneous recording of Vm and CaT broadens the understanding of the interrelation between Vm and CaT and could be used to elucidate the mechanisms underlying arrhythmia in cardiac disease condition.
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Project description:Human-induced pluripotent stem cells (hiPSCs) can differentiate into functional cardiomyocytes; however, the electrophysiological properties of hiPSC-derived cardiomyocytes have yet to be fully characterized. We performed detailed electrophysiological characterization of highly pure hiPSC-derived cardiomyocytes. Action potentials (APs) were recorded from spontaneously beating cardiomyocytes using a perforated patch method and had atrial-, nodal-, and ventricular-like properties. Ventricular-like APs were more common and had maximum diastolic potentials close to those of human cardiac myocytes, AP durations were within the range of the normal human electrocardiographic QT interval, and APs showed expected sensitivity to multiple drugs (tetrodotoxin, nifedipine, and E4031). Early afterdepolarizations (EADs) were induced with E4031 and were bradycardia dependent, and EAD peak voltage varied inversely with the EAD take-off potential. Gating properties of seven ionic currents were studied including sodium (I(Na)), L-type calcium (I(Ca)), hyperpolarization-activated pacemaker (I(f)), transient outward potassium (I(to)), inward rectifier potassium (I(K1)), and the rapidly and slowly activating components of delayed rectifier potassium (I(Kr) and I(Ks), respectively) current. The high purity and large cell numbers also enabled automated patch-clamp analysis. We conclude that these hiPSC-derived cardiomyocytes have ionic currents and channel gating properties underlying their APs and EADs that are quantitatively similar to those reported for human cardiac myocytes. These hiPSC-derived cardiomyocytes have the added advantage that they can be used in high-throughput assays, and they have the potential to impact multiple areas of cardiovascular research and therapeutic applications.
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Project description:Drug-induced cardiotoxicity and hepatotoxicity are major causes of drug attrition. To decrease late-stage drug attrition, pharmaceutical and biotechnology industries need to establish biologically relevant models that use phenotypic screening to detect drug-induced toxicity in vitro. In this study, we sought to rapidly detect patterns of cardiotoxicity using high-content image analysis with deep learning and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). We screened a library of 1280 bioactive compounds and identified those with potential cardiotoxic liabilities in iPSC-CMs using a single-parameter score based on deep learning. Compounds demonstrating cardiotoxicity in iPSC-CMs included DNA intercalators, ion channel blockers, epidermal growth factor receptor, cyclin-dependent kinase, and multi-kinase inhibitors. We also screened a diverse library of molecules with unknown targets and identified chemical frameworks that show cardiotoxic signal in iPSC-CMs. By using this screening approach during target discovery and lead optimization, we can de-risk early-stage drug discovery. We show that the broad applicability of combining deep learning with iPSC technology is an effective way to interrogate cellular phenotypes and identify drugs that may protect against diseased phenotypes and deleterious mutations.
2021-07-07 | GSE172181 | GEO
Project description:Human induced pluripotent stem (iPS) cells hold great promise for cardiovascular research and therapeutic applications, but the ability of human iPS cells to differentiate into functional cardiomyocytes has not yet been demonstrated. The aim of this study was to characterize the cardiac differentiation potential of human iPS cells generated using OCT4, SOX2, NANOG, and LIN28 transgenes compared to human embryonic stem (ES) cells. The iPS and ES cells were differentiated using the embryoid body (EB) method. The time course of developing contracting EBs was comparable for the iPS and ES cell lines, although the absolute percentages of contracting EBs differed. RT-PCR analyses of iPS and ES cell-derived cardiomyocytes demonstrated similar cardiac gene expression patterns. The pluripotency genes OCT4 and NANOG were downregulated with cardiac differentiation, but the downregulation was blunted in the iPS cell lines because of residual transgene expression. Proliferation of iPS and ES cell-derived cardiomyocytes based on 5-bromodeoxyuridine labeling was similar, and immunocytochemistry of isolated cardiomyocytes revealed indistinguishable sarcomeric organizations. Electrophysiology studies indicated that iPS cells have a capacity like ES cells for differentiation into nodal-, atrial-, and ventricular-like phenotypes based on action potential characteristics. Both iPS and ES cell-derived cardiomyocytes exhibited responsiveness to beta-adrenergic stimulation manifest by an increase in spontaneous rate and a decrease in action potential duration. We conclude that human iPS cells can differentiate into functional cardiomyocytes, and thus iPS cells are a viable option as an autologous cell source for cardiac repair and a powerful tool for cardiovascular research.
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