Open access peer-reviewed chapter

Modelling of Genetic Cardiac Diseases

Written By

Chandra Prajapati and Katriina Aalto-Setälä

Submitted: September 28th, 2018 Reviewed: February 5th, 2019 Published: April 16th, 2019

DOI: 10.5772/intechopen.84965

Chapter metrics overview

752 Chapter Downloads

View Full Metrics

Abstract

Cardiac disease modeling is crucial to improve our understanding of the mechanism of various cardiac diseases and to discover new therapeutic approaches. Several modeling methods such as animal and computer simulations have been used to elucidate the cardiac diseases’ mechanism and drug responses. However, each modeling technique has its own particular advantages and limitations. Human-based models would be particularly useful to investigate human cardiac diseases because humans and animals have differing cardiac physiologies and drug tolerability. In addition, the phenotype of cardiac diseases and response to therapeutic intervention differ not only between mutations but also among patients. Therefore, such diseases strongly demand the individualized/personalized strategies. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) offer the striking feature of retaining the same genetic information as donor, which guide us to investigate diseases and predict response to drug treatment individually. This feature of hiPSC-CMs is superior to the conventional in vitro modeling of cardiac diseases. Thus far, hiPSC-CMs have been successfully recapitulated many monogenic and also complex genetic cardiac diseases. hiPSC-CMs could be differentiated into different types of cardiomyocytes and non-cardiomyocyte cells, which empower us to understand cardiac chamber-specific arrhythmias such as atrial fibrillation and ventricular tachycardia.

Keywords

  • cardiac disease
  • modeling
  • hiPSC-CMs
  • drug

1. The importance of hiPSC-CMs

Cardiovascular diseases (CVDs) are the major causes of premature death and chronic disability worldwide [1]. Among CVD-related deaths, the occurrence of inherited lethal arrhythmias is the main reason for sudden cardiac death (SCD) in cardiac patients especially at young age [2]. Although many risk factors associated with SCD have been identified and understanding of pathogenesis of many cardiac diseases is progressing, the considerable number of cardiac patients still suffers SCD without warning, and we are still far from disease-specific treatment. Heterogeneous and multifactorial natures of genetic cardiac diseases are reasons for these complications. Furthermore, founder mutations causing cardiac disease have been reported in Finland [3], the Netherlands [4], and South Africa [5]. Not only disease phenotypes vary among different mutations, but also these vary among individuals carrying the same mutation. For example, long QT syndrome (LQTS) patients demonstrate a wide range of clinical phenotypes even among family members with the identical mutation [6]. Despite carrying the same gene variant resulting in cardiac disease, patients often demonstrate the wide spectrum of clinical outcomes ranging from the absence of distinct electrocardiogram (ECG) abnormalities and being lifelong asymptomatic to clear abnormalities in ECG (e.g., prolonged QT interval and arrhythmias) and premature SCD. In addition, SCD could also be the first manifestation of cardiac disease. These suggest that the type of genetic mutation cannot always be the sole factor that dictates the prognosis of disease and clinical phenotype in all individuals who carry it [7]. Thus, genetic cardiac diseases exhibit the incomplete penetrance and differ among genetic cardiac diseases. For example, Brugada syndrome (BrS) has a penetration range from 12.5 to 50%; mean penetrance of LQTS is ~40%, while overall penetrance of catecholaminergic polymorphic ventricular tachycardia (CPVT) is 78% [7]. Another convoluting factor that hinders the genotype-phenotype correlation is variable expressivity within one phenotype because some mutation carriers display all the phenotypic symptoms, whereas some only display part of mutation-specific phenotypes [8]. The clinical heterogeneity of genetic cardiac diseases suggests that ultimate disease severity (i.e., penetrance and expressivity) does not solely depend on one particular gene causing cardiac disease, but instead results from the combination of many modifying factors such as age, gender, and environmental and lifestyle factors, which either exacerbate or protect against disease [9]. In addition, patients carrying more than one disease-causing mutations (i.e., not polymorphisms) either in the same gene or different genes yield to more severe clinical disease including earlier onset of disease, early heart failure, and premature SCD [10]. Besides these, some of the cardiac diseases overlap their phenotypes with other cardiac diseases (Figure 1). For example, mutations in cardiac sodium (Na+) channel gene, SCN5A, are associated with type 3 long QT (LQT3), BrS, cardiac conduction diseases, and sinus node dysfunction [11]. These incomplete penetrance, variable expressivity, and phenotypic overlap impede the complete understanding of diseases’ mechanism as well as disease-specific treatment. Furthermore, the treatment therapies are mainly targeted for symptomatic patients to prevent and counteract the symptoms, but treatments in asymptomatic individuals are still of concern with variable opinions. Nevertheless, pharmacological therapies have been resulted in poor outcomes in the cardiac diseases [12]. So far, implantable cardioverter-defibrillator (ICD) is the only proven therapy for preventing detrimental consequences in cardiac patients with high risk of SCD [13]. However, ICD implantation is associated with its own complications and lower quality of life [14]. There are large groups of asymptomatic cardiac patients who do not have risk factors, which shift them into high-risk category as candidate for ICD implantation, but suffer SCD. Thus, the management for asymptomatic patients carrying pathogenic variant is the most challenging since SCD could be the first manifestation of disease [15, 16]. The clinical management of most cardiac diseases is suboptimal due to lack of comprehensive knowledge of mutations and possible mechanism involved. Thus, the mechanism of how mutation leads to modify the normal cardiac physiology and engender lethal arrhythmias should be deciphered so that the promising prevention and treatment could be established.

Figure 1.

Heterogeneity of genetic cardiac diseases. (A) Overlapping genes causing channelopathies [27]. Brugada syndrome (BrS), long QT syndrome (LQTS), short QT syndrome (SQTS), catecholaminergic polymorphic ventricular tachycardia (CPVT) (ref). (B) Overlapping genes causing cardiomyopathies [72]. Arrhythmogenic right ventricular cardiomyopathy (ARVC), dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RCM), left ventricular non-compaction cardiomyopathy (LVNC).

The prior cardiovascular research and drug screening have mostly been performed in animal models through knock-in/knock-out approaches. Although animal models have provided some fundamental information and led to many discoveries in genetic cardiac disease, physiological and pharmacological results cannot directly extrapolate from animals to humans because of some fundamental differences that exist between animal and human cardiac physiology [17]. For example, the resting heart rate of human is 75 bpm, while that of rat is 300 bpm, and the animal (mice and rats) can tolerate 6–400-fold higher concentration of some drugs compared to human [18]. The animal models become even worse when studying human cardiomyopathies due to mutations in contractile proteins, which are not highly expressed in mouse or rat. Therefore, it is more complicated to extrapolate physiological and pharmacological results from animal to human [17, 18]. Furthermore, most of cardiovascular drug screening and toxicology studies were performed in non-cardiac cell lines or animals, which do not accurately represent human CMs. Thus, considerable amount of cardiovascular drugs were withdrawn from market due to off-target effects [19]. Therefore, human tissues are required to study the human cardiac diseases and drug testing. However, the human sample exhibits some of the major challenges: there is limited supply of human cardiac biopsies, and it involves complex procedures and ethical issues. In addition, these cardiac biopsies are typically obtained from the end stage of cardiac diseases; hence it is not possible to understand the mechanism of cardiac diseases [20, 21]. These obstacles are mostly overcome by the groundbreaking discovery of reprogramming adult somatic cells into induced pluripotent stem cells (iPSCs) [22, 23] which can be differentiated into cardiomyocytes (CMs) (hiPSC-CMs) [24, 25, 26]. The main advantages of hiPSC-CMs are iPSCs can be generated at any period of a patient’s life, they have unlimited supply, and these retain the same genetic information as the donor, i.e., hiPSC-CMs are patient specific (Figure 2). These are superior features of hiPSC-CMs to the conventional in vitro modeling of cardiac diseases. In addition, hiPSC-CMs can be cultured for several months, which enable us to study acute and chronic effect of mutation and drugs on CMs. Thus, hiPSC-CMs not only provide the platform to investigate the mutation-specific mechanism but also assist to anticipate drug response on an individual basis and guide us to personalized medicine in future.

Figure 2.

hiPSC-CM-based modeling of human genetic cardiac diseases. Human-induced pluripotent stem cells (hiPSCs) can be differentiated into hiPSC-derived cardiomyocytes (hiPSC-CMs). There are at least three subtypes of hiPSC-CMs, namely, ventricular-like, atrial-like, and nodal-like hiPSC-CMs. hiPSC-CMs derived from cardiac patients carrying genetic mutation recapitulate calcium and electrical abnormalities (early afterdepolarization (EAD) and delayed afterdepolarization (DAD)). Newly emerging gene editing techniques were able to mitigate these abnormalities in hiPSC-CMs.

Advertisement

2. Channelopathy phenotypes in hiPSC-CMs

Channelopathy cardiac diseases are caused by mutations in cardiac ion channels located in the cellular membrane or organelles. Mutations in ion channels result in misbalance of fine-tuning ion exchange during excitation-contraction coupling (ECC), which could lead to cardiac arrhythmias and SCD in the worst case. The main cardiac channelopathies are CPVT, LQTS, BrS, and short QT syndromes (SQTS) [27]. These cardiac channelopathies have been extensively studied using hiPSC-CMs and described below.

2.1 Catecholaminergic polymorphic ventricular tachycardia (CPVT)

CPVT is an inherited cardiac disease with the prevalence of about 1:5000/10,000. This disease is characterized by premature ventricular contraction and/or polymorphic ventricular tachycardia (VT) induced by adrenergic stimulation in response to emotional stress or physical exercise in structurally normal heart. Over 150 mutations in ryanodine receptor type 2 (RYR2 gene) are responsible for ~ 55% of CPVT type 1 cases (CPVT1), and mutation in calsequestrin 2 (CASQ2 gene) CPVT accounts for 3–5% CPVT type 2 (CPVT2) cases [28, 29]. In addition, mutations in calmodulin (CALM1) genes and in triadin (TRDN) have been reported causing CPVT. RYR2, CASQ2, CALM1, and TRDN are involved in ECC, and mutation in any of these genes results in elevated intracellular Ca2+, which leads to abnormal Ca2+ handling and arrhythmias [28, 29]. In consistency with clinical phenotype, many hiPSC-CM model had demonstrated the exacerbation of electrophysiological and Ca2+ handling abnormalities upon adrenergic stimulation [26, 30, 31, 32]. Furthermore, Zhang and colleagues had modeled hiPSC-CMs harboring CPVT1-associated F2483I mutation in RYR2 gene and demonstrated that CPVT1 hiPSC-CMs had longer and wandering Ca2+ sparks and smaller sarcoplasmic reticulum Ca2+ content [32]. Later on, the same group corrected this mutation using clustered regularly interspaced short palindromic repeats/Cas9 (CRISPR/Cas9) gene editing technique and showed that this mutation is causative rather than associative to the disease [33]. hiPSC-CM model for CPVT has also been used in studying the efficacy of various drugs. Previously we had directly compared the clinical results from CPVT1 patients with dantrolene medication, and the clinical response of dantrolene was similar as in hiPSC-CMs from the same patients; dantrolene abolished or markedly reduced arrhythmias in patients and their hiPSC-CMs with certain mutation in RYR2, while it did not have any clinical effect with hiPSC-CMs or with other RYR2 mutations [31]. Furthermore, an antiarrhythmic drug, flecainide, used to treat CPVT1 patients [34] was able to reduce the Ca2+ irregularities under adrenergic stimulation in CPVT1 hiPSC-CMs [30, 35]. CPVT2 patients harboring homozygous CASQ2-G112 + 5X mutation in CASQ2 gene showed the rapid polymorphic VT under exercise stress test [36]. Adult rat ventricular myocytes were studied to understand the effect of CASQ2 mutation in ECC, demonstrating that mutated CMs exhibited spontaneous extrasystolic Ca2+ elevations and delayed afterdepolarization (DADs) upon adrenergic stimulation [36]. Later, hiPSC-CM model harboring CASQ2-G112 + 5X mutation emulated these phenotypic features of disease, and AAV9-based gene delivery effectively prevents the development of adrenergic-induced DADs and triggered arrhythmias in CPVT2 hiPSC-CMs [37].

2.2 LQT type 1 (LQT1)

LQT type 1 (LQT1) is caused by loss-of-function mutation in KCNQ1 gene encoding α subunit of potassium (K+) channel mediating slow delayed rectifier K+ current (IKs). LQT1 is responsible for 30–35% of all LQTS cases [38]. LQT1 is characterized by prolongation of QT interval in ECG, which could lead to SCD due to VT, typically torsades de pointes [39]. hiPSC-CMs derived from LQT1 patients faithfully recapitulated the clinical hallmark by showing prolonged action potential duration (APD) which is analogous to QT duration in ECG, and reduced IKs current densities are held responsible for abnormal repolarization [40, 41, 42]. ML277, an IKs activator, increased the IKs amplitude by enhancing the activation of IKs, thus resulting in shortening of APD in LQT1 hiPSC-CMs [40]. In addition, adrenergic stimulation in LQT1 hiPSC-CMs induced the early afterdepolarization (EAD) [42], which is similar to arrhythmias triggered in LQT1 patients by exercise or emotional stress [39]. Clinically, β-blockers were effective in minimizing the risk of cardiac events in LQT1 patients [43]. Similar antiarrhythmic effect of β-blockers has been observed in LQT1 hiPSC-CMs [42]. Furthermore, hypokalemia is the electrolyte disturbance caused by lower K+ level in blood serum, which aggravates the QT prolongation and facilitates the development of hypokalemia-induced torsades de pointes in LQT1 patients [39, 44]. We successfully developed and mimicked these disease phenotypes in LQT1 hiPSC-CMs carrying G589D or IVS7-2A > G mutation in KCNQ1 gene. Additionally, lowering the extracellular K+ concentration prolonged APDs and induced the formation of EADs in LQT1 hiPSC-CMs [45]. Both G589D- and IVS7-2A > G-specific LQT1 hiPSC-CMs displayed longer APD and higher Ca2+ abnormalities in baseline; G589D hiPSC-CMs demonstrated prolonged contraction, while IVS7-2A > G hiPSC-CMs showed impaired relaxation [46] observed in our video image-based software analysis [47].

2.3 LQT type 2 (LQT2)

LQT type 2 (LQT2) is an LQTS subtype, which is caused by loss-of-function mutations in KCNH2 gene also known as human ether-a-go-go-related gene (hERG) encoding K+ channel mediating rapid delayed rectifier K current (IKr). LQT2 is responsible for approximately 25–30% of all LQTS cases [38]. Similar to LQT1, LQT2 patients also exhibit the prolongation of QT interval and torsades de pointes. As in LQT1 hiPSC-CM model, LQT2 hiPSC-CMs also recapitulated clinical phenotypes by displaying longer APD resulted from reduced IKr current densities and enhanced EAD following the adrenergic stimulation [48, 49, 50]. Our early study of LQT2 hiPSC-CMs carrying R176W mutation in KCNH2 gene demonstrated the reduced IKr current densities, prolonged repolarization, and increased arrhythmogenicity although the donor is an asymptomatic carrier [50]. These results are in parallel with clinical findings that LQT2 patients usually display symptoms when heart rate is slow. In addition, this report illustrated that electrophysiological abnormalities can be detected in hiPSC-CMs, although iPSCs are derived from asymptomatic carriers of KCNH2 mutations. The application of IKr blockers (E4031 and sotalol) further prolonged the APD resulting in EADs, whereas Ca2+ channel blocker (nifedipine), IK,ATP channel opener (pinacidil and nicorandil), and IKr channel enhancer (PD-118057) reduced the APD and thus mitigated the formation of EAD in LQT2 hiPSC-CMs [48, 49]. Several novel pharmacological strategies including ICA-105574 (potent IKr activator) [51], chaperone modulator N-[N-(N-acetyl-L-leucyl)-L-leucyl]-L-norleucine (ALLN) [52], LUF7346 (hERG allosteric modulators) [53], as well as application of allele-specific RNA interference approach [54] have been attempts to rescue the LQT phenotype in LQT2 hiPSC-CMs. Correcting the mutation associated with LQT2 not only confirmed that mutation caused IKr reduction and APD prolongation but also suggested that trafficking defect as the pathological mechanism is responsible for the electrophysiological phenotype in LQT2 [51, 55].

2.4 LQT type 3 (LQT3)

LQT type 3 (LQT3) is caused by gain-of-function mutations in SCN5A encoding α subunit of cardiac Na+ channels [56]. The gain-of-function SCN5A mutation results in augmented late or persistent Na+ current (INaL), which leads to prolongation of QT interval in ECG and proarrhythmia. LQT3 is the third most common LQTS accounting for 5–10% of all LQTS cases [56]. LQT3 patients exhibit longer QT duration at slower heart rate, thus LQT3 patients are at higher risk for cardiac events during rest or sleep [57]. LQT3 patients harboring V1763 M mutation in SCN5A [58] R1644H mutation in SCN5A [59] or F1473C mutation in SCN5A and a polymorphism (K897 T) in KCNH2 [60] had prolonged QT interval, and in vitro models using hiPSC-CMs derived from all those LQT3 patients demonstrated prolonged APD resulting in the larger INa,L and altered biophysical properties of Na+ channels [58, 59, 60]. Mexiletine, a Na+ channel inhibitor commonly used in LQT3 therapy, lowered the INa,L and thereby rescued the APD prolongation phenotype [58, 59] and suppressed the occurrence of EAD [59] and also corrected the altered Na+ channel inactivation [60]. Incorporating the biophysics of Na+ channel and pharmacological analysis illustrated that the improper functioning of Na+ channel was responsible for LQT3 phenotypes rather than KCNH2 polymorphism [60]. In addition to LQT3, mutation in SCN5A gene can cause BrS, and mixed phenotypes are often seen, which is also known as the “overlap syndrome.” Loss in function of Na+ channel is often seen in BrS. Liang and co-workers had generated hiPSCs from two BrS patients, one with double missense mutation (R620H and R811H) in SCN5A gene (BrS(p1)) and another with one-base pair deletion mutation in the SCN5A gene (BrS(p2)), and showed that BrS hiPSC-CMs derived from both patients had reduced Na+ current and increased triggered activity and abnormal Ca2+ handling [61]. These phenotypes were alleviated by correcting the mutation by CRISPR/Cas9 in hiPSCs derived from BrS (p2) [61]. Importantly, only BrS hiPSC-CMs harboring BrS-associated SCN5A-1795insD mutation displayed reduced Na+ current and upstroke velocity, but not with three sets of hiPSC-CMs derived from BrS patients who tested negative for mutations in the known BrS-associated genes suggesting the Na+ channel dysfunction may not be prerequisite for BrS [62]. In another study, Na+ current and upstroke velocity were reduced, but not the voltage-dependent inactivation in BrS hiPSC-CMs carrying the mutations R1638X and W156X [63].

2.5 LQT type 7 (LQT7) or Andersen-Tawil syndrome (ATS)

LQT type 7 (LQT7) or Andersen-Tawil syndrome (ATS) is a rare inherited cardiac disease associated with mutation in KCNJ2 gene (ATS type 1) encoding inward rectifying K+ channel (Kir2.1) and accounts for ~70% of all ATS cases. However, the genetic cause of the remaining 30% of ATS (ATS type 2) remains unknown. In ATS patients, QT interval prolongation is not common, but prominent U wave and QU interval in ECG could be hallmarks of ATS, and they experienced cardiac arrhythmias including non-sustained VT and torsade de pointes [64]. Kuroda and co-workers generated hiPSCs from ATS patients carrying R218W, R67W, and R218Q mutations in KCNJ2 gene and showed strong arrhythmic events and higher incidence of irregular Ca2+ handling in ATS hiPSC-CMs, but flecainide and KB-R7943 (a reverse-mode Na+/Ca2+ exchanger inhibitor) were able to suppress those events [65].

2.6 LQT type 8 (LQT8) or Timothy syndrome (TS)

2.6 LQT type 8 (LQT8) or Timothy syndrome (TS) is a very rare genetic cardiac disease which results from mutation in CACNA1C gene encoding Ca2+ channel (CaV1.2). LQT8 is the most severe type of LQTS, which is characterized by markedly prolonged QT interval, severe ventricular arrhythmia, and multiorgan dysfunction [66]. hiPSC-CMs derived from TS patients recapitulated the disease phenotypes, but roscovitine rescued those abnormalities such as altered Ca2+ channel inactivation, prolonged APD, higher incidences of arrhythmias, and abnormal Ca2+ handling [67].

2.7 Short QT (SQT)

SQT is a rare inherited cardiac disease characterized by QT internal shortening, which is in contrast to QT prolongation observed in LQTS. SQT is associated with mutations in genes associated with K+ channel or Ca2+ channels [68]. The prevalence of SQT is between 0.02–0.1% and 0.05% in adults and children, respectively [69]. Recently El-Battrawy and co-workers had generated hiPSCs from SQT type 1 patients carrying a mutation (N588K) in KCNH2, and hiPSC-CMs mimicked the clinical phenotype of SQT by showing a shortened APD as a result of increased IKr current densities [70]. In addition, SQT hiPSC-CMs exhibited abnormal Ca2+ transients and rhythmic activities, which are enhanced by carbachol, but quinidine alleviated those carbachol-induced arrhythmias and prolonged the APD [70].

Advertisement

3. Cardiomyopathy phenotypes in hiPSC-CMs

Cardiomyopathies are diseases of cardiac muscle and associated with structural and/or functional abnormalities. The most common genetic cardiomyopathies are hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D). These genetic cardiomyopathies have been also extensively studied using hiPSC-CMs [71, 72].

3.1 Hypertrophic cardiomyopathy (HCM)

HCM is one of the most common genetic cardiac diseases with an estimate prevalence of 1 in 500. HCM is characterized by unexplained symmetrical or asymmetrical left ventricular hypertrophy. Mutations in sarcomeric proteins account for ~60% of all HCM cases including mutation in β-myosin heavy chain (MYH7), cardiac myosin-binding protein C (MYBPC3), cardiac troponin I (cTnI), cardiac troponin T (cTnT), and tropomyosin (TPM1) [73]. Hypertrophy of myocytes and disarray of sarcomere are the histological hallmarks of HCM seen in cardiac biopsies from HCM patients [74], and these histological phenotypes are also observed in hiPSC-CM model of HCM [25, 75, 76, 77]. In addition, HCM hiPSC-CMs also demonstrated other hallmarks of HCM such as nuclear translocation of nuclear factor of activated T cells (NFAT) [75, 76, 77], elevation of β-myosin/α-myosin ratio, and calcineurin activation [75]. Furthermore, isolated CMs from HCM patients displayed the prolonged APDs, increased Ca2+ current densities, reduced transient outward K+ current densities, abnormal Ca2+ handling, and increased frequency of arrhythmias [21]. These electrophysiological and Ca2+ transient irregularity phenotypes have been faithfully recapitulated in HCM hiPSC-CMs [25, 75, 76, 78]. When HCM tissues carrying a mutation in MYBPC3 gene were compared with donor heart sample, no specific truncated MyBP-C peptides were detected, but the overall level of MyBP-C in myofibrils was significantly reduced [79]. Similar haploinsufficiency results were also shown in HCM hiPSC-CMs with mutation in MYBPC3 gene [25, 80], and gene replacement in HCM hiPSC-CMs partially improves the haploinsufficiency and reduces cellular hypertrophy [80]. Similar to higher myofilament Ca2+ sensitivity observed in isolated cardiac biopsies from HCM with E99K mutation in cardiac actin [81], in vitro model of HCM hiPSC-CMs carrying E99K mutation in cardiac actin demonstrated significantly stronger contraction and increased arrhythmogenic events [82] Furthermore, a study in HCM mice harboring I79N mutation in cTnT resulted in increased cardiac contractility, altered Ca2+ transients, and remodeling of action potential [83]. These phenotypes were faithfully recapitulated by HCM hiPSC-CMs carrying the same I79N mutation in cTnT [84]. These hypercontractility and increased arrhythmogenicity phenotypes were reversed in HCM hiPSC-CMs when the E99K mutation in cardiac actin [82] and I79N mutation in cTnT [84] were corrected using CRISPR/Cas9 gene editing technique. Recently, we have shown that HCM hiPSC-CMs carrying TPM1-Asp175Asn mutation exhibited VT type of arrhythmias [78], and this observation is in line with earlier clinical observation of HCM patients with TPM1-Asp175Asn mutation being at increased risk of fatal arrhythmias [85]. Currently, there is no specific pharmacological therapy for HCM patients, and drugs are prescribed mainly based on symptoms and personal history. However, drug therapy has also resulted in poor outcomes in HCM patients [12]. We reported the similar poor antiarrhythmic efficiency of β-blocker in preventing lethal arrhythmias in HCM hiPSC-CMs [78]. In another HCM report, several environmental factors were investigated with hiPSC-CMs to study their effect on disease progression [77]. They found that endothelin (ET)-1 was able to induce HCM phenotypes such as cellular hypertrophy and myofibrillar disarray in hiPSC-CMs, which are inhibited by ET receptor type A blocker [77]. HCM patients exhibited defects in mitochondrial functions and ultrastructure and abnormal energy metabolism [74]. These structural and functional phenotypes were recapitulated in hiPSC-CMs carrying m.2336 T > C mutation in mitochondrial genome causing HCM [86]. They reported that HCM hiPSC-CMs expressed reduced levels of mitochondrial proteins, ATP/ADP ratio, and mitochondrial membrane potential [86].

3.2 Dilated cardiomyopathy (DCM)

DCM is a myocardial disease characterized by ventricular chamber enlargement and systolic dysfunction and progressive heart failure without significant change in ventricular wall thickness. Mutations in >30 genes encoding proteins of cytoskeleton, sarcomere, and nuclear lamina are found in 30–35% of DCM patients [87]. DCM patients with mutations in RBM20, encoding RNA binding motif protein 20 (RBM20), have an early onset of disease phenotype [88]. Isolated CMs from DCM patients carrying mutation in RBM20 displayed elongated and thinner sarcomere structure [88], and such disorganized sarcomeric structure phenotypes were recapitulated in DCM hiPSC-CMs carrying mutation in RBM20 [89, 90]. RBM20 is the main regulator of the heart-specific titin splicing, and N2BA isoform is predominantly expressed in CMs from DCM patient carrying mutation in the RBM20 gene [91]. In vitro model of RBM20 hiPSC-CMs successfully mirrored the altered titin isoform expression (titin isoform switch) [89, 90]. Furthermore, RBM20 hiPSC-CMs showed delayed Ca2+ extrusion and reuptake and more Ca2+ being released during each ECC, which resulted into deficient muscle contraction, the hallmark of cardiac dysfunction of DCM patients [89, 90]. In addition, a three-dimensional engineered heart muscle generated from RBM20 hiPSC-CMs showed an impaired force of contraction, and passive stress was decreased in response to stepwise increase in strain, suggesting higher viscoelasticity caused by mutation in RBM20 [89]. Besides HCM, mutation in cTnT also caused DCM and resulted in shifts in Ca2+ sensitivity and force of contraction [92]. Sun and co-workers generated iPSCs from DCM patients carrying R173W mutation in cTnT and reported that DCM hiPSC-CMs exhibited altered Ca2+ handling, decreased contractility, and abnormal sarcomeric α–actinin distribution [93]. DCM patients with lamin A/C (LMNA) mutations show a highly variable phenotype. Cardiac biopsies from DCM patients harboring LMNA mutations exhibit reduced LMNA in nuclei with nuclear membrane damage such as focal disruption and nuclear pore clustering [94]. Nonsense mutation (R225X) in exon 4 of the LMNA gene causing DCM was associated with accelerated nuclear senescence and apoptosis of DCM hiPSC-CMs under electrical stimulation [95]. In another in vitro modeling of DCM, harboring A285V mutation in desmin (DES) using hiPSC-CMs displayed the pathogenic phenotypes of DCM such as diffuse abnormal DES aggregation, poor co-localization of DES with cTnT, and Z-disk streaming with accumulation of granulofilamentous materials or pleomorphic dense structures adjacent to the Z-disk or between the myofibrils [96]. DCM patients harboring R14del mutation in phospholamban (PLN) result in ventricular dilation, contractile dysfunction, and episodic ventricular arrhythmias [97]. Similarly, hiPSC-CMs carrying R14del mutation in PLN induced the Ca2+ handling abnormalities, irregular electrical activity, and abnormal intracellular distribution of PLN in DCM hiPSC-CMs [98]. These PLN R14del-associated disease phenotypes were mitigated upon correction of PLN R14del mutation by transcription activator-like effector nuclease (TALENs) gene editing technique [98]. Furthermore, genetic correction of PLN R14del mutation by TALENs improved the force development and restored the contractile function in three-dimensional human engineered cardiac tissue derived from R14del-iPSCs [99].

3.3 Arrhythmogenic right ventricular cardiomyopathy (ARVC)

ARVC is rare genetic cardiac disease with the prevalence ranging from 1:000 to 1:5000 worldwide. The histopathological hallmark of ARVC is the substitution of the cardiac myocytes with fibro-fatty deposits, particularly within the free wall of the right ventricle. The consequent results from the disruption of normal myocardial architecture can lead to right ventricular dysfunction, life-threatening arrhythmias, and SCD [100]. ARVC is caused by mutations in genes encoding desmosomal proteins such as plakoglobin (JUP), desmoplakin (DSP), plakophilin-2 (PKP2), desmoglein-2 (DSG2), and desmocollin-2 (DSC2) [100]. Similar to immunohistological results from the biopsy sample from ARVC patients [101], ARVC hiPSC-CMs harboring a plakophilin 2 (PKP2) gene mutation mimicked the reduced PKP2 immunosignal [102, 103]. In addition, clusters of lipid droplets accumulating within the cytoplasm were identified in ARVC-hiPSC-CMs associated with structural distortion of desmosomes [103]. Another study showed that induction of adult-like metabolic energetics from an embryonic/glycolytic state and abnormal peroxisome proliferator-activated receptor gamma (PPARγ) activation underlie the pathogenesis of ARVC [104]. It has been observed that male ARVC patients develop earlier and more severe phenotype than female ARVC patients [105]. To understand whether sex hormones in serum may contribute to the major arrhythmic cardiovascular events in ARVC, Akdis and co-workers combined a clinical study and in vitro hiPSC-CM model and showed that increased levels of testosterone accelerate ARVC pathologies, while premenopausal female estradiol levels slow down exaggerated apoptosis and lipid accumulation in ARVC hiPSC-CMs [106].

Advertisement

4. Limitations and future prospective

The reprogramming of somatic cells into pluripotent stems cells and subsequent differentiation into specific cell types is a newly emerging technique and is certainly not free from limitation.

One of the most questionable issues of hiPSC-CMs is their maturity. Despite expressing relevant ion channels [107] and structural genes [25, 26, 75, 76, 89, 108], hiPSC-CMs lack t-tubules and exhibit lower expression of Kir2.1 and weaker contractility; thus they do not fully resemble adult CMs. In order to improve the maturity of hiPSC-CMs and consequently upgrade the functionality of hiPSC-CMs, various techniques have been investigated in different groups. Three-dimensional construction of engineered heart tissue is a rapidly growing technique for structural and functional maturations of hiPSC-CMs [109], which resulted in higher Na+ current density and upstroke velocity [110], and enhances the metabolic maturation [111] comparable to adult CMs. Furthermore, Shadrin and co-workers introduced the “Cardiopatch” platform for three-dimensional culture and maturation of hiPSC-CMs; this platform produces robust electromechanical coupling, consistent H-zone and I bands, and evidence of t-tubules and M-bands [112].

Another issue of hiPSC-CMs is the purity of differentiated CMs. The CMs differentiated from hiPSCs yield in heterogeneous population of CMs. There are at least three subtypes of CMs such as ventricular, atrial, and nodal CMs; among them the majority (~70%) of CMs are ventricular-like, and only a minority of CMs are atrial-like (~20%) and nodal-like (~10%) [40, 58, 93, 107]. Although many molecular and functional characteristics are shared among these CMs subtypes, they also exhibit their own unique features. For example, ventricular CMs have prominent plateau phase (phase 2) in action potential profile, atrial CMs exclusively exhibit IKur channels, and nodal CMs lack strong upstroke velocity [113]. Most of the published methods of differentiation protocol yield in a lower amount of atrial-like and nodal-like CMs [40, 58, 93, 107], but sufficient numbers of subtype-specific CMs are needed to understand the subtype-related disease mechanism and development of specific therapeutic approaches. Atrial fibrillation (AF) is one of the most common cardiac arrhythmias; however, current antiarrhythmic drugs for treatment of AF are not atrial-specific and could cause unacceptable ventricular events [114]. Thus, sufficient supply of atrial CMs is crucial for investigating the AF cellular mechanism. hiPSCs have been differentiated into high-purity atrial-specific CMs by using retinoic acid signaling at the mesoderm stage of development [115]. These patient-specific atrial CMs allow us to investigate in detail mechanisms of AF and to develop atrial-specific therapeutic drugs. Furthermore, sinoatrial node (SAN) dysfunction can manifest bradycardia and asystolic pauses, but its pathophysiology is not completely understood [116]. SAN pacemaker cells from hiPSCs would facilitate the study of the disease mechanism and provide a cell source for developing a biological pacemaker. Protze and co-workers had reported the transgene-independent method for the generation of pacemaker cells (nodal-like CMs) from human pluripotent stem cells by stage-specific manipulation of developmental signaling pathways [117]. Besides CMs, the heart also consists of many other cell types such as fibroblast, endothelial and vascular smooth muscle cells, and also extracellular matrix. Importantly, the origin of cardiac diseases may not always exclusively originate from CMs, but might involve non-CMs. Thus, incorporating the fibroblasts [118], endothelial cells [119], and vascular smooth muscle cells [120] into CMs from the same hiPSCs could offer new insight of disease mechanism.

The establishment of appropriate control is another challenge in disease modeling using hiPSC-CMs. It is generally argued/suggested that when comparing the results between control and mutated hiPSC-CMs, both should have the same genetic background. This objective is achieved in somehow by using healthy family members as control [58, 93]. However, only ~50% of genome is shared between siblings, and phenotypic difference could result from DNA variants in the rest of genome besides disease-associated mutation [121]. Mutated genes can be corrected with the help of newly growing gene editing technology such as TALENs [98] and CRISPR/Cas9 [33, 51, 84], thus establishing the so-called isogenic lines. This isogenic line would be the most appropriate control for comparison as it differs only in the presence and absence of mutation. Therefore, advance genome engineering will not only provide more reliable control lines but also guide us to understand how mutation modifies the normal functioning of cells. However, for diseased CMs without known mutation, healthy family members or otherwise controls are still the best.

Advertisement

5. Conclusion

While animal models fail to recapitulate human cardiac disease phenotype properly, hiPSC-CMs have been successful in recapitulating crucial phenotypes of many genetic cardiac diseases in terms of morphology, contractility, Ca2+ handling, ion channel biophysics, cell signaling, and metabolism. Most strikingly, hiPSC-CMs provide the patient-specific platform to study the disease mechanism and drug response individually, which the traditional disease modeling technique would never offer. In addition, cardiac subtype-specific arrhythmias and drug screening could be performed with the help of unlimited supply of hiPSC-CMs; thus chamber-specific treatment modalities could be identified. Certainly, by improving the current weaknesses of hiPSC-CMs and incorporating with new gene editing techniques, complex cardiac disease mechanism could be deciphered, and novel effective treatment therapies could be identified to improve the life of cardiac patients.

Advertisement

Acknowledgments

We would like to thank funders for our research group: Tekes–Finnish Funding Agency for Innovation, Academy of Finland, and Finnish Cardiovascular Research Foundation.

Advertisement

Conflict of interest

No conflict of interest.

Advertisement

Abbreviations

AFatrial fibrillation
ARVC/Darrhythmogenic right ventricular cardiomyopathy/dysplasia
APDaction potential duration
ATSAndersen-Tawil syndrome
BrSBrugada syndrome
Ca2+calcium ion
CPVTcatecholaminergic polymorphic ventricular tachycardia
CRISPRclustered regularly interspaced short palindromic repeats
cTnTcardiac troponin T
CVDscardiovascular diseases
DADsdelayed afterdepolarization
DCMdilated cardiomyopathy
DSC2desmocollin-2
DSG2desmoglein-2
DSPdesmoplakin
EADearly afterdepolarization
ECCexcitation-contraction coupling
ECGelectrocardiogram
ETendothelin
hiPSC-CMshuman-induced pluripotent stem cell-derived cardiomyocytes
ICDimplantable cardioverter-defibrillator
iPSCsinduced pluripotent stem cells
K+potassium ion
LMNAlamin A/C
LQTSlong QT syndromes
MYBPC3cardiac myosin-binding protein C
MYH7myosin heavy chain
Na+sodium ion
PKP2plakophilin-2
PLNphospholamban
SANsinoatrial node
SCDsudden cardiac death
SQTSshort QT syndromes
TALENstranscription activator-like effector nucleases
TSTimothy syndrome
VTventricular tachycardia

References

  1. 1. Roth GA, Johnson C, Abajobir A, Abd-Allah F, Abera SF, Abyu G, et al. Global, regional, and national burden of cardiovascular diseases for 10 causes, 1990 to 2015. Journal of the American College of Cardiology. 2017;70(1):1-25
  2. 2. Meyer L, Stubbs B, Fahrenbruch C, Maeda C, Harmon K, Eisenberg M, et al. Incidence, causes, and survival trends from cardiovascular-related sudden cardiac arrest in children and young adults 0 to 35 years of age: A 30-year review. Circulation. 2012;126(11):1363-1372
  3. 3. Jääskelainen P, Helio T, Aalto-Setala K, Kaartinen M, Ilveskoski E, Hamalainen L, et al. Two founder mutations in the alpha-tropomyosin and the cardiac myosin-binding protein C genes are common causes of hypertrophic cardiomyopathy in the Finnish population. Annals of Medicine. 2013;45(1):85-90
  4. 4. Christiaans I, Nannenberg EA, Dooijes D, Jongbloed RJE, Michels M, Postema PG, et al. Founder mutations in hypertrophic cardiomyopathy patients in the Netherlands. Netherlands heart journal: Monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation. 2010;18(5):248-254
  5. 5. Brink PA, Crotti L, Corfield V, Goosen A, Durrheim G, Hedley P, et al. Phenotypic variability and unusual clinical severity of congenital long-QT syndrome in a founder population. Circulation. 2005;112(17):2602-2610
  6. 6. Giudicessi JR, Ackerman MJ. Genotype- and phenotype-guided management of congenital long QT syndrome. Current Problems in Cardiology. 2013;38(10):417-455
  7. 7. Giudicessi JR, Ackerman MJ. Determinants of incomplete penetrance and variable expressivity in heritable cardiac arrhythmia syndromes. Translational Research. 2013;161:1-14
  8. 8. Shinozawa T, Nakamura K, Shoji M, Morita M, Kimura M, Furukawa H, et al. Recapitulation of clinical individual susceptibility to drug-induced QT prolongation in healthy subjects using iPSC-derived cardiomyocytes. Stem Cell Reports. 2017;8(2):226-234
  9. 9. Coll M, Pérez-Serra A, Mates J, del Olmo B, Puigmulé M, Fernandez-Falgueras A, et al. Incomplete penetrance and variable expressivity: Hallmarks in channelopathies associated with sudden cardiac death. Biology (Basel) [Internet]. 2017;7(1):3. Available from: http://www.mdpi.com/2079-7737/7/1/3
  10. 10. Kelly M, Semsarian C, Cirino AL, Ho CY, Ashley EA. Multiple mutations in genetic cardiovascular disease: A marker of disease severity? Circulation: Cardiovascular Genetics [Internet]. 2009;2(2):182-190. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20031583
  11. 11. Veltmann C, Barajas-Martinez H, Wolpert C, Borggrefe M, Schimpf R, Pfeiffer R, et al. Further insights in the most common SCN5A mutation causing overlapping phenotype of long QT syndrome, Brugada syndrome, and conduction defect. Journal of the American Heart Association. 2016;5(7)
  12. 12. Spoladore R, Maron MS, D’Amato R, Camici PG, Olivotto I. Pharmacological treatment options for hypertrophic cardiomyopathy: High time for evidence. European Heart Journal. 2012;33:1724-1733
  13. 13. McAnulty J, Halperin B, Kron J, Larsen G, Raitt M, Swenson R, et al. A comparison of antiarrhythmic-drug therapy with implantable defibrillators in patients resuscitated from near-fatal ventricular arrhythmias. New England Journal of Medicine. 1997;337(22):1576-1583
  14. 14. Olde Nordkamp LRA, Postema PG, Knops RE, Van Dijk N, Limpens J, Wilde AAM, et al. Implantable cardioverter-defibrillator harm in young patients with inherited arrhythmia syndromes: A systematic review and meta-analysis of inappropriate shocks and complications. Heart Rhythm. 2016;13(2):443-454
  15. 15. Suzuki H, Hoshina S, Ozawa J, Sato A, Minamino T, Aizawa Y, et al. Short QT syndrome in a boy diagnosed on screening for heart disease. Pediatrics International. 2014;56(5):774-776
  16. 16. Giustetto C, Schimpf R, Mazzanti A, Scrocco C, Maury P, Anttonen O, et al. Long-term follow-up of patients with short QT syndrome. Journal of the American College of Cardiology. 2011;58(6):587-595
  17. 17. Farraj AK, Hazari MS, Cascio WE. The utility of the small rodent electrocardiogram in toxicology. Toxicological Sciences. 2011;121:11-30
  18. 18. Jung G, Bernstein D. hiPSC modeling of inherited cardiomyopathies. Current Treatment Options in Cardiovascular Medicine [Internet]. 2014;16(7):320. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24838688%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4096486
  19. 19. Munos B. Lessons from 60 years of pharmaceutical innovation. Nature Reviews. Drug Discovery. 2009;8:959-968
  20. 20. Barajas-Martínez H, Hu D, Goodrow RJ, Joyce F, Antzelevitch C. Electrophysiologic characteristics and pharmacologic response of human cardiomyocytes isolated from a patient with hypertrophic cardiomyopathy. PACE—Pacing and Clinical Electrophysiology. 2013;36(12):1512-1515
  21. 21. Coppini R, Ferrantini C, Yao L, Fan P, Del Lungo M, Stillitano F, et al. Late sodium current inhibition reverses electromechanical dysfunction in human hypertrophic cardiomyopathy. Circulation. 2013;127(5):575-584
  22. 22. Takahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131(5):861-872
  23. 23. Yu J, Vodyanik MA, Smuga-Otto K, Antosiewicz-Bourget J, Frane JL, Tian S, et al. Induced pluripotent stem cell lines derived from human somatic cells. Science (80-). 2007;318(5858):1917-1920
  24. 24. Kujala K, Paavola J, Lahti A, Larsson K, Pekkanen-Mattila M, Viitasalo M, et al. Cell model of catecholaminergic polymorphic ventricular tachycardia reveals early and delayed afterdepolarizations. PLoS One. 2012;7(9):e44660
  25. 25. Ojala M, Prajapati C, Pölönen R-P, Rajala K, Pekkanen-Mattila M, Rasku J, et al. Mutation-specific phenotypes in hiPSC-derived cardiomyocytes carrying either myosin-binding protein C or α-tropomyosin mutation for hypertrophic cardiomyopathy. Stem Cells International. 2016. Article ID: 1684792
  26. 26. Novak A, Barad L, Lorber A, Gherghiceanu M, Reiter I, Eisen B, et al. Functional abnormalities in iPSC-derived cardiomyocytes generated from CPVT1 and CPVT2 patients carrying ryanodine or calsequestrin mutations. Journal of Cellular and Molecular Medicine. 2015;19(8):2006-2018
  27. 27. Campuzano O, Sarquella-Brugada G, Brugada R, Brugada J. Genetics of channelopathies associated with sudden cardiac death. Global Cardiology Science & Practice [Internet]. 2015;2015(3):39. Available from: http://www.qscience.com/doi/10.5339/gcsp.2015.39
  28. 28. Venetucci L, Denegri M, Napolitano C, Priori SG. Inherited calcium channelopathies in the pathophysiology of arrhythmias. Nature Reviews. Cardiology. 2012;9:561-575
  29. 29. Pérez-Riera AR, Barbosa-Barros R, de Rezende Barbosa MPC, Daminello-Raimundo R, de Lucca AA, de Abreu LC. Catecholaminergic polymorphic ventricular tachycardia, an update. Annals of Noninvasive Electrocardiology. 2018;23:e12512
  30. 30. Pölönen RP, Penttinen K, Swan H, Aalto-Setälä K. Antiarrhythmic effects of carvedilol and flecainide in cardiomyocytes derived from catecholaminergic polymorphic ventricular tachycardia patients. Stem Cells International [Internet]. 2018;2018:1-11. Available from: https://www.hindawi.com/journals/sci/2018/9109503/
  31. 31. Penttinen K, Swan H, Vanninen S, Paavola J, Lahtinen AM, Kontula K, et al. Antiarrhythmic effects of dantrolene in patients with catecholaminergic polymorphic ventricular tachycardia and replication of the responses using iPSC models. PLoS One. 2015;10(5):e0134746
  32. 32. Zhang XH, Haviland S, Wei H, Šarić T, Fatima A, Hescheler J, et al. Ca2+ signaling in human induced pluripotent stem cell-derived cardiomyocytes (iPS-CM) from normal and catecholaminergic polymorphic ventricular tachycardia (CPVT)-afflicted subjects. Cell Calcium. 2013;54(2):57-70
  33. 33. Wei H, Zhang XH, Clift C, Yamaguchi N, Morad M. CRISPR/Cas9 Gene editing of RyR2 in human stem cell-derived cardiomyocytes provides a novel approach in investigating dysfunctional Ca2+ signaling. Cell Calcium. 2018;73:104-111
  34. 34. Van Der Werf C, Kannankeril PJ, Sacher F, Krahn AD, Viskin S, Leenhardt A, et al. Flecainide therapy reduces exercise-induced ventricular arrhythmias in patients with catecholaminergic polymorphic ventricular tachycardia. Journal of the American College of Cardiology. 2011;57(22):2244-2254
  35. 35. Preininger MK, Jha R, Maxwell JT, Wu Q , Singh M, Wang B, et al. A human pluripotent stem cell model of catecholaminergic polymorphic ventricular tachycardia recapitulates patient-specific drug responses. Disease Models & Mechanisms [Internet]. 2016;9(9):927-939 Available from: http://dmm.biologists.org/lookup/doi/10.1242/dmm.026823
  36. 36. Di Barletta MR, Viatchenko-Karpinski S, Nori A, Memmi M, Terentyev D, Turcato F, et al. Clinical phenotype and functional characterization of CASQ2 mutations associated with catecholaminergic polymorphic ventricular tachycardia. Circulation. 2006;114(10):1012-1019
  37. 37. Lodola F, Morone D, Denegri M, Bongianino R, Nakahama H, Rutigliano L, et al. Adeno-associated virus-mediated CASQ2 delivery rescues phenotypic alterations in a patient-specific model of recessive catecholaminergic polymorphic ventricular tachycardia. Cell Death & Disease. 2016;7(10)
  38. 38. Giudicessi JR, Ackerman MJ. Potassium-channel mutations and cardiac arrhythmias—Diagnosis and therapy. Nature Reviews. Cardiology. 2012;9:319-332
  39. 39. Morita H, Wu J, Zipes DP. The QT syndromes: Long and short. The Lancet. 2008;372:750-763
  40. 40. Ma D, Wei H, Lu J, Huang D, Liu Z, Loh LJ, et al. Characterization of a novel KCNQ1 mutation for type 1 long QT syndrome and assessment of the therapeutic potential of a novel IKs activator using patient-specific induced pluripotent stem cell-derived cardiomyocytes. Stem Cell Research & Therapy. 2015;6(1):39
  41. 41. Sogo T, Morikawa K, Kurata Y, Li P, Ichinose T, Yuasa S, et al. Electrophysiological properties of iPS cell-derived cardiomyocytes from a patient with long QT syndrome type 1 harboring the novel mutation M437V of KCNQ1. Regenerative Therapy. 2016;4:9-17
  42. 42. Moretti A, Bellin M, Welling A, Jung CB, Lam JT, Bott-Flügel L, et al. Patient-specific induced pluripotent stem-cell models for long-QT syndrome. New England Journal of Medicine [Internet]. 2010;363(15):1397-1409. Available from: http://www.nejm.org/doi/abs/10.1056/NEJMoa0908679
  43. 43. Ahn J, Kim HJ, Choi J-I, Lee KN, Shim J, Ahn HS, et al. Effectiveness of beta-blockers depending on the genotype of congenital long-QT syndrome: A meta-analysis. PLoS One. 2017;12(10):e0185680
  44. 44. Kubota T, Shimizu W, Kamakura S, Horie M. Hypokalemia-induced long QT syndrome with an underlying novel missense mutation in S4-S5 linker of KCNQ1. Journal of Cardiovascular Electrophysiology. 2000;11(9):1048-1054
  45. 45. Kuusela J, Larsson K, Shah D, Prajapati C, Aalto-Setälä K. Low extracellular potassium prolongs repolarization and evokes early afterdepolarization in human induced pluripotent stem cell-derived cardiomyocytes. Biology Open [Internet]. 2017;6(6):777-784. Available from: http://bio.biologists.org/lookup/doi/10.1242/bio.024216
  46. 46. Kiviaho AL, Ahola A, Larsson K, Penttinen K, Swan H, Pekkanen-Mattila M, et al. Distinct electrophysiological and mechanical beating phenotypes of long QT syndrome type 1-specific cardiomyocytes carrying different mutations. IJC Heart and Vasculature. 2015;8:19-31
  47. 47. Ahola A, Kiviaho AL, Larsson K, Honkanen M, Aalto-Setälä K, Hyttinen J. Video image-based analysis of single human induced pluripotent stem cell derived cardiomyocyte beating dynamics using digital image correlation. Biomedical Engineering Online. 2014;13(1):39
  48. 48. Matsa E, Rajamohan D, Dick E, Young L, Mellor I, Staniforth A, et al. Drug evaluation in cardiomyocytes derived from human induced pluripotent stem cells carrying a long QT syndrome type 2 mutation. European Heart Journal. 2011;32(8):952-962
  49. 49. Itzhaki I, Maizels L, Huber I, Zwi-Dantsis L, Caspi O, Winterstern A, et al. Modelling the long QT syndrome with induced pluripotent stem cells. Nature. 2011;471(7337):225-230
  50. 50. Lahti AL, Kujala VJ, Chapman H, Koivisto A-P, Pekkanen-Mattila M, Kerkelä E, et al. Model for long QT syndrome type 2 using human iPS cells demonstrates arrhythmogenic characteristics in cell culture. Disease Models & Mechanisms [Internet]. 2012;5(2):220-230. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3291643&tool=pmcentrez&rendertype=abstract
  51. 51. Garg P, Oikonomopoulos A, Chen H, Li Y, Lam CK, Sallam K, et al. Genome editing of induced pluripotent stem cells to decipher cardiac channelopathy variant. Journal of the American College of Cardiology. 2018;72(1):62-75
  52. 52. Mehta A, Sequiera GL, Ramachandra CJA, Sudibyo Y, Chung Y, Sheng J, et al. Re-trafficking of hERG reverses long QT syndrome 2 phenotype in human iPS-derived cardiomyocytes. Cardiovascular Research. 2014;102(3):497-506
  53. 53. Sala L, Yu Z, Ward-Van Oostwaard D, Pd Van Veldhoven J, Moretti A, Laugwitz K-L, et al. A new hERG allosteric modulator rescues genetic and drug-induced long-QT syndrome phenotypes in cardiomyocytes from isogenic pairs of patient induced pluripotent stem cells. EMBO Molecular Medicine. 2016;8:1065-1081
  54. 54. Matsa E, Dixon JE, Medway C, Georgiou O, Patel MJ, Morgan K, et al. Allele-specific RNA interference rescues the long-QT syndrome phenotype in human-induced pluripotency stem cell cardiomyocytes. European Heart Journal. 2014;35(16):1078-1087
  55. 55. Bellin M, Casini S, Davis RP, D’Aniello C, Haas J, Ward-Van Oostwaard D, et al. Isogenic human pluripotent stem cell pairs reveal the role of a KCNH2 mutation in long-QT syndrome. The EMBO Journal. 2013;32(24):3161-3175
  56. 56. Wang Q , Shen J, Splawski I, Atkinson D, Li Z, Robinson JL, et al. SCN5A mutations associated with an inherited cardiac arrhythmia, long QT syndrome. Cell. 1995;80(5):805-811
  57. 57. Schwartz PJ, Priori SG, Spazzolini C, Moss AJ, Michael Vincent G, Napolitano C, et al. Genotype-phenotype correlation in the long-QT syndrome: Gene-specific triggers for life-threatening arrhythmias. Circulation. 2001;103(1):89-95
  58. 58. Ma D, Wei H, Zhao Y, Lu J, Li G, Sahib NBE, et al. Modeling type 3 long QT syndrome with cardiomyocytes derived from patient-specific induced pluripotent stem cells. International Journal of Cardiology. 2013;168(6):5277-5286
  59. 59. Malan D, Zhang M, Stallmeyer B, Müller J, Fleischmann BK, Schulze-Bahr E, et al. Human iPS cell model of type 3 long QT syndrome recapitulates drug-based phenotype correction. Basic Research in Cardiology. 2016;111(2):1-11
  60. 60. Terrenoire C, Wang K, Chan Tung KW, Chung WK, Pass RH, Lu JT, et al. Induced pluripotent stem cells used to reveal drug actions in a long QT syndrome family with complex genetics. The Journal of General Physiology [Internet]. 2013;141(1):61-72. Available from: http://www.jgp.org/lookup/doi/10.1085/jgp.201210899
  61. 61. Liang P, Sallam K, Wu H, Li Y, Itzhaki I, Garg P, et al. Patient-specific and genome-edited induced pluripotent stem cell–derived cardiomyocytes elucidate single-cell phenotype of Brugada syndrome. Journal of the American College of Cardiology. 2016;68(19):2086-2096
  62. 62. Veerman CC, Mengarelli I, Guan K, Stauske M, Barc J, Tan HL, et al. HiPSC-derived cardiomyocytes from Brugada syndrome patients without identified mutations do not exhibit clear cellular electrophysiological abnormalities. Scientific Reports. 2016;6:30967
  63. 63. Kosmidis G, Veerman CC, Casini S, Verkerk AO, Van De Pas S, Bellin M, et al. Readthrough-promoting drugs gentamicin and PTC124 Fail to Rescue Na v 1.5 function of human-induced pluripotent stem cell-derived cardiomyocytes carrying nonsense mutations in the sodium channel gene SCN5A. Circulation. Arrhythmia and Electrophysiology. 2016;9(11):e004227
  64. 64. Zhang L, Benson DW, Tristani-Firouzi M, Ptacek LJ, Tawil R, Schwartz PJ, et al. Electrocardiographic features in Andersen-Tawil syndrome patients with KCNJ2 mutations: Characteristic T-U-wave patterns predict the KCNJ2 genotype. Circulation. 2005;111(21):2720-2726
  65. 65. Kuroda Y, Yuasa S, Watanabe Y, Ito S, Egashira T, Seki T, et al. Flecainide ameliorates arrhythmogenicity through NCX flux in Andersen-Tawil syndrome-iPS cell-derived cardiomyocytes. Biochemistry and Biophysics Reports. 2017;9:245-256
  66. 66. Splawski I, Timothy KW, Sharpe LM, Decher N, Kumar P, Bloise R, et al. CaV1.2 calcium channel dysfunction causes a multisystem disorder including arrhythmia and autism. Cell. 2004;119(1):19-31
  67. 67. Yazawa M, Hsueh B, Jia X, Pasca AM, Bernstein JA, Hallmayer J, et al. Using iPS cells to investigate cardiac phenotypes in patients with Timothy syndrome. Nature [Internet]. 2011;471(7337):230-234. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3077925/
  68. 68. Pérez-Riera AR, Paixão-Almeida A, Barbosa-Barros R, Yanowitz FG, Baranchuk A, Dubner S, et al. Congenital short QT syndrome: Landmarks of the newest arrhythmogenic cardiac channelopathy. Cardiology Journal. 2013;20:464-471
  69. 69. Guerrier K, Kwiatkowski D, Czosek RJ, Spar DS, Anderson JB, Knilans TK. Short QT interval prevalence and clinical outcomes in a pediatric population. Circulation. Arrhythmia and Electrophysiology. 2015;8(6):1460-1464
  70. 70. El-Battrawy I, Lan H, Cyganek L, Zhao Z, Li X, Buljubasic F, et al. Modeling short QT syndrome using human-induced pluripotent stem cell-derived cardiomyocytes. Journal of the American Heart Association. 2018;7(7):e007394
  71. 71. Sisakian H. Cardiomyopathies: Evolution of pathogenesis concepts and potential for new therapies. World Journal of Cardiology [Internet]. 2014;6(6):478. Available from: http://www.wjgnet.com/1949-8462/full/v6/i6/478.htm
  72. 72. Van Tintelen JP, Pieper PG, Van Spaendonck-Zwarts KY, Van Den Berg MP. Pregnancy, cardiomyopathies, and genetics. Cardiovascular Research. 2014;101:571-578
  73. 73. Maron BJ. Hypertrophic cardiomyopathy. Circulation. 2002;106(19):2419-2421
  74. 74. Pisano A, Cerbelli B, Perli E, Pelullo M, Bargelli V, Preziuso C, et al. Impaired mitochondrial biogenesis is a common feature to myocardial hypertrophy and end-stage ischemic heart failure. Cardiovascular Pathology. 2016;25(2):103-112
  75. 75. Lan F, Lee AS, Liang P, Sanchez-Freire V, Nguyen PK, Wang L, et al. Abnormal calcium handling properties underlie familial hypertrophic cardiomyopathy pathology in patient-specific induced pluripotent stem cells. Cell Stem Cell. 2013;12(1):101-113
  76. 76. Han L, Li Y, Tchao J, Kaplan AD, Lin B, Li Y, et al. Study familial hypertrophic cardiomyopathy using patient-specific induced pluripotent stem cells. Cardiovascular Research. 2014;104(2):258-269
  77. 77. Tanaka A, Yuasa S, Mearini G, Egashira T, Seki T, Kodaira M, et al. Endothelin-1 induces myofibrillar disarray and contractile vector variability in hypertrophic cardiomyopathy-induced pluripotent stem cell-derived cardiomyocytes. Journal of the American Heart Association. 2014;3(6):e001263
  78. 78. Prajapati C, Ojala M, Aalto-Setälä K. Divergent effect of adrenaline in human induced pluripotent stem cell derived cardiomyocytes obtained from hypertrophic cardiomyopathy. Disease Models & Mechanisms [Internet]. 2018;11:dmm.032896. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29361520
  79. 79. Marston S, Copeland O, Jacques A, Livesey K, Tsang V, McKenna WJ, et al. Evidence from human myectomy samples that MYBPC3 mutations cause hypertrophic cardiomyopathy through haploinsufficiency. Circulation Research. 2009;105(3):219-222
  80. 80. Prondzynski M, Krämer E, Laufer SD, Shibamiya A, Pless O, Flenner F, et al. Evaluation of MYBPC3 trans-splicing and gene replacement as therapeutic options in human iPSC-derived cardiomyocytes. Molecular Therapy—Nucleic Acids. 2017;7:475-486
  81. 81. Song W, Dyer E, Stuckey DJ, Copeland O, Leung MC, Bayliss C, et al. Molecular mechanism of the E99K mutation in cardiac actin (ACTC gene) that causes apical hypertrophy in man and mouse. The Journal of Biological Chemistry. 2011;286(31):27582-27593
  82. 82. Smith JGW, Owen T, Bhagwan JR, Mosqueira D, Scott E, Mannhardt I, et al. Isogenic pairs of hiPSC-CMs with hypertrophic cardiomyopathy/LVNC-associated ACTC1 E99K mutation unveil differential functional deficits. Stem Cell Reports. 2018;11(5):1226-1243
  83. 83. Knollmann BC, Kirchhof P, Sirenko SG, Degen H, Greene AE, Schober T, et al. Familial hypertrophic cardiomyopathy-linked mutant troponin T causes stress-induced ventricular tachycardia and Ca2+-dependent action potential remodeling. Circulation Research. 2003;92(4):428-436
  84. 84. Wang L, Kim K, Parikh S, Cadar AG, Bersell KR, He H, et al. Hypertrophic cardiomyopathy-linked mutation in troponin T causes myofibrillar disarray and pro-arrhythmic action potential changes in human iPSC cardiomyocytes. Journal of Molecular and Cellular Cardiology. 2018;114:320-327
  85. 85. Hedman A, Hartikainen J, Vanninen E, Laitinen T, Jääskeläinen P, Laakso M, et al. Inducibility of life-threatening ventricular arrhythmias is related to maximum left ventricular thickness and clinical markers of sudden cardiac death in patients with hypertrophic cardiomyopathy attributable to the Asp175Asn mutation in the α-tropomyosin. Journal of Molecular and Cellular Cardiology. 2004;36(1):91-99
  86. 86. Li S, Pan H, Tan C, Sun Y, Song Y, Zhang X, et al. Mitochondrial dysfunctions contribute to hypertrophic cardiomyopathy in patient iPSC-derived cardiomyocytes with MT-RNR2 mutation. Stem Cell Reports. 2018;10(3):808-821
  87. 87. Hershberger RE, Siegfried JD. Update 2011: Clinical and genetic issues in familial dilated cardiomyopathy. Journal of the American College of Cardiology. 2011;57(16):1641-1649
  88. 88. Beraldi R, Li X, Fernandez AM, Reyes S, Secreto F, Terzic A, et al. Rbm20-deficient cardiogenesis reveals early disruption of RNA processing and sarcomere remodeling establishing a developmental etiology for dilated cardiomyopathy. Human Molecular Genetics. 2014;23(14):3779-3791
  89. 89. Streckfuss-Bömeke K, Tiburcy M, Fomin A, Luo X, Li W, Fischer C, et al. Severe DCM phenotype of patient harboring RBM20 mutation S635A can be modeled by patient-specific induced pluripotent stem cell-derived cardiomyocytes. Journal of Molecular and Cellular Cardiology. 2017;113:9-21
  90. 90. Wyles SP, Li X, Hrstka SC, Reyes S, Oommen S, Beraldi R, et al. Modeling structural and functional deficiencies of RBM20 familial dilated cardiomyopathy using human induced pluripotent stem cells. Human Molecular Genetics. 2016;25(2):254-265
  91. 91. Guo W, Schafer S, Greaser ML, Radke MH, Liss M, Govindarajan T, et al. RBM20, a gene for hereditary cardiomyopathy, regulates titin splicing. Nature Medicine. 2012;18(5):766-773
  92. 92. Hershberger RE, Pinto JR, Parks SB, Kushner JD, Li D, Ludwigsen S, et al. Clinical and functional characterization of TNNT2 mutations identified in patients with dilated cardiomyopathy. Circulation. Cardiovascular Genetics. 2009;2(4):306-313
  93. 93. Sun N, Yazawa M, Liu J, Han L, Sanchez-Freire V, Abilez OJ, et al. Patient-specific induced pluripotent stem cells as a model for familial dilated cardiomyopathy. Science Translational Medicine. 2012;4(130):130ra47
  94. 94. Song K, Dubé MP, Lim J, Hwang I, Lee I, Kim J-J. Lamin A/C mutations associated with familial and sporadic cases of dilated cardiomyopathy in Koreans. Experimental & Molecular Medicine [Internet]. 2007;39(1):114-120. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17334235
  95. 95. Siu CW, Lee YK, Ho JCY, Lai WH, Chan YC, Ng KM, et al. Modeling of lamin A/C mutation premature cardiac aging using patient-specific induced pluripotent stem cells. Aging. 2012;4(11):803-822
  96. 96. Tse HF, Ho JCY, Choi SW, Lee YK, Butler AW, Ng KM, et al. Patient-specific induced-pluripotent stem cells-derived cardiomyocytes recapitulate the pathogenic phenotypes of dilated cardiomyopathy due to a novel DES mutation identified by whole exome sequencing. Human Molecular Genetics. 2013;22(7):1395-1403
  97. 97. Van Der Zwaag PA, Van Rijsingen IAW, Asimaki A, Jongbloed JDH, Van Veldhuisen DJ, Wiesfeld ACP, et al. Phospholamban R14del mutation in patients diagnosed with dilated cardiomyopathy or arrhythmogenic right ventricular cardiomyopathy: Evidence supporting the concept of arrhythmogenic cardiomyopathy. European Journal of Heart Failure. 2012;14(11):1199-1207
  98. 98. Karakikes I, Stillitano F, Nonnenmacher M, Tzimas C, Sanoudou D, Termglinchan V, et al. Correction of human phospholamban R14del mutation associated with cardiomyopathy using targeted nucleases and combination therapy. Nature Communications. 2015;6:6955
  99. 99. Stillitano F, Turnbull IC, Karakikes I, Nonnenmacher M, Backeris P, Hulot JS, et al. Genomic correction of familial cardiomyopathy in human engineered cardiac tissues. European Heart Journal. 2016;37(43):3282-3284
  100. 100. Sommariva E, Stadiotti I, Perrucci GL, Tondo C, Pompilio G. Cell models of arrhythmogenic cardiomyopathy: Advances and opportunities. Disease Models & Mechanisms [Internet]. 2017;10(7):823-835. Available from: http://dmm.biologists.org/lookup/doi/10.1242/dmm.029363
  101. 101. Asimaki A, Tandri H, Huang H, Halushka MK, Gautam S, Basso C, et al. A new diagnostic test for arrhythmogenic right ventricular cardiomyopathy. New England Journal of Medicine [Internet]. 2009;360(11):1075-1084. Available from: http://www.nejm.org/doi/abs/10.1056/NEJMoa0808138
  102. 102. Ma D, Wei H, Lu J, Ho S, Zhang G, Sun X, et al. Generation of patient-specific induced pluripotent stem cell-derived cardiomyocytes as a cellular model of arrhythmogenic right ventricular cardiomyopathy. European Heart Journal. 2013;34(15):1122-1133
  103. 103. Caspi O, Huber I, Gepstein A, Arbel G, Maizels L, Boulos M, et al. Modeling of arrhythmogenic right ventricular cardiomyopathy with human induced pluripotent stem cells. Circulation. Cardiovascular Genetics. 2013;6(6):557-568
  104. 104. Kim C, Wong J, Wen J, Wang S, Wang C, Spiering S, et al. Studying arrhythmogenic right ventricular dysplasia with patient-specific iPSCs. Nature. 2013;494(7435):105-110
  105. 105. Bauce B, Frigo G, Marcus FI, Basso C, Rampazzo A, Maddalena F, et al. Comparison of clinical features of arrhythmogenic right ventricular cardiomyopathy in men versus women. The American Journal of Cardiology. 2008;102(9):1252-1257
  106. 106. Akdis D, Saguner AM, Shah K, Wei C, Medeiros-Domingo A, Von Eckardstein A, et al. Sex hormones affect outcome in arrhythmogenic right ventricular cardiomyopathy/dysplasia: From a stem cell derived cardiomyocyte-based model to clinical biomarkers of disease outcome. European Heart Journal. 2017;38(19):1498-1508
  107. 107. Prajapati C, Pölönen R-P, Aalto-Setälä K. Simultaneous recordings of action potentials and calcium transients from human induced pluripotent stem cell derived cardiomyocytes. Biology Open [Internet]. 2018;7(7):bio035030. Available from: http://bio.biologists.org/content/early/2018/06/20/bio.035030.abstract
  108. 108. Jung CB, Moretti A, Mederos y Schnitzler M, Iop L, Storch U, Bellin M, et al. Dantrolene rescues arrhythmogenic RYR2 defect in a patient-specific stem cell model of catecholaminergic polymorphic ventricular tachycardia. EMBO Molecular Medicine. 2012;4(3):180-191
  109. 109. Tiburcy M, Hudson JE, Balfanz P, Schlick S, Meyer T, Liao MLC, et al. Defined engineered human myocardium with advanced maturation for applications in heart failure modeling and repair. Circulation. 2017;135(19):1832-1847
  110. 110. Lemoine MD, Mannhardt I, Breckwoldt K, Prondzynski M, Flenner F, Ulmer B, et al. Human iPSC-derived cardiomyocytes cultured in 3D engineered heart tissue show physiological upstroke velocity and sodium current density. Scientific Reports. 2017;7(1)
  111. 111. Correia C, Koshkin A, Duarte P, Hu D, Carido M, Sebastião MJ, et al. 3D aggregate culture improves metabolic maturation of human pluripotent stem cell derived cardiomyocytes. Biotechnology and Bioengineering [Internet]. 2017;115(3):360-644. Available from: http://doi.wiley.com/10.1002/bit.26504
  112. 112. Shadrin IY, Allen BW, Qian Y, Jackman CP, Carlson AL, Juhas ME, et al. Cardiopatch platform enables maturation and scale-up of human pluripotent stem cell-derived engineered heart tissues. Nature Communications. 2017;8(1):1825
  113. 113. Amin AS, Tan HL, Wilde AAM. Cardiac ion channels in health and disease. Heart Rhythm [Internet]. 2010;7(1):117-126. Available from: http://www.sciencedirect.com/science/article/pii/S1547527109008443
  114. 114. Dobrev D, Nattel S. New antiarrhythmic drugs for treatment of atrial fibrillation. The Lancet. 2010;375:1212-1223
  115. 115. Lee JH, Protze SI, Laksman Z, Backx PH, Keller GM. Human pluripotent stem cell-derived atrial and ventricular cardiomyocytes develop from distinct mesoderm populations. Cell Stem Cell. 2017;21(2):179-194.e4
  116. 116. Choudhury M, Boyett MR, Morris GM. Biology of the sinus node and its disease. Arrhythmia & Electrophysiology Review [Internet]. 2015;4(1):28. Available from: http://www.radcliffecardiology.com/articles/biology-sinus-node-and-its-disease
  117. 117. Protze SI, Liu J, Nussinovitch U, Ohana L, Backx PH, Gepstein L, et al. Sinoatrial node cardiomyocytes derived from human pluripotent cells function as a biological pacemaker. Nature Biotechnology. 2017;35(1):56-68
  118. 118. Shamis Y, Hewitt KJ, Bear SE, Addy AH, Qari H, Margvelashvilli M, et al. IPSC-derived fibroblasts demonstrate augmented production and assembly of extracellular matrix proteins. In Vitro Cellular & Developmental Biology—Animal. 2012;48(2):112-122
  119. 119. Orlova VV, Van Den Hil FE, Petrus-Reurer S, Drabsch Y, Ten Dijke P, Mummery CL. Generation, expansion and functional analysis of endothelial cells and pericytes derived from human pluripotent stem cells. Nature Protocols. 2014;9(6):1514-1531
  120. 120. Granata A, Serrano F, Bernard WG, McNamara M, Low L, Sastry P, et al. An iPSC-derived vascular model of Marfan syndrome identifies key mediators of smooth muscle cell death. Nature Genetics. 2017;49(1):97-109
  121. 121. Musunuru K. Genome editing of human pluripotent stem cells to generate human cellular disease models. Disease Models & Mechanisms [Internet]. 2013;6(4):896-904. Available from: http://dmm.biologists.org/cgi/doi/10.1242/dmm.012054

Written By

Chandra Prajapati and Katriina Aalto-Setälä

Submitted: September 28th, 2018 Reviewed: February 5th, 2019 Published: April 16th, 2019