Physiological genomics identifies genetic modifiers of long QT syndrome type 2 severity

Chai, Sam; Wan, Xiaoping; Ramirez‐Navarro, Angelina; Tesar, Paul J.; Kaufman, Elizabeth S.; Ficker, Eckhard; George, Alfred L.; Deschênes, Isabelle

doi:10.1172/jci94996

Cited by 59 publications

(53 citation statements)

References 58 publications

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“…Clinically, genetic modifiers have been seen to modify the severity of long QT syndrome type 2. Patients with the same hERG mutations have differential severity in QT prolongation, depending on the presence of other mutations that coregulate cellular repolarization (Chai et al 2018). The present study provides a framework that can be expanded to elucidate these types of feedback and coregulation mechanisms in iPSC-CMs, which directly relate to mechanisms of adult human cardiomyocyte behaviour.…”

Section: Discussionmentioning

confidence: 85%

A computational model of induced pluripotent stem‐cell derived cardiomyocytes incorporating experimental variability from multiple data sources

Kernik

Morotti

et al. 2019

The Journal of Physiology

105

128

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Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) capture patient-specific genotype-phenotype relationships, as well as cell-to-cell variability of cardiac electrical activity r Computational modelling and simulation provide a high throughput approach to reconcile multiple datasets describing physiological variability, and also identify vulnerable parameter regimes r We have developed a whole-cell model of iPSC-CMs, composed of single exponential voltage-dependent gating variable rate constants, parameterized to fit experimental iPSC-CM outputs r We have utilized experimental data across multiple laboratories to model experimental variability and investigate subcellular phenotypic mechanisms in iPSC-CMs r This framework links molecular mechanisms to cellular-level outputs by revealing unique subsets of model parameters linked to known iPSC-CM phenotypes Abstract There is a profound need to develop a strategy for predicting patient-to-patient vulnerability in the emergence of cardiac arrhythmia. A promising in vitro method to address patient-specific proclivity to cardiac disease utilizes induced pluripotent stem cell-derived Divya Kernik is currently a PhD candidate in Biomedical Engineering at the University of California, Davis. She obtained a BS in Biomedical Engineering from Johns Hopkins University. The focus of her PhD work has been the development of computational methods that help to understand human-derived cardiac cells, as reported in the present study. In the future, she aims to continue to use computational modelling to address questions in cardiac physiology and pharmacology, with the underlying goal of incorporating human diversity throughout these efforts.

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Section: Discussionmentioning

confidence: 85%

A computational model of induced pluripotent stem‐cell derived cardiomyocytes incorporating experimental variability from multiple data sources

Kernik

Morotti

et al. 2019

The Journal of Physiology

105

128

View full text Add to dashboard Cite

show abstract

“…Unbiased approaches using combinations of genomic and physiological investigations have also emerged recently as successful strategies. 9 Table 1 summarizes the known genetic modifiers of LQTS according to their deleterious or protective effect.…”

Section: Genetic Modifiers Of Long Qt Syndromementioning

confidence: 99%

“…While candidate gene approaches have had some success in identifying plausible modifier genes in LQTS, additional unbiased approaches are needed to discover previously unrecognized genetic factors. An example of a new approach is illustrated by recent work of Chai et al 9 that combined whole exome sequencing and electrophysiological investigations of induced pluripotent stem cell derived cardiomyocytes (iPSC-CM) from members of a large family with type 2 LQTS. In this family, LQTS was associated with a pathogenic mutation in KCNH2 but there were notable differences in disease expression among mutation carriers.…”

Section: Discovery Of Long Qt Syndrome Modifiers Using a Physiologicamentioning

confidence: 99%

Modifier genes for sudden cardiac death

Schwartz

Crotti

George

2018

European Heart Journal

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Genetic conditions, even those associated with identical gene mutations, can present with variable clinical manifestations. One widely accepted explanation for this phenomenon is the existence of genetic factors capable of modifying the consequences of disease-causing mutations (modifier genes). Here, we address the concepts and principles by which genetic factors may be involved in modifying risk for cardiac arrhythmia, then discuss the current knowledge and interpretation of their contribution to clinical heterogeneity. We illustrate these concepts in the context of two important clinical conditions associated with risk for sudden cardiac death including a monogenic disorder (congenital long QT syndrome) in which the impact of modifier genes has been established, and a complex trait (life-threatening arrhythmias in acute myocardial infarction) for which the search for genetic modifiers of arrhythmic risk is more challenging. Advances in understanding the contribution of modifier genes to a higher or lower propensity towards sudden death should improve patient-specific risk stratification and be a major step towards precision medicine.

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“…This makes it challenging to not only accurately diagnose the patient, but also to determine appropriate clinical management. The ability to generate hiPSCs from patients, combined with advances in genome editing technologies, has demonstrated how such a platform can be used to determine the pathogenicity of variants of uncertain significance (VUS) 30,31 , or the contribution of genetic modifiers to the disease phenotype 32 . However, the extent to which hiPSCs can reflect intragenotype differences in disease risk such as that observed between LQT2 patients has not been fully explored 33 .…”

Section: Discussionmentioning

confidence: 99%

Isogenic sets of hiPSC-CMs harboringKCNH2mutations capture location-related phenotypic differences

Brandão

Brink

Miller

et al. 2019

Preprint

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AimsLong QT syndrome type 2 (LQT2) is caused by mutations in the gene KCNH2, encoding the hERG ion channel. Clinically, mild and severe phenotypes are associated with this cardiac channelopathy, complicating efforts to predict patient risk. The location of the mutation within KCNH2 contributes to this variable disease manifestation. Here we determined whether such phenotypic differences could be detected in cardiomyocytes derived from isogenic human induced pluripotent stem cells (hiPSCs) genetically edited to harbour a range of KCNH2 mutations. Methods and ResultsThe hiPSC lines heterozygous for missense mutations either within the pore or tail region of the ion channel were generated using CRISPR-Cas9 editing and subsequently differentiated to cardiomyocytes (hiPSC-CMs) for functional assessment. Electrophysiological analysis confirmed the mutations prolonged the action potentials and field potentials of the hiPSC-CMs, with differences detected between the pore and tail region mutations when measured as paced 2D monolayers. This was also reflected in the cytosolic Ca 2+ transients and contraction kinetics of the different lines. Pharmacological blocking of the hERG channel in the hiPSC-CMs also revealed that mutations in the pore-loop region conferred a greater susceptibility to arrhythmic events. ConclusionThese findings establish that subtle phenotypic differences related to the location of the KCNH2 mutation in LQT2 patients are reflected in hiPSC-CMs under genetically controlled conditions. Moreover, the results validate hiPSC-CMs as a strong candidate for evaluating the underlying severity of individual KCNH2 mutations in humans which could ultimately facilitate patient risk stratification.

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Physiological genomics identifies genetic modifiers of long QT syndrome type 2 severity

Cited by 59 publications

References 58 publications

A computational model of induced pluripotent stem‐cell derived cardiomyocytes incorporating experimental variability from multiple data sources

A computational model of induced pluripotent stem‐cell derived cardiomyocytes incorporating experimental variability from multiple data sources

Modifier genes for sudden cardiac death

Isogenic sets of hiPSC-CMs harboringKCNH2mutations capture location-related phenotypic differences

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