Referenced in: none

Automatically associated channels: Kv10.1 , Kv11.1 , Kv7.1

Title: Modelling the long QT syndrome with induced pluripotent stem cells.

Authors: Ilanit Itzhaki, Leonid Maizels, Irit Huber, Limor Zwi-Dantsis, Oren Caspi, Aaron Winterstern, Oren Feldman, Amira Gepstein, Gil Arbel, Haim Hammerman, Monther Boulos, Lior Gepstein

Journal, date & volume: , 2011 Jan 16 , ,

PubMed link: http://www.ncbi.nlm.nih.gov/pubmed/21240260

Abstract
The ability to generate patient-specific human induced pluripotent stem cells (iPSCs) offers a new paradigm for modelling human disease and for individualizing drug testing. Congenital long QT syndrome (LQTS) is a familial arrhythmogenic syndrome characterized by abnormal ion channel function and sudden cardiac death. Here we report the development of a patient/disease-specific human iPSC line from a patient with type-2 LQTS (which is due to the A614V missense mutation in the KCNH2 gene). The generated iPSCs were coaxed to differentiate into the cardiac lineage. Detailed whole-cell patch-clamp and extracellular multielectrode recordings revealed significant prolongation of the action-potential duration in LQTS human iPSC-derived cardiomyocytes (the characteristic LQTS phenotype) when compared to healthy control cells. Voltage-clamp studies confirmed that this action-potential-duration prolongation stems from a significant reduction of the cardiac potassium current I(Kr). Importantly, LQTS-derived cells also showed marked arrhythmogenicity, characterized by early-after depolarizations and triggered arrhythmias. We then used the LQTS human iPSC-derived cardiac-tissue model to evaluate the potency of existing and novel pharmacological agents that may either aggravate (potassium-channel blockers) or ameliorate (calcium-channel blockers, K(ATP)-channel openers and late sodium-channel blockers) the disease phenotype. Our study illustrates the ability of human iPSC technology to model the abnormal functional phenotype of an inherited cardiac disorder and to identify potential new therapeutic agents. As such, it represents a promising paradigm to study disease mechanisms, optimize patient care (personalized medicine), and aid in the development of new therapies.