The long QT syndrome (LQTS) is a condition characterized by abnormal prolongation of the QT interval with an associated risk of ventricular arrhythmias and sudden cardiac death. Congenital forms of LQTS arise due to rare and highly penetrant mutations that segregate in a Mendelian fashion. Over the years, multiple mutations in genes encoding ion channels and ion channel binding proteins have been reported to underlie congenital LQTS. Drugs are by far the most common cause of acquired forms of LQTS. Emerging evidence suggests that drug-induced LQTS also has a significant heritable component. However, the genetic substrate underlying drug-induced LQTS is presently largely unknown. In recent years, advances in next-generation sequencing technology and molecular biology techniques have significantly enhanced our ability to identify genetic variants underlying both monogenic diseases and more complex traits. In this review, we discuss the genetic basis of congenital and drug-induced LQTS and focus on future avenues of research in the field. Ultimately, a detailed characterization of the genetic substrate underlying congenital and drug-induced LQTS will enhance risk stratification and potentially result in the development of tailored genotype-based therapies.
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http://dx.doi.org/10.1007/s10840-013-9779-5 | DOI Listing |
J Biol Chem
November 2024
Department of Pharmacology, College of Pharmacy, Harbin Medical University, Harbin, Heilongjiang Province, China. Electronic address:
Cureus
July 2024
Department for Cardiovascular Diseases, Institute for Treatment and Rehabilitation Niska Banja, Nis, SRB.
Atrial fibrillation (AF) is the most common long-term arrhythmia in adults. Rhythm control in patients with AF involves efforts to restore and maintain sinus rhythm and is accomplished by medication, catheter ablation, or electrical cardioversion. Amiodarone represents one of the most commonly used antiarrhythmic medications.
View Article and Find Full Text PDFCureus
November 2023
Cardiology, Centro Hospitalar Universitário de Santo António, Porto, PRT.
Drug-induced long QT syndrome (LQTS) is defined as prolonged corrected QT interval (QTc ≥460 ms) plus polymorphic ventricular arrhythmia fitting the description of torsades de pointes temporally associated with the administration of a drug or combination of drugs. Amiodarone therapy is a known uncommon cause of acquired QT interval prolongation that should not be underestimated. We present a case of an iatrogenic electrical storm with atrial fibrillation (AF) in which amiodarone was administered to attempt chemical cardioversion, resulting in an unnoticed prolongation of the QT interval, with subsequent repeated polymorphic ventricular tachycardia, managed with isoproterenol.
View Article and Find Full Text PDFACS Omega
October 2023
Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahçeşehir University, Istanbul 34353, Turkey.
The human ether-à-go-go-related gene (hERG) channel plays a crucial role in membrane repolarization. Any disruptions in its function can lead to severe cardiovascular disorders such as long QT syndrome (LQTS), which increases the risk of serious cardiovascular problems such as tachyarrhythmia and sudden cardiac death. Drug-induced LQTS is a significant concern and has resulted in drug withdrawals from the market in the past.
View Article and Find Full Text PDFJ Electrocardiol
January 2024
Department of Computer Science, The University of Manchester, Manchester, UK.
Background: Drug-induced QT-prolongation increases the risk of TdP arrhythmia attacks and sudden cardiac death. However, measuring the QT-interval and determining a precise cut-off QT/QTc value that could put a patient at risk of TdP is challenging and influenced by many factors including female sex, drug-free baseline, age, genetic predisposition, and bradycardia.
Objectives: This paper presents a novel approach for intuitively and visually monitoring QT-prolongation showing a potential risk of TdP, which can be adjusted according to patient-specific risk factors, using a pseudo-coloring technique and explainable artificial intelligence (AI).
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