While molecular biology has evidenced gene-specific ion-channel dysfunctions in patients with the Long QT syndrome (LQTS), the clinical studies have described a large spectrum of arrhythmogenic mechanisms involved in the triggering of life-threatening arrhythmias between and within specific gene. Genotyping is considered the most reliable tool to identify the presence of the LQTS, but genetic testing captures only 75% of phenotypically affected LQTS individuals, and negative test in a phenotype-positive patient does not rule out the presence of the syndrome. Importantly, these tests do not fully capture an individual risk to life-threatening arrhythmias that is modulated by exogenous factors. The surface electrocardiogram (ECG) is an investigational tool that could provide insights into the integrated functional defects associated with LQTS mutations. Therefore, we propose to conduct a project to identify ECG features associated with risk in LQTS patients. We will investigate ECG parameters beyond QTc prolongation focusing on capturing dynamic features of the QT and RR intervals coupling. More specifically, we propose to evaluate a method describing the instantaneous components of the QT response to changes in heart rate as a genetically-determined imprint of cardiac repolarization profile in LQTS patients. The proposal relies on a unique set of Holter ECGs recorded from ~1,210 genotyped LQTS patients gathered from three registries (American, Italian and French). We will study the reproducibility of the proposed ECG markers and their association with patients'events based on data from a retrospective and a prospective study. Several methods will be developed to risk stratify LQTS patients for cardiac events, and to estimate their susceptibility to specific triggers such as arousal, sleep/rest, and physical stress. Ultimately, we aim to improve the prognosis and management of LQTS patients.
We plan to conduct a study of 24-hour Holter electrocardiograms from a large cohort of ~1210 genotyped Long QT syndrome (LQTS) patients acquired from both retrospective and prospective studies. The project focuses on the measurements of static and dynamic features of the ventricular repolarization with a strong component pertaining to the measurements of the dynamic coupling between the QT and the RR intervals. Based on novel computerized ECG techniques, we will evaluate if these ECG factors are associated with both cardiac events and their triggers (arousal, exercise, and sleep). The proposed work aimed to validate novel risk stratification techniques that will help clinicians to better treat patients with the long QT syndrome.
| Page, Alex; McNitt, Scott; Xia, Xiaojuan et al. (2017) Population-based beat-to-beat QT analysis from Holter recordings in the long QT syndrome. J Electrocardiol 50:787-791 |
| Page, Alex; Aktas, Mehmet K; Soyata, Tolga et al. (2016) ""QT clock"" to improve detection of QT prolongation in long QT syndrome patients. Heart Rhythm 13:190-8 |
