Electrophysiological Phenotyping Of Patients at Risk of Ventricular Arrhythmia and Sudden Cardiac Death

Overview

Obesity, rheumatoid arthritis (RA) and gene-specific dilated cardiomyopathy (DCM) are common medical conditions. Small-scale studies have shown that these are associated with proarrhythmic changes on 12-lead electrocardiogram (ECG) and a higher risk of sudden cardiac death (SCD). However, these studies lack the deep electrophysiological phenotyping required to explain their observations. Electrocardiographic imaging (ECGi) is a non-invasive alternative to 12-lead ECG, by which epicardial potentials, electrograms and activation sequences can be recorded to study adverse electrophysiological modelling in greater depth and on a more focussed, subject-specific scale. Therefore, this study proposes to better define the risk of arrhythmia and understand the underlying adverse electrophysiological remodelling conferring this risk in three groups (obesity, RA and DCM). Firstly, data from two large, national repositories will be analysed to identify associations between routine clinical biomarkers and proarrhythmic 12-lead ECG parameters, to confirm adverse electrophysiological remodelling and a higher risk of arrhythmia. Secondly,ECGi will be performed before and after planned clinical intervention in obese and RA patients, and at baseline in titin-truncating variant (TTNtv)-positive and -negative DCM patients, to characterise the specific and potentially reversible conduction and repolarisation abnormalities that may underlie increased arrhythmic risk.

Sudden cardiac death (SCD) occurs in groups that are neither traditionally considered high-risk nor have been the subject of large-scale studies. These include obesity, inflammatory arthropathy and gene-specific cardiomyopathy. Existing data to explain higher risk of arrhythmia in these cohorts rely on 12-lead ECG and therefore lack in-depth electrophysiological phenotyping. The investigators have access to the two large national data repositories providing a wealth of data to study risks of arrhythmia on a scale larger than any previously published study. They also have a proven track record of utilising electrocardiographic imaging (ECGi) to conduct in-depth investigation of electrophysiological remodelling to better characterise arrhythmic risk. ECGi is a validated, noninvasive method of acquiring body surface potential data using 252-electrodes and combining it with subjectspecific heart-torso geometry from crosssectional imaging. Using inverse solution mathematical algorithms, the ECGi system reconstructs epicardial unipolar electrograms and panoramic activation and potential maps over a single sinus beat, which is visualised on a digitised image of the subject's heart. Various studies have demonstrated the efficacy of ECGi to localise ventricular arrhythmias; more accurately calculate QT interval dispersion than 12-lead ECGs in obesity; and characterise ventricular tachycardia (VT) with intramural re-entry following myocardial infarction-induced scarring. The study aims to confirm that obesity, RA and DCM are risk factors for arrhythmia and associated with electrophysiological remodelling manifest on 12-lead ECG, using large data repositories. The investigators will also perform electrocardiographic imaging (ECGi) to investigate and understand specific, and potentially reversible, conduction and repolarisation abnormalities conferring risk of arrhythmia in these cohorts using ECGi. Hypotheses: 1. Routine clinical biomarkers correlate with proarrhythmic 12-lead ECG parameters 2. Adverse (proarrhythmic) electrophysiological remodelling can be quantified with ECGi 3. Bariatric surgery reverses adverse electrophysiological remodelling in obesity 4. Pharmacological therapy reverses adverse electrophysiological remodelling in RA 5. TTNtv is associated with adverse electrophysiological remodelling in DCM In-keeping with hypothesis 1, the study population will include participants from the UK biobank and Airwave Health Monitoring Study in which risk of arrhythmia will be defined. Participants in both data repositories provided informed consent for their data to be used for research. With respect to hypotheses 2-5, the study will involve 3 distinct ECGi sub-studies, each in a well-defined cohort to identify specific, and potentially reversible, conduction and repolarisation abnormalities, and comparing the disease to healthy controls. These are: i. Obesity (BMI \>40) ii. RA iii. TTNtv-positive and -negative DCM