Novel ECG measures of electrophysiological substrate
Approved Research ID: 42021
Approval date: December 18th 2018
A sudden cardiac arrest is a tragic event, impacting relatives and community at large. With our long-term goal to reduce the rate of sudden cardiac arrest, we initiated a study of its mechanisms. We use a widely available, inexpensive, and non-invasive tool (12-lead ECG) to describe the underlying abnormalities in the electrical system of the heart. The specific objectives of our proposal are to study an electrical system of the heart, considering sex- and racial/ethnic differences, and to investigate whether and which genetic factors determine a function of the electrical system of the heart, and how it can affect the risk of sudden death. In this application, we build on our prior work. In Specific Aim 1 we will determine the associations between novel ECG phenotypes and incident cardiovascular disease, and describe sex- and racial/ethnic differences in novel ECG phenotypes in populations of men and women. We will analyze resting 12-lead ECG and will measure global electrical heterogeneity (sum absolute QRST integral, spatial ventricular gradient elevation, magnitude, and azimuth, and spatial QRS-T angle). On the exercise ECG, we will analyze heart rate variability, QT variability, and ectopic beats. In Specific Aim 2, we will determine cross-sectional and longitudinal associations of ECG phenotypes with left ventricular function and cardiovascular disease, and with body habitus, body composition, impedance, and physical activity. In Specific Aim 3, we will identify genetic factors associated with the ECG phenotypes and will assess effect modification by sex. This research, building on large previous data collection, will uncover how the cardiac electrical system function, and will improve our understanding of underlying mechanisms that may explain why some people die suddenly and will inform future research that will help to prevent sudden death and reduce its risk.
Study aims are: (1) to identify genetic factors associated with the novel ECG phenotypes (including analyses of premature ventricular contractions at rest and during exercise, repolarization lability, heart rate variability, global electrical heterogeneity), which have been developed by Tereshchenko's group and previously have been shown associated with sudden cardiac arrest; (2) determine associations of novel ECG phenotypes with body habitus, composition, and impedance, and medical history and risk factors of cardiovascular disease in cross-sectional analysis; (3) determine associations of novel ECG phenotypes with longitudinal clinically important outcomes (incident cardiovascular disease, incident coronary heart disease, incident myocardial infarction, incident stroke, incident heart failure, incident atrial fibrillation, sudden death, cardiovascular death, all-cause mortality). Overall, goal of Tereshchenko laboratory is to re-design electrocardiology based on sound electrophysiological foundation. UK Biobank has unique data that can help us to understand effect of body habitus, body composition, and body impedance on ECG morphology. Prospective nature of the UK Biobank will help us to validate associations of novel ECG phenotypes with incident cardiovascular outcomes. Genomics data will allow us to study genetic architecture of novel ECG phenotypes, to uncover underlying biology behind novel ECG phenotypes.
Additional aim: To begin to understand the underlying biology behind electrical dyssynchrony, determine the cross-sectional associations of multiomic data (currently available proteome and metabolome, and as become available telomere length (epigenetic assessment) and transcriptome) with each of the global electrical heterogeneity (GEH) phenotypes in the UK Biobank (UKB).
The GEH concept is based on biophysically sound Wilson's Spatial Ventricular Gradient (SVG) idea. GEH is quantified by 5 features of SVG: SVG direction (azimuth and elevation), SVG magnitude, SVG's scalar (SAIQRST), and spQRSTa. In a large (n=118,780) multi-ancestry genome-wide association study (GWAS) for spQRSTa, the PI's team identified 61 genetic loci. Notably, in Mendelian randomization analysis, the polygenic risk score of the spQRSTa was associated with BBB, suggesting that spQRSTa is a causal biomarker for BBB. Considering the strong biophysical, mechanistic nature of the 5 GEH phenotypes and their causal role for BBB, there is a high likelihood of meaningful discoveries of biological mechanisms underlying HF development, leading to future discoveries of novel HF therapies. To uncover the underlying biology behind GEH, we will use WGS and multiomics data.