Analysing electrocardiographic traits and predicting cardiac risk in UK biobank

Abstract

The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.

Keywords: Arrhythmias; clinical electrophysiology; drugs; genomics; ion channels; membrane transport.

Figure 1.

Heart rate profile and indices. (a) Heart rate (HR) profile and HR markers during the exercise stress test. The heart rate profile, x_HR(t) (solid dark line) is a function of time obtained by filtering the instantaneous HR (dots). HR_rest: Mean x_HR(t) over 15 sec resting; HR_rec: minimum x_HR(t) during recovery; ΔHR_ex = HR at peak exercise − HR_rest: HR dynamics during exercise; ΔHR_rec = HR at peak exercise − HR at full recovery: HR dynamics during recovery. (b) Distribution of the heart rate profile across all participants. Black solid line, dark and light shadowed areas represent median, 25th–75th percentiles and 5th–95th percentile intervals, respectively. Adapted from Orini et al.

Figure 2.

Schematic illustration of markers of ventricular repolarisation dynamics during exercise and recovery. Three averaged heartbeats were derived at rest (black), peak exercise (red), and full recovery (green), respectively. QT and T-peak-to-end (Tpe) intervals were measured for each of the three heartbeats. The QT and Tpe dynamics during exercise were calculated as the difference between the QT and Tpe intervals, respectively, at rest and peak exercise, divided by the corresponding change in RR interval (not shown here). Dynamics during recovery were calculated in a similar fashion but using the intervals measured at recovery instead of rest. Morphological changes between the T waves at rest, peak exercise and recovery were quantified by the T-wave morphology restitution (TMR) index.

Figure 3.

Overlap of candidate genes for dynamic traits and Tpeak-Tend interval. The figure shows overlap of candidate genes for each ECG measure. 1. Heart rate response to exercise, 2. Heart rate response to recovery, 3. QT dynamics on exercise, 4. QT dynamics on recovery, 5. Resting Tpeak-Tend interval, 6. Tpeak-Tend dynamics on exercise, 7. T-wave morphology restitution index (TMR) on exercise, 8. TMR on recovery. PK; Protein kinase. Graphic created using BioRender.com.

Figure 4.

Overview of genetic analyses in the UKB exercise study. The number of loci are those which are genome-wide significant (P value). H2 = heritability; ^ indicates approx. number of resting heart rate loci (results from all UK Biobank sample); * indicates number of loci discovered in the exercise study (unpublished); QTc = corrected QT interval, Tpe = T-waves peak and end, TMR = T-wave morphology restitution index, ΔTrait ex = difference in trait from resting and peak exercise; ΔTrait rec - difference in trait from peak exercise and 1 min following exercise; CV = cardiovascular.