Investigations of the neural mechanisms of cardiac stability

Electrical instability of the heart is known to precede the onset of lethal arrhythmias and the autonomic nervous system (ANS) is a primary factor in this process. However, the exact mechanisms of failure remain poorly understood. This work aims to better understand how ANS activity affects the electrical properties of the heart by investigating the effect of autonomic rhythms on the ventricular action potential duration (APD) recorded at tissue level using unipolar electrograms (UEGs). Studying dynamic behaviour of APD was associated with large data-sets of UEGs. Methods were developed to improve accuracy of automatic detection of APD, like narrow search windows and correlation filters to detect ambiguous activity. A simulation study was conducted to generate realistic UEG recordings to examine the effect of signal quality and filtering on tracking of APD dynamics. New insights were provided in how signal quality and filtering affect the accuracy of APD tracking. The proposed improvements were found to reduce the detection error substantially. The effect of autonomic rhythms on ventricular APD was explored using existing clinical data. By employing techniques to determine causality and time-frequency coherence, evidence was found that the ANS modulates ventricular electrophysiology: (1) with respiratory behaviour via a direct causal pathway, and (2) at a lower frequency and related to signs of enhanced sympathetic activity in blood pressure observed during mental stress. Further investigations were undertaken by designing and conducting a clinical experiment to study the effect of baroreceptor control on APD. Novel methodologies to determine the statistical significance of response curves were used to demonstrate for the first time that ventricular APD can be influenced by baroreceptor stimulation independent of heart rate. Identification of the neural mechanisms controlling cardiac stability may ultimately contribute to the development of new diagnostic tools and treatments to prevent thousands of deaths each year

Sex Differences in the Morphology of RR-Matched T-waves

Evidence of sex-related differences in cardiac risk is emerging, but whether these reflect sex-related differences in ventricular electrophysiology remains unclear. Our aim was to quantify T-wave morphological differences between men and women across different leads and RR interval values. We analysed 12-lead ECG recordings from 23,962 participants in the UK Biobank without known cardiovascular disease, and subsequently clustered them into bins of RR interval. In each cluster, we derived a lead and sex-specific mean warped T-wave (MWT). Then, we quantified differences between MWT in men and women in time and amplitude using linear, d_{w} and d_{a}, and non-linear markers, d_{w}^{NL} and d_{a}^{NL}. Leads V3 and aVR showed the lowest differences between men and women (median d_{w}, d_{w}^{NL}, d_{a} and d_{a}^{NL} of 1.12 ms, 0.69 ms, 3.29 and 1.20, respectively), while V1 showed the largest (5.69 ms, 4.50 ms, 208.94 and 199.45, respectively). Sex-related differences in MWT increased with the RR interval (d_{w}, d_{w}^{NL}, d_{a} and d_{a}^{NL} ranging 1.44 - 5.89 ms, 1.23 - 3.97 ms, 8.58 - 28.38 and 1.53 - 4.41, respectively). These values compare to those found for morphological T-wave variations due to large changes in heart rate (5.66 ms, 2.35 ms, 57.61 and 9.51, respectively). These results indicate sex and lead should be considered when using T-wave morphologies for cardiovascular risk prediction

Theoretical assessment of a repolarization time marker based on the intracardiac bipolar electrogram

The spatio-temporal organization of cardiac repolarization modulates the vulnerability to dangerous ventricular arrhythmias. Methodologies that provide accurate assessment of cardiac repolarization are of primary importance for a better understanding of cardiac electrophysiology and represent a potentially useful tool for clinical applications. The most commonly used repolarization time (RT) marker from extracellular recordings is derived from the unipolar electrogram (UEG). However, far field potentials and remote activity may in certain conditions bias this marker. In this paper, a RT marker based on the bipolar electrogram (BEG) is proposed. An analytical expression of the BEG based on a simple model of the cardiac extracellular potential is derived. According to the proposed analytical framework the BEG exhibits a repolarization wave whose extremum (maximum or minimum) corresponds to the average of the local RTs at the two electrodes of the bipole. The amplitude of this extremum is a function of the steepness of phase 3 of the action potentials, inter-electrode distance, conduction velocity and direction of wave-back propagation. A simulation study based on this analytical framework showed that for noisy to good signal quality (SNR of the UEG ≥ 10 dB), and for a typical inter-electrode distance of 2 mm, conduction velocity between 0.2 and 0.6 m/s, and an angle between conduction direction and the inter-electrode axis ≤ π/4, the median absolute error was lower than 6.8 ms while the median linear correlation between estimated and theoretical RT was higher than 0.91. Examples of RT derived from BEG recorded in a structurally normal heart in both the right and left ventricles demonstrate that the proposed procedure is feasible in human in-vivo studies

Genetic Architecture of Quantitative Cardiovascular Traits: Blood Pressure, ECG and Imaging Phenotypes

Background: We provide an overview of the genetic architecture of quantitative cardiovascular phenotypes such as blood pressure (BP), electrocardiogram (ECG) and cardiac imaging measurements which play a critical and prognostic role in the management of numerous diseases. Methods: The genetics of BP, ECG and cardiac imaging traits have been studied in large-scale genome-wide association studies (GWASs). Results: To-date more than 1,400 BP loci have been discovered. These genetic loci harbouring known and novel BP-regulating genes, several of which are linked to existing drugs, that can be repurposed for BP treatment. Regarding the ECG indices, 437 independent signals have been reported for resting heart rate (n 400,000), mainly modulating the autonomic nervous system, as well as 202 loci for PR interval, 29 loci for QRS duration and 35 loci for QT interval. The LV GWASs (n 17,000) identified 14 loci harbouring genes regulating the cardiac developmental pathways. Conclusion: Large-scale genetic analyses of quantitative cardiovascular traits have yielded hundreds of susceptibility loci, candidate genes and key biological pathways, which significantly advance our understanding of their genetic architecture and shed lights on potential novel therapeutic targets

Effect of autonomic blocking agents on the respiratory-related oscillations of ventricular action potential duration in humans

Ventricular action potential duration (APD) is an important component of many physiological functions including arrhythmogenesis. APD oscillations have recently been reported in humans at the respiratory frequency. This study investigates the contribution of the autonomic nervous system to these oscillations. In 10 patients undergoing treatment for supraventricular arrhythmias, activation recovery intervals (ARI; a conventional surrogate for APD) were measured from multiple left and right ventricular (RV) endocardial sites, together with femoral artery pressure. Respiration was voluntarily regulated and heart rate clamped by RV pacing. Sympathetic and parasympathetic blockade was achieved using intravenous metoprolol and atropine, respectively. Metroprolol reduced the rate of pressure development (maximal change in pressure over time): 1,271 (± 646) vs. 930 (± 433) mmHg/s; P < 0.01. Systolic blood pressure (SBP) showed a trend to decrease after metoprolol, 133 (± 21) vs. 128 (± 25) mmHg; P = 0.06, and atropine infusion, 122 (± 26) mmHg; P < 0.05. ARI and SBP exhibited significant cyclical variations (P < 0.05) with respiration in all subjects with peak-to-peak amplitudes ranging between 0.7 and 17.0 mmHg and 1 and 16 ms, respectively. Infusion of metoprolol reduced the mean peak-to-peak amplitude [ARI, 6.2 (± 1.4) vs. 4.4 (± 1.0) ms, P = 0.008; SBP, 8.4 (± 1.6) vs. 6.2 (± 2.0) mmHg, P = 0.002]. The addition of atropine had no significant effect. ARI, SBP, and respiration showed significant coupling (P < 0.05) at the breathing frequency in all subjects. Directed coherence from respiration to ARI was high and reduced after metoprolol infusion [0.70 (± 0.17) vs. 0.50 (± 0.23); P < 0.05]. These results suggest a role of respiration in modulating the electrophysiology of ventricular myocardium in humans, which is partly, but not totally, mediated by β-adrenergic mechanisms

Interaction between ECG and Genetic Markers of Coronary Artery Disease

Coronary artery disease (CAD) is the main contributor to cardiovascular mortality in developed countries, making accurate diagnosis of utmost importance. We developed risk scores to assess CAD risk in a population without known cardiovascular disease by combining ECG and a genetic risk score (GRS) for CAD. We analysed data in 52,260 individuals in the UK Biobank study. ECG indices included heart rate, PR, QRS, QT and T-peak-to-T-end intervals, while we built the GRS from publicly available genome-wide association results for CAD that were derived in an independent population. In a training set (N = 39,195), the indices with the strongest CAD prognostic impact were the PR and QT intervals, and the GRS. When combined together into a Multivariate model, both the ECG markers and the GRS were independently associated with CAD. In an independent test set (N = 13,065), we then built three risk scores based on (1) ECG markers, (2) genetic data, and (3) a combination of ECG and genetic data, respectively. The hazard ratio (95% confidence interval) for CAD comparing high versus low-risk individuals was 6.5 (5.1 - 8.3),8.4 (6.4 - 10.8) and 8.4 (6.5 - 10.8) for the three risk scores, respectively. In conclusion, the inclusion of genetic markers into risk scores with ECG markers independently contributes to CAD risk prediction in a large population of individuals without known cardiovascular disease

Evaluating the Impact of Physiological Variability in Genome-Wide Association Studies of Resting Heart Rate

Genome-wide association studies (GWAS) have discovered hundreds of genetic loci for resting heart rate (RHR). However, the impact of intra-individual variation in RHR on GWAS results is unclear. We evaluated this impact by analyzing two RHR recordings from N 61,000 subjects from UK Biobank. In addition, we modelled variations in RHR as independent white zero-mean Gaussian noise with a standard deviation of 0.5x, 1x, and 2x the standard deviation of the difference between the original RHR values (4,8, and 16 bpm, respectively). The two original RHR recordings were highly correlated (? =0.77), but results from the genetic analyses were s lightly different: the number of genome-wide significant (p < 5x10-8) variants at the locus with the strongest reported association (MYH6): n=39 vs. n=34; the p-value of the corresponding lead-variant, 3.6x10-24 vs. 2.1x10-19; and the estimated heritability 20.0% vs. 16.7%. Simulated data showed an inverse relationship between RHR variation and genetic association strength and heritability. Results formally demonstrate the impact of intra-individual RHR variability on the discovery of genetic variants in single-measurement studies

A Method to Minimise the Impact of ECG Marker Inaccuracies on the Spatial QRS-T angle: Evaluation on 1,512 Manually Annotated ECGs

© 2020 The Author(s) The spatial QRS-T angle (QRS-Ta) derived from the vectorcardiogram (VCG) is a strong risk predictor for ventricular arrhythmia and sudden cardiac death with potential use for mass screening. Accurate QRS-Ta estimation in the presence of ECG delineation errors is crucial for its deployment as a prognostic test. Our study assessed the effect of inaccurate QRS and T-wave marker placement on QRS-Ta estimation and proposes a robust method for its calculation. Reference QRS-Ta measurements were derived from 1,512 VCGs manually annotated by three expert reviewers. We systematically changed onset and offset timings of QRS and T-wave markers to simulate inaccurate placement. The QRS-Ta was recalculated using a standard approach and our proposed algorithm, which limits the impact of VCG marker inaccuracies by defining the vector origin as an interval preceding QRS-onset and redefines the beginning and end of QRS and T-wave loops. Using the standard approach, mean absolute errors (MAE) in peak QRS-Ta were >40% and sensitivity and precision in the detection of abnormality (>105°) were 15 ms. Using our proposed algorithm, MAE for peak QRS-Ta were reduced to 94% for inaccuracies up to ±15 ms. Similar results were obtained for mean QRS-Ta. In conclusion, inaccuracies of QRS and T-wave markers can significantly influence the QRS-Ta. Our proposed algorithm provides robust QRS-Ta measurements in the presence of inaccurate VCG annotation, enabling its use in large datasets