Effect of Sex and Underlying Disease on the Genetic Association of QT Interval and Sudden Cardiac Death

Does COVID-19 impact the QT interval prolongation? Answers from genetic causal inference

During the COVID-19 pandemic, there has been heightened interest in the QT interval, a crucial indicator of ventricular electrical activity. Mendelian randomization (MR) is used here to investigate the genetic causation between QT interval alterations and COVID-19. Genetic proxies representing three COVID-19 phenotypes-severe, hospitalized, and COVID-19-were identified in over 1,000,000 individuals of European ancestry. Univariate two-sample MR (TSMR) and multi-exposure-adjusted multivariate MR (MVMR) were used to assess genetic causal associations between COVID-19 and QT intervals in 84,630 UK Biobank participants. The MR-robust adjusted profile score (MR-RAPS) method and radial MR frame were utilized for effective robustness and outlier variant detection, with sensitivity analyses conducted to identify horizontal pleiotropy. For every COVID-19 phenotype, univariate TSMR analysis revealed non-significant causal estimates between COVID-19 and the QT interval [COVID-19: βIVW (95% CI): -0.44 (-1.72, 0.84), P = 0.50; hospitalization: βIVW: 0.12 (-0.57, 0.80), P = 0.74; severe case: βIVW: 0.11 (-0.29, 0.51), P = 0.58]. MR-RAPS and outlier-corrected radial MR analyses further supported this null causal estimation. In confounder-adjusted MVMR analysis, this nonsignificant causality was independent of body mass index (BMI), smoking, and alcohol consumption [βBMI+Alcohol+Smoking (95% CI): -0.77 (-2.44, 0.91), P = 0.37]. Sensitivity analyses did not detect any evidence of bias from horizontal pleiotropy, abnormal data distribution, or weak instruments. These findings suggest that COVID-19 does not directly causally prolong the QT interval. Inconsistent findings in observational research may be attributed to residual confounding.

Causal inference in the field of arrhythmia: An introduction to mendelian randomization

Mendelian randomization (MR) uses genetic variants associated with an exposure (eg, high blood pressure) as instrumental variables to test causal effects on an outcome (eg, atrial fibrillation [AF]). By leveraging the random assortment of genetic variants during gamete formation, MR reduces biases like confounding and reverse causation. We screened 391 papers, examining 277 that applied MR to investigate arrhythmia and, in others, cardiovascular traits, lifestyle, behavioral traits, and body composition. Our analysis focused on MR studies of arrhythmia and cardiovascular traits. Key findings highlight high systolic blood pressure, low resting heart rate, elevated cardiac troponin I levels, coronary artery disease, and heart failure as risk factors for AF, whereas AF itself increases heart failure risk. As genetic data become more accessible, MR's relevance grows. Sensitivity analyses and integrating MR with other methodologies in a triangulation framework enhance the robustness of causal inferences by navigating different biases.

Sudden Cardiac Death: A Systematic Review

Sudden cardiac death (SCD) is a condition that accounts for a high percentage of cardiovascular fatalities, with ventricular tachyarrhythmias being the most common cause. There are signs and symptoms of SCD that occur spontaneously without any warning and are deadly. Despite preventative efforts focusing on the use of subcutaneous implanted cardioverter defibrillators (S-ICD) in the highest-risk population categories, a high number of SCDs occur in the normal population and in people who do not have a documented cardiac condition. Therefore, primary prevention for SCD should be a more viable strategy for the general population, considering measures in the form of preventive medicine such as knowing more about any genetic predisposition, family history of any fatal arrhythmia, continuous surveillance after any syncope with unknown causes, etc. However, little data about SCD risk factors are known in comparison with other well-known diseases like ischemic heart disease and stroke. In search of medical databases for relevant medical literature, we looked at PubMed/Medline, the Cochrane Library, and Google Scholar. Thirteen publications were discovered after the papers were located, assessed, and qualifying criteria were applied. The finished articles were done to give an overview of SCD. Some others have shown that the major predisposition for SCD is related to the male gender, which increases the incidence if they have a family history of SCD. We described the importance of obstructive sleep apnea (OSA) as a comorbid condition. Patients with S-ICD and young athletes with a history of ventricular arrhythmia showed us that the predisposition for SCD can be higher than in the normal population. Based on the above, we concluded that more study is required to establish the most important approach for each of the risk factors mentioned in this systematic review in order to apply them in daily practice and have more knowledge about how to apply preventive and therapeutic medicine to the population at risk and the ones that already develop the disease.

Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization.

Gender-affirming hormone treatment causes changes in gender phenotype in a 12-lead electrocardiogram

BACKGROUND

Men and women have specific patterns in an electrocardiogram (ECG) differentiated by J-point elevation and ST-segment angle. Although gender-affirming hormone treatment is one of the treatments for gender dysphoria, its influence on an ECG has not been clarified yet.

OBJECTIVE

The purpose of this study was to investigate ECG changes induced by gender-affirming hormone treatment.

METHODS

The study population consisted of 29 transgender males and 8 transgender females and 37 age- and sex-matched cisgender females and males. Male pattern was defined as J-point elevation > 0.1 mV and ST-segment angle > 20° in precordial leads.

RESULTS

In the comparison between 29 transgender males and cisgender females, the prevalence of the male pattern (89.7% vs 6.9%; P < .001), prevalence of the early repolarization pattern (51.7% vs 17.2%; P = .01), J-point elevation (leads V₁-V₆), T-wave amplitudes (leads V₁-V₆), QRS amplitudes (leads II, III, V₁-V₆), and P-wave amplitudes (leads V₁-V₃) were significantly higher in transgender males. The prevalence of the male pattern was lower in transgender females than in cisgender males (25.0% vs 87.5%; P = .04). In the analysis of transgender males for whom ECGs were available before and after gender-affirming hormone treatment (n = 13), J-point elevation and T-wave amplitudes significantly increased after gender-affirming hormone treatment, leading to a higher prevalence of the male pattern (23.1% vs 92.3%; P < .001). The prevalence of the early repolarization pattern and QRS amplitudes also significantly increased after the treatment, but the augmentation of P-wave amplitudes was modest.

CONCLUSION

Gender-affirming hormone treatment for gender dysphoria is accompanied by a change in ECG phenotype toward affirming gender, in which change in androgen level may be involved.

Effect of Sex and Underlying Disease on the Genetic Association of QT Interval and Sudden Cardiac Death

Background Sudden cardiac death (SCD) accounts for ≈300 000 deaths annually in the United States. Men have a higher risk of SCD and are more likely to have underlying coronary artery disease, while women are more likely to have arrhythmic events in the setting of inherited or acquired QT prolongation. Moreover, there is evidence of sex differences in the genetics of QT interval duration. Using sex- and coronary artery disease-stratified analyses, we assess differences in genetic association between longer QT interval and SCD risk. Methods and Results We examined 2282 SCD subjects and 3561 Finnish controls. The SCD subjects were stratified by underlying disease (ischemic versus nonischemic) and by sex. We used logistic regression to test for association between the top QT interval-associated single-nucleotide polymorphism, rs12143842 (in the NOS1AP locus), and SCD risk. We also performed Mendelian randomization to test for causal association of QT interval in the various subgroups. No statistically significant differences were observed between the sexes for associations with rs12143842, despite the odds ratio being higher in females across all subgroup analyses. Consistent with our hypothesis, female non-ischemics had the highest odds ratio point estimate for association between rs12143842 and SCD risk and male ischemics the lowest odds ratio point estimate (P=0.036 for difference). Similar trends were observed for the Mendelian randomization analysis. Conclusions While individual subgroup comparisons did not achieve traditional criteria for statistical significance, this study is consistent with the hypothesis that the causal association of longer QT interval on SCD risk is stronger in women and nonischemic individuals.