Common Genetic Variants Modulate the Electrocardiographic Tpeak-to-Tend Interval

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

Electrocardiographic Findings in Children With Growth Hormone Deficiency

Introduction It has been shown that cardiac functions begin to deteriorate in growth hormone (GH) deficiency even in childhood. However, little is known about how GH deficiency affects arrhythmogenesis. The aim of this study was to evaluate the parameters of P wave dispersion (Pd), QT dispersion (QTd), corrected QT (QTc) dispersion (QTcd), T wave peak-to-end (Tp-e) interval, Tp-e/QT ratio, and Tp-e/QTc ratio in children with GH deficiency. This study also aimed to evaluate the relationship of these parameters with insulin-like growth factor 1 (IGF-1) and insulin-like growth factor binding protein 3 (IGFBP-3). Method In the study, records of children diagnosed with GH deficiency in Adana City Training and Research Hospital Pediatric Endocrine Outpatient Clinic between September 2021 and December 2022 were retrospectively reviewed. The control group consisted of children in the same age group who applied to the Emergency Outpatient Clinic with a complaint of chest pain and no pathological finding was detected. The electrocardiograms (ECGs) of all patients were retrospectively evaluated. Results There were a total of 82 children in the study, 41 of whom were diagnosed with GH deficiency and 41 in the healthy control group. The age and male/female ratio of children with GH deficiency were similar to those in the control group (p>0.05). There were 27 (66%) children with complete GH deficiency and 14 (34%) children with partial GH deficiency. P wave dispersion was similar in both GH-deficient children and control group children. It was also similar in children with complete and partial GH deficiency (p>0.05). QT and QTc dispersions were found to be increased in children with GH deficiency, although not statistically significant, compared to the control group (p>0.05). Tp-e interval, Tp-e/QTmax (longest QT interval), and Tp-e/QTcmax (longest QTc interval) ratios were increased in children with GH deficiency compared to the control group (p=0.001, p=0.003, and p=0.001, respectively). QT and QTc dispersion, Tp-e interval, Tp-e/QTmax, and Tp-e/QTcmax ratios were found to be increased in children with complete GH deficiency compared to children with partial GH deficiency, but the difference was not significant (p>0.05). No correlation was found between these ECG parameters and IGF-1, IGFBP-3, and peak GH levels after stimulation tests (p>0.05). Conclusion We found in our study that the Tp-e interval was longer and Tp-e/QT and Tp-e/QTc ratios were increased in children with GH deficiency. These results suggest that the risk of ventricular arrhythmias in children with GH deficiency may start to increase from childhood. However, further prospective studies are needed to confirm our results.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Cardiac Repolarization in Health and Disease

Abnormal cardiac repolarization is at the basis of life-threatening arrhythmias in various congenital and acquired cardiac diseases. Dysfunction of ion channels involved in repolarization at the cellular level are often the underlying cause of the repolarization abnormality. The expression pattern of the gene encoding the affected ion channel dictates its impact on the shape of the T-wave and duration of the QT interval, thereby setting the stage for both the occurrence of the trigger and the substrate for maintenance of the arrhythmia. Here we discuss how research into the genetic and electrophysiological basis of repolarization has provided us with insights into cardiac repolarization in health and disease and how this in turn may provide the basis for future improved patient-specific management.

CLIN_SKAT: an R package to conduct association analysis using functionally relevant variants

Background

Availability of next generation sequencing data, allows low-frequency and rare variants to be studied through strategies other than the commonly used genome-wide association studies (GWAS). Rare variants are important keys towards explaining the heritability for complex diseases that remains to be explained by common variants due to their low effect sizes. However, analysis strategies struggle to keep up with the huge amount of data at disposal therefore creating a bottleneck. This study describes CLIN_SKAT, an R package, that provides users with an easily implemented analysis pipeline with the goal of (i) extracting clinically relevant variants (both rare and common), followed by (ii) gene-based association analysis by grouping the selected variants.

Results

CLIN_SKAT offers four simple functions that can be used to obtain clinically relevant variants, map them to genes or gene sets, calculate weights from global healthy populations and conduct weighted case–control analysis. CLIN_SKAT introduces improvements by adding certain pre-analysis steps and customizable features to make the SKAT results clinically more meaningful. Moreover, it offers several plot functions that can be availed towards obtaining visualizations for interpretation of the analyses results. CLIN_SKAT is available on Windows/Linux/MacOS and is operative for R version 4.0.4 or later. It can be freely downloaded from https://github.com/ShihChingYu/CLIN_SKAT, installed through devtools::install_github("ShihChingYu/CLIN_SKAT", force=T) and executed by loading the package into R using library(CLIN_SKAT). All outputs (tabular and graphical) can be downloaded in simple, publishable formats.

Conclusions

Statistical association analysis is often underpowered due to low sample sizes and high numbers of variants to be tested, limiting detection of causal ones. Therefore, retaining a subset of variants that are biologically meaningful seems to be a more effective strategy for identifying explainable associations while reducing the degrees of freedom. CLIN_SKAT offers users a one-stop R package that identifies disease risk variants with improved power via a series of tailor-made procedures that allows dimension reduction, by retaining functionally relevant variants, and incorporating ethnicity based priors. Furthermore, it also eliminates the requirement for high computational resources and bioinformatics expertise.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04987-2.

Prediction of Coronary Artery Disease and Major Adverse Cardiovascular Events Using Clinical and Genetic Risk Scores for Cardiovascular Risk Factors

BACKGROUND

Coronary artery disease (CAD) and major adverse cardiovascular events (MACE) are the leading causes of death in the general population, but risk stratification remains suboptimal. CAD genetic risk scores (GRSs) predict risk independently from clinical tools, like QRISK3. We assessed the added value of GRSs for a variety of cardiovascular traits (CV GRSs) for predicting CAD and MACE and tested their early-life screening potential by comparing against the CAD GRS only.

METHODS

We used data from 379 581 participants in the UK Biobank without known cardiovascular conditions (follow-up, 11.3 years; 3.3% CAD cases and 5.2% MACE cases). In a training subset (50%) we built 3 scores: QRISK3; QRISK3 and an established CAD GRS; and QRISK3, the CAD GRS and the CV GRSs. In an independent subset (50%), we evaluated each score's performance using the concordance index, odds ratio and net reclassification index. We then repeated the analyses without considering QRISK3.

RESULTS

For CAD, the combination of QRISK3 and the CAD GRS had a better performance than QRISK3 alone (concordance index, 0.766 versus 0.753; odds ratio, 5.47 versus 4.82; net reclassification index, 7.7%). Adding the CV GRSs did not significantly improve risk stratification. When only looking at genetic information, the combination of CV GRSs and the CAD GRS had a better performance than the CAD GRS alone (concordance index, 0.637 versus 0.625; odds ratio, 2.17 versus 2.07; net reclassification index, 3.3%). Similar results were obtained for MACE.

CONCLUSIONS

In individuals without known cardiovascular disease, the inclusion of CV GRSs to a clinical tool and an established CAD GRS does not improve CAD or MACE risk stratification. However, their combination only with the CAD GRS increases prediction performance indicating potential use in early-life screening before the advanced development of conventional cardiovascular risk factors.

ECG T-Wave Morphologic Variations Predict Ventricular Arrhythmic Risk in Low- and Moderate-Risk Populations

Background Early identification of individuals at risk of sudden cardiac death (SCD) remains a major challenge. The ECG is a simple, common test, with potential for large-scale application. We developed and tested the predictive value of a novel index quantifying T-wave morphologic variations with respect to a normal reference (TMV), which only requires one beat and a single-lead ECG. Methods and Results We obtained reference T-wave morphologies from 23 962 participants in the UK Biobank study. With Cox models, we determined the association between TMV and life-threatening ventricular arrhythmia in an independent data set from UK Biobank study without a history of cardiovascular events (N=51 794; median follow-up of 122 months) and SCD in patients with coronary artery disease from ARTEMIS (N=1872; median follow-up of 60 months). In UK Biobank study, 220 (0.4%) individuals developed life-threatening ventricular arrhythmias. TMV was significantly associated with life-threatening ventricular arrhythmias (hazard ratio [HR] of 1.13 per SD increase [95% CI, 1.03-1.24]; P=0.009). In ARTEMIS, 34 (1.8%) individuals reached the primary end point. Patients with TMV ≥5 had an HR for SCD of 2.86 (95% CI, 1.40-5.84; P=0.004) with respect to those with TMV <5, independently from QRS duration, corrected QT interval, and left ventricular ejection fraction. TMV was not significantly associated with death from a cause other than SCD. Conclusions TMV identifies individuals at life-threatening ventricular arrhythmia and SCD risk using a single-beat single-lead ECG, enabling inexpensive, quick, and safe risk assessment in large populations.

Does the use of proton pump inhibitors in children affect ventricular repolarisation parameters?

Proton pump inhibitors are widely used agents in the treatment of dyspepsia, and their effects on ventricular repolarisation through ion channels are well-known. Our aim is to evaluate the change in ventricular repolarisation parameters on electrocardiogram before and after proton pump inhibitor treatment. This study included 69 patients who had symptoms such as burning stomach pain, bloating, nausea, and heartburn for at least 3 months. Electrolyte levels of the patients were measured before and after treatment, and 12-lead electrocardiograms were taken at the initial and 1st month follow-up visit. Heart rate, QT interval, corrected QT (QTc), QT dispersion (QTd), QTc dispersion (QTcd), Tp-e measurements, and Tp-e/QT ratio were calculated and compared. Thirty-nine of the patients were girls, 30 were boys, and the mean age was 13.16 ± 3.02 years. Electrolyte levels of the patients before and after treatment were within the normal range. There was no statistically significant difference in the QTc, the Tp-e duration, or the Tp-e/QT ratio of the patients before and after treatment. We did not find a significant prolongation in the QTc duration or any other ventricular repolarisation parameters after proton pump inhibitor treatment in children with dyspepsia. We did not observe ventricular arrhythmia in our patients during follow-up. However, different results might be obtained with a larger sample and a longer follow-up period. These patients may have an increased risk of developing ventricular arrhythmias. Therefore, precaution should be taken when using drugs that prolong the QT period, and follow-up with serial electrocardiograms should be planned.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Cardiovascular waveforms - can we extract more from routine signals?

Cardiovascular waveforms such as blood pressure, ECG and photoplethysmography (PPG), are routinely acquired by specialised monitoring devices. Such devices include bedside monitors, wearables and radiotelemetry which sample at very high fidelity, yet most of this numerical data is disregarded and focus tends to reside on single point averages such as the maxima, minima, amplitude, rate and intervals. Whilst, these measures are undoubtedly of value, we may be missing important information by simplifying the complex waveform signal in this way. This Special Collection showcases recent advances in the appraisal of routine signals. Ultimately, such approaches and technologies may assist in improving the accuracy and sensitivity of detecting physiological change. This, in turn, may assist with identifying efficacy or safety signals for investigational new drugs or aidpatient diagnosis and management, supporting scientific and clinical decision making.

Genomic and pleiotropic analyses of resting QT interval identifies novel loci and overlap with atrial electrical disorders

The resting QT interval, an electrocardiographic (ECG) measure of ventricular myocardial repolarization, is a heritable risk marker of cardiovascular mortality, but the mechanisms remain incompletely understood. Previously reported candidate genes have provided insights into the regulatory mechanisms of the QT interval. However, there are still important knowledge gaps. We aimed to gain new insights by (i) providing new candidate genes, (ii) identifying pleiotropic associations with other cardiovascular traits, and (iii) scanning for sexually dimorphic genetic effects. We conducted a genome-wide association analysis for resting QT interval with ~9.8 million variants in 52 107 individuals of European ancestry without known cardiovascular disease from the UK Biobank. We identified 40 loci, 13 of which were novel, including 2 potential sex-specific loci, explaining ~11% of the trait variance. Candidate genes at novel loci were involved in myocardial structure and arrhythmogenic cardiomyopathy. Investigation of pleiotropic effects of QT interval variants using phenome-wide association analyses in 302 000 unrelated individuals from the UK Biobank and pairwise genome-wide comparisons with other ECG and cardiac imaging traits revealed genetic overlap with atrial electrical pathology. These findings provide novel insights into how abnormal myocardial repolarization and increased cardiovascular mortality may be linked.

Analysing electrocardiographic traits and predicting cardiac risk in UK biobank

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.