Corrected QT Interval–Polygenic Risk Score and Its Contribution to Type 1, Type 2, and Type 3 Long-QT Syndrome in Probands and Genotype-Positive Family Members

Unraveling Complexities in Genetically Elusive Long QT Syndrome

Genetic testing has become standard of care for patients with long QT syndrome (LQTS), providing diagnostic, prognostic, and therapeutic information for both probands and their family members. However, up to a quarter of patients with LQTS do not have identifiable Mendelian pathogenic variants in the currently known LQTS-associated genes. This absence of genetic confirmation, intriguingly, does not lessen the severity of LQTS, with the prognosis in these gene-elusive patients with unequivocal LQTS mirroring genotype-positive patients in the limited data available. Such a conundrum instigates an exploration into the causes of corrected QT interval (QTc) prolongation in these cases, unveiling a broad spectrum of potential scenarios and mechanisms. These include multiple environmental influences on QTc prolongation, exercise-induced repolarization abnormalities, and the profound implications of the constantly evolving nature of genetic testing and variant interpretation. In addition, the rapid advances in genetics have the potential to uncover new causal genes, and polygenic risk factors may aid in the diagnosis of high-risk patients. Navigating this multifaceted landscape requires a systematic approach and expert knowledge, integrating the dynamic nature of genetics and patient-specific influences for accurate diagnosis, management, and counseling of patients. The role of a subspecialized expert cardiogenetic clinic is paramount in evaluation to navigate this complexity. Amid these intricate aspects, this review outlines potential causes of gene-elusive LQTS. It also provides an outline for the evaluation of patients with negative and inconclusive genetic test results and underscores the need for ongoing adaptation and reassessment in our understanding of LQTS, as the complexities of gene-elusive LQTS are increasingly deciphered.

Genetic QT Score and Sleep Apnea as Predictors of Sudden Cardiac Death in the UK Biobank

Introduction

The goal of this study was to evaluate the association between a polygenic risk score (PRS) for QT prolongation (QTc-PRS), QTc intervals and mortality in patients enrolled in the UK Biobank with and without sleep apnea.

Methods

The QTc-PRS was calculated using allele copy number and previously reported effect estimates for each single nuclear polymorphism SNP. Competing-risk regression models adjusting for age, sex, BMI, QT prolonging medication, race, and comorbid cardiovascular conditions were used for sudden cardiac death (SCD) analyses.

Results

500,584 participants were evaluated (56.5 ±8 years, 54% women, 1.4% diagnosed with sleep apnea). A higher QTc-PRS was independently associated with the increased QTc interval duration (p<0.0001). The mean QTc for the top QTc-PRS quintile was 15 msec longer than the bottom quintile (p<0.001). Sleep apnea was found to be an effect modifier in the relationship between QTc-PRS and SCD. The adjusted HR per 5-unit change in QTc-PRS for SCD was 1.64 (95% CI 1.16 - 2.31, p=0.005) among those with sleep apnea and 1.04 (95% CI 0.95 - 1.14, p=0.44) among those without sleep apnea (p for interaction =0.01). Black participants with sleep apnea had significantly elevated adjusted risk of SCD compared to White participants (HR=9.6, 95% CI 1.24 - 74, p=0.03).

Conclusion

In the UK Biobank population, the QTc-PRS was associated with SCD among participants with sleep apnea but not among those without sleep apnea, indicating that sleep apnea is a significant modifier of the genetic risk. Black participants with sleep apnea had a particularly high risk of SCD.

The Role of Genetics in the Management of Heart Failure Patients

Over the last decades, the relevance of genetics in cardiovascular diseases has expanded, especially in the context of cardiomyopathies. Its relevance extends to the management of patients diagnosed with heart failure (HF), given its capacity to provide invaluable insights into the etiology of cardiomyopathies and identify individuals at a heightened risk of poor outcomes. Notably, the identification of an etiological genetic variant necessitates a comprehensive evaluation of the family lineage of the affected patients. In the future, these genetic variants hold potential as therapeutic targets with the capability to modify gene expression. In this complex setting, collaboration among cardiologists, specifically those specializing in cardiomyopathies and HF, and geneticists becomes paramount to improving individual and family health outcomes, as well as therapeutic clinical results. This review is intended to offer geneticists and cardiologists an updated perspective on the value of genetic research in HF and its implications in clinical practice.

Genetics of congenital arrhythmia syndromes: the challenge of variant interpretation

Congenital arrhythmia syndromes are rare genetic disorders that can cause a high risk of sudden cardiac death. Expert panels have affirmed 15 genes that are linked to congenital arrhythmias. These genes mostly encode cardiac ion channel proteins or associated regulatory proteins that generate the cardiac action potential. Common genetic variation modulates the risk of rare variants and partially explains the incomplete penetrance of these disorders. As genetic testing becomes more prevalent, a major challenge is that most detected variants are annotated as variants of uncertain significance. This review will highlight emerging methods that are refining our understanding of arrhythmia genetics, including phenotype risk scores, large cohorts, in vitro functional assays, structural models, and computational predictions.

From diagnostic testing to precision medicine: the evolving role of genomics in cardiac channelopathies and cardiomyopathies in children

Pediatric sudden cardiac death (SCD) is the sudden unexpected death of a child or adolescent due to a presumed cardiac etiology. Heritable causes of pediatric SCD are predominantly cardiomyopathies and cardiac ion channelopathies. This review illustrates recent advances in determining the genetic cause of established and emerging channelopathies and cardiomyopathies, and how broader genomic sequencing is uncovering complex interactions between genetic architecture and disease manifestation. We discuss innovative models and experimental platforms for resolving the variant of uncertain significance as both the variants and genes associated with disease continue to evolve. Finally, we highlight the growing problem of incidentally identified variants in cardiovascular disease-causing genes and review innovative methods to determining whether these variants may ultimately result in penetrant disease. Overall, we seek to illustrate both the promise and inherent challenges in bridging the traditional role for genetics in diagnosing cardiomyopathies and channelopathies to one of true risk-predictive precision medicine.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Prolonged corrected QT interval in hospitalized patients with coronavirus disease 2019 in Dubai, United Arab Emirates: a single-center, retrospective study

OBJECTIVE

To evaluate the association of a prolonged corrected QT (QTc) interval in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its association with in-patient mortality.

METHODS

A cohort of 745 patients were recruited from a single center between 1 March 2020 and 31 May 2020. We analyzed the factors associated with a prolonged QTc and mortality.

RESULTS

A prolonged QTc interval >450 ms was found in 27% of patients admitted with SARS-CoV-2 infection. These patients were predominantly older, on a ventilator, and had hypertension, diabetes mellitus, or ischemic heart disease. They also had high troponin and D-dimer concentrations. A prolonged QTc interval had a significant association with the requirement of ventilator support and was associated with an increased odds of mortality. Patients who died were older than 55 years, and had high troponin, D-dimer, creatinine, procalcitonin, and ferritin concentrations, a high white blood cell count, and abnormal potassium concentrations (hypo- or hyperkalemia).

CONCLUSIONS

A prolonged QTc interval is common in patients with SARS-CoV-2 infection and it is associated with worse outcomes. Older individuals and those with comorbidities should have an electrocardiogram performed, which is noninvasive and easily available, on admission to hospital to identify high-risk patients.

Genetics and genomics of arrhythmic risk: current and future strategies to prevent sudden cardiac death

A genetic risk of sudden cardiac arrest and sudden death due to an arrhythmic cause, known as sudden cardiac death (SCD), has become apparent from epidemiological studies in the general population and in patients with ischaemic heart disease. However, genetic susceptibility to sudden death is greatest in young people and is associated with uncommon, monogenic forms of heart disease. Despite comprehensive pathology and genetic evaluations, SCD remains unexplained in a proportion of young people and is termed sudden arrhythmic death syndrome, which poses challenges to the identification of relatives from affected families who might be at risk of SCD. In this Review, we assess the current understanding of the epidemiology and causes of SCD and evaluate both the monogenic and the polygenic contributions to the risk of SCD in the young and SCD associated with drug therapy. Finally, we analyse the potential clinical role of genomic testing in the prevention of SCD in the general population.

Estimating the Posttest Probability of Long QT Syndrome Diagnosis for Rare KCNH2 Variants

BACKGROUND

The proliferation of genetic profiling has revealed many associations between genetic variations and disease. However, large-scale phenotyping efforts in largely healthy populations, coupled with DNA sequencing, suggest variants currently annotated as pathogenic are more common in healthy populations than previously thought. In addition, novel and rare variants are frequently observed in genes associated with disease both in healthy individuals and those under suspicion of disease. This raises the question of whether these variants can be useful predictors of disease. To answer this question, we assessed the degree to which the presence of a variant in the cardiac potassium channel gene KCNH2 was diagnostically predictive for the autosomal dominant long QT syndrome.

METHODS

We estimated the probability of a long QT diagnosis given the presence of each KCNH2 variant using Bayesian methods that incorporated variant features such as changes in variant function, protein structure, and in silico predictions. We call this estimate the posttest probability of disease. Our method was applied to over 4000 individuals heterozygous for 871 missense or in-frame insertion/deletion variants in KCNH2 and validated against a separate international cohort of 933 individuals heterozygous for 266 missense or in-frame insertion/deletion variants.

RESULTS

Our method was well-calibrated for the observed fraction of heterozygotes diagnosed with long QT syndrome. Heuristically, we found that the innate diagnostic information one learns about a variant from 3-dimensional variant location, in vitro functional data, and in silico predictors is equivalent to the diagnostic information one learns about that same variant by clinically phenotyping 10 heterozygotes. Most importantly, these data can be obtained in the absence of any clinical observations.

CONCLUSIONS

We show how variant-specific features can inform a prior probability of disease for rare variants even in the absence of clinically phenotyped heterozygotes.

Precision Medicine Approaches to Cardiac Arrhythmias: JACC Focus Seminar 4/5

In the initial 3 papers in this Focus Seminar series, the fundamentals and key concepts of precision medicine were reviewed, followed by a focus on precision medicine in the context of vascular disease and cardiomyopathy. For the remaining 2 papers, we focus on precision medicine in the context of arrhythmias. Specifically, in this fourth paper we focus on long QT syndrome, Brugada syndrome, and atrial fibrillation. The final (fifth) paper will deal with catecholaminergic polymorphic ventricular tachycardia. These arrhythmias represent a spectrum of disease ranging from common to relatively rare, with very different genetic and environmental causative factors, and with differing clinical manifestations that range from almost no consequences to lethality in childhood or adolescence if untreated. Accordingly, the emerging precision medicine approaches to these arrhythmias vary significantly, but several common themes include increased use of genetic testing, avoidance of triggers, and personalized risk stratification to guide the use of arrhythmia-specific therapies.

The Interface of Therapeutics and Genomics in Cardiovascular Medicine

Pharmacogenomics has a burgeoning role in cardiovascular medicine, from warfarin dosing to antiplatelet choice, with recent developments in sequencing bringing the promise of personalised medicine ever closer to the bedside. Further scientific evidence, real-world clinical trials, and economic modelling are needed to fully realise this potential. Additionally, tools such as polygenic risk scores, and results from Mendelian randomisation analyses, are only in the early stages of clinical translation and merit further investigation. Genetically targeted rational drug design has a strong evidence base and, due to the nature of genetic data, academia, direct-to-consumer companies, healthcare systems, and industry may meet in an unprecedented manner. Data sharing navigation may prove problematic. The present manuscript addresses these issues and concludes a need for further guidance to be provided to prescribers by professional bodies to aid in the consideration of such complexities and guide translation of scientific knowledge to personalised clinical action, thereby striving to improve patient care. Additionally, technologic infrastructure equipped to handle such large complex data must be adapted to pharmacogenomics and made user friendly for prescribers and patients alike.