Genome-Wide Associations of Global Electrical Heterogeneity ECG Phenotype: The ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study)

Single Nucleotide Variants (SNVs) of the Mesocorticolimbic System Associated with Cardiovascular Diseases and Type 2 Diabetes: A Systematic Review

The mesocorticolimbic (MCL) system is crucial in developing risky health behaviors which lead to cardiovascular diseases (CVDs) and type 2 diabetes (T2D). Although there is some knowledge of the MCL system genes linked to CVDs and T2D, a comprehensive list is lacking, underscoring the significance of this review. This systematic review followed PRISMA guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. The PubMed and Web of Science databases were searched intensively for articles related to the MCL system, single nucleotide variants (SNVs, formerly single nucleotide polymorphisms, SNPs), CVDs, T2D, and associated risk factors. Included studies had to involve a genotype with at least one MCL system gene (with an identified SNV) for all participants and the analysis of its link to CVDs, T2D, or associated risk factors. The quality assessment of the included studies was performed using the Q-Genie tool. The VEP and DAVID tools were used to annotate and interpret genetic variants and identify enriched pathways and gene ontology terms associated with the gene list. The review identified 77 articles that met the inclusion criteria. These articles provided information on 174 SNVs related to the MCL system that were linked to CVDs, T2D, or associated risk factors. The COMT gene was found to be significantly related to hypertension, dyslipidemia, insulin resistance, obesity, and drug abuse, with rs4680 being the most commonly reported variant. This systematic review found a strong association between the MCL system and the risk of developing CVDs and T2D, suggesting that identifying genetic variations related to this system could help with disease prevention and treatment strategies.

Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms

BACKGROUND

Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial fibrillation (AF), a heritable and morbid arrhythmia. However, the factors forming the basis of risk predictions from AI models are usually not well understood. We hypothesized that there might be a genetic basis for an AI algorithm for predicting the 5-year risk of new-onset AF using 12-lead ECGs (ECG-AI)-based risk estimates.

METHODS

We applied a validated ECG-AI model for predicting incident AF to ECGs from 39 986 UK Biobank participants without AF. We then performed a genome-wide association study (GWAS) of the predicted AF risk and compared it with an AF GWAS and a GWAS of risk estimates from a clinical variable model.

RESULTS

In the ECG-AI GWAS, we identified 3 signals (P<5×10-8) at established AF susceptibility loci marked by the sarcomeric gene TTN and sodium channel genes SCN5A and SCN10A. We also identified 2 novel loci near the genes VGLL2 and EXT1. In contrast, the clinical variable model prediction GWAS indicated a different genetic profile. In genetic correlation analysis, the prediction from the ECG-AI model was estimated to have a higher correlation with AF than that from the clinical variable model.

CONCLUSIONS

Predicted AF risk from an ECG-AI model is influenced by genetic variation implicating sarcomeric, ion channel and body height pathways. ECG-AI models may identify individuals at risk for disease via specific biological pathways.

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.

Digitizing ECG image: A new method and open-source software code

BACKGROUND AND OBJECTIVE

We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads.

METHODS

We used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis.

RESULTS

The sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9-13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρ_c 0.97(95% confidence interval [CI] 0.95-0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2-30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρ_c 0.90(95%CI 0.82-0.95)].

CONCLUSIONS

We developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.

Intermittent fasting and caloric restriction interact with genetics to shape physiological health in mice

Dietary interventions can dramatically affect physiological health and organismal lifespan. The degree to which organismal health is improved depends upon genotype and the severity of dietary intervention, but neither the effects of these factors, nor their interaction, have been quantified in an outbred population. Moreover, it is not well understood what physiological changes occur shortly after dietary change and how these may affect the health of an adult population. In this article, we investigated the effect of 6-month exposure of either caloric restriction (CR) or intermittent fasting (IF) on a broad range of physiological traits in 960 1-year old Diversity Outbred mice. We found CR and IF affected distinct aspects of physiology and neither the magnitude nor the direction (beneficial or detrimental) of effects were concordant with the severity of the intervention. In addition to the effects of diet, genetic variation significantly affected 31 of 36 traits (heritabilities ranged from 0.04 to 0.65). We observed significant covariation between many traits that was due to both diet and genetics and quantified these effects with phenotypic and genetic correlations. We genetically mapped 16 diet-independent and 2 diet-dependent significant quantitative trait loci, both of which were associated with cardiac physiology. Collectively, these results demonstrate the degree to which diet and genetics interact to shape the physiological health of adult mice following 6 months of dietary intervention.

Reproducibility of global electrical heterogeneity measurements on 12-lead ECG: The Multi-Ethnic Study of Atherosclerosis

OBJECTIVE

Vectorcardiographic (VCG) global electrical heterogeneity (GEH) metrics showed clinical usefulness. We aimed to assess the reproducibility of GEH metrics.

METHODS

GEH was measured on two 10-s 12‑lead ECGs recorded on the same day in 4316 participants of the Multi-Ethnic Study of Atherosclerosis (age 69.4 ± 9.4 y; 2317(54%) female, 1728 (40%) white, 1138(26%) African-American, 519(12%) Asian-American, 931(22%) Hispanic-American). GEH was measured on a median beat, comprised of the normal sinus (N), atrial fibrillation/flutter (S), and ventricular-paced (VP) beats. Spatial ventricular gradient's (SVG's) scalar was measured as sum absolute QRST integral (SAIQRST) and vector magnitude QT integral (VMQTi).

RESULTS

Two N ECGs with heart rate (HR) bias of -0.64 (95% limits of agreement [LOA] -5.68 to 5.21) showed spatial area QRS-T angle (aQRST) bias of -0.12 (95%LOA -14.8 to 14.5). Two S ECGs with HR bias of 0.20 (95%LOA -15.8 to 16.2) showed aQRST bias of 1.37 (95%LOA -33.2 to 35.9). Two VP ECGs with HR bias of 0.25 (95%LOA -3.0 to 3.5) showed aQRST bias of -1.03 (95%LOA -11.9 to 9.9). After excluding premature atrial or ventricular beat and two additional beats (before and after extrasystole), the number of cardiac beats included in a median beat did not affect the GEH reproducibility. Mean-centered log-transformed values of SAIQRST and VMQTi demonstrated perfect agreement (Bias 0; 95%LOA -0.092 to 0.092).

CONCLUSION

GEH measurements on N, S, and VP median beats are reproducible. SVG's scalar can be measured as either SAIQRST or VMQTi.

SIGNIFICANCE

Satisfactory reproducibility of GEH metrics supports their implementation.

Exome sequencing in patient-parent trios suggests new candidate genes for early-onset primary sclerosing cholangitis

BACKGROUND & AIMS

Primary sclerosing cholangitis (PSC) is a rare bile duct disease strongly associated with inflammatory bowel disease (IBD). Whole-exome sequencing (WES) has contributed to understanding the molecular basis of very early-onset IBD, but rare protein-altering genetic variants have not been identified for early-onset PSC. We performed WES in patients diagnosed with PSC ≤ 12 years to investigate the contribution of rare genetic variants to early-onset PSC.

METHODS

In this multicentre study, WES was performed on 87 DNA samples from 29 patient-parent trios with early-onset PSC. We selected rare (minor allele frequency < 2%) coding and splice-site variants that matched recessive (homozygous and compound heterozygous variants) and dominant (de novo) inheritance in the index patients. Variant pathogenicity was predicted by an in-house developed algorithm (GAVIN), and PSC-relevant variants were selected using gene expression data and gene function.

RESULTS

In 22 of 29 trios we identified at least 1 possibly pathogenic variant. We prioritized 36 genes, harbouring a total of 54 variants with predicted pathogenic effects. In 18 genes, we identified 36 compound heterozygous variants, whereas in the other 18 genes we identified 18 de novo variants. Twelve of 36 candidate risk genes are known to play a role in transmembrane transport, adaptive and innate immunity, and epithelial barrier function.

CONCLUSIONS

The 36 candidate genes for early-onset PSC need further verification in other patient cohorts and evaluation of gene function before a causal role can be attributed to its variants.

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

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Inaccuracies of QRS and T-wave markers significantly impact QRS-Ta estimation.

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These errors influence the classification of clinically relevant abnormal values.

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Our algorithm provides robust measurements in the presence of inaccurate VCG markers.

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We present for the first time, the distribution of the QRS-Ta in a large cohort.

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 <80% and <65% respectively, when QRS-onset was delayed or QRS-offset anticipated >15 ms. Using our proposed algorithm, MAE for peak QRS-Ta were reduced to <4% and sensitivity and precision of abnormality were >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.

Sex differences in vectorcardiogram of African-Americans with and without cardiovascular disease: a cross-sectional study in the Jackson Heart Study cohort

OBJECTIVES

We hypothesised that (1) the prevalent cardiovascular disease (CVD) is associated with global electrical heterogeneity (GEH) after adjustment for demographic, anthropometric, socioeconomic and traditional cardiovascular risk factors, (2) there are sex differences in GEH and (3) sex modifies an association of prevalent CVD with GEH.

DESIGN

Cross-sectional, cohort study.

SETTING

Prospective African-American The Jackson Heart Study (JHS) with a nested family cohort in 2000-2004 enrolled residents of the Jackson, Mississippi metropolitan area.

PARTICIPANTS

Participants from the JHS with analysable ECGs recorded in 2009-2013 (n=3679; 62±12 y; 36% men; 863 family units). QRS, T and spatial ventricular gradient (SVG) vectors' magnitude and direction, spatial QRS-T angle and sum absolute QRST integral (SAI QRST) were measured.

OUTCOME

Prevalent CVD was defined as the history of (1) coronary heart disease defined as diagnosed/silent myocardial infarction, or (2) revascularisation procedure defined as prior coronary/peripheral arterial revascularisation, or (3) carotid angioplasty/carotid endarterectomy, or (4) stroke.

RESULTS

In adjusted mixed linear models, women had a smaller spatial QRS-T angle (-12.2 (95% CI -19.4 to -5.1)°; p=0.001) and SAI QRST (-29.8 (-39.3 to -20.3) mV*ms; p<0.0001) than men, but larger SVG azimuth (+16.2(10.5-21.9)°; p<0.0001), with a significant random effect between families (+20.8 (8.2-33.5)°; p=0.001). SAI QRST was larger in women with CVD as compared with CVD-free women or men (+15.1 (3.8-26.4) mV*ms; p=0.009). Men with CVD had a smaller T area (by 5.1 (95% CI 1.2 to 9.0) mV*ms) and T peak magnitude (by 44 (95%CI 16 to 71) µV) than CVD-free men. T vectors pointed more posteriorly in women as compared with men (peak T azimuth + 17.2(8.9-25.6)°; p<0.0001), with larger sex differences in T azimuth in some families by +26.3(7.4-45.3)°; p=0.006.

CONCLUSIONS

There are sex differences in the electrical signature of CVD in African-American men and women. There is a significant effect of unmeasured genetic and environmental factors on cardiac repolarisation.

[Diagnostic and prognostic significance of QRS-T angle]

The angle between theQRSandTvectors reflects the consistency or inconsistency of the processes of de- and repolarization of the ventricles of the heart and is considered one of the indicators of global electrical heterogeneity of myocardium. In recent years, the prognostic value of theQRS-Tangle has been demonstrated in relation to total and cardiovascular mortality, both in the population and in various groups of patients. The mechanisms of this phenomenon are not completely clear. The review analyses studies published over the past five years on the relationship between theQRS-Tangle and mortality, as well as coronary heart disease and heart failure. Possible mechanisms for increasing theQRS-Tangle are discussed. Data are given on the use of theQRS-Tangle in diagnostic and prognostic scales, including in combination with other indicators of global electrical heterogeneity of myocardium.

Kir2.1 Interactome Mapping Uncovers PKP4 as a Modulator of the Kir2.1-Regulated Inward Rectifier Potassium Currents

Kir2.1, a strong inward rectifier potassium channel encoded by the KCNJ2 gene, is a key regulator of the resting membrane potential of the cardiomyocyte and plays an important role in controlling ventricular excitation and action potential duration in the human heart. Mutations in KCNJ2 result in inheritable cardiac diseases in humans, e.g. the type-1 Andersen-Tawil syndrome (ATS1). Understanding the molecular mechanisms that govern the regulation of inward rectifier potassium currents by Kir2.1 in both normal and disease contexts should help uncover novel targets for therapeutic intervention in ATS1 and other Kir2.1-associated channelopathies. The information available to date on protein-protein interactions involving Kir2.1 channels remains limited. Additional efforts are necessary to provide a comprehensive map of the Kir2.1 interactome. Here we describe the generation of a comprehensive map of the Kir2.1 interactome using the proximity-labeling approach BioID. Most of the 218 high-confidence Kir2.1 channel interactions we identified are novel and encompass various molecular mechanisms of Kir2.1 function, ranging from intracellular trafficking to cross-talk with the insulin-like growth factor receptor signaling pathway, as well as lysosomal degradation. Our map also explores the variations in the interactome profiles of Kir2.1WTversus Kir2.1Δ314-315, a trafficking deficient ATS1 mutant, thus uncovering molecular mechanisms whose malfunctions may underlie ATS1 disease. Finally, using patch-clamp analysis, we validate the functional relevance of PKP4, one of our top BioID interactors, to the modulation of Kir2.1-controlled inward rectifier potassium currents. Our results validate the power of our BioID approach in identifying functionally relevant Kir2.1 interactors and underline the value of our Kir2.1 interactome as a repository for numerous novel biological hypotheses on Kir2.1 and Kir2.1-associated diseases.

Global electrical heterogeneity associated with drug-induced torsades de pointes

BACKGROUND

Drugs belonging to diverse therapeutic classes can prolong myocardial refractoriness or slow conduction. These drugs may be effective and well-tolerated, but the risk of sudden cardiac death from torsades de pointes (TdP) remains a major concern. The corrected QT interval has significant limitations when used for risk stratification. Measurement of global electrical heterogeneity (GEH) could help identify the substrate vulnerable to drug-induced ventricular arrhythmias.

OBJECTIVE

The purpose of this study was to improve risk stratification for drug-induced TdP by measuring GEH on the electrocardiogram (ECG).

METHODS

We analyzed ECG data from a case-control study of patients with a history of drug-induced TdP as well as age- and sex-matched controls. Vectorcardiograms were constructed from ECGs. GEH was measured via the spatial ventricular gradient (SVG) vector (magnitude, azimuth, and elevation). Log odds coefficients for TdP were estimated using multivariable logistic regression.

RESULTS

Among 17 cases (47% male; age 58.9 ± 12.5 years) and 17 controls (29% male; age 61.0 ± 12.2 years), 34 ECGs were analyzed. SVG azimuth was significantly different between cases and controls (3.4 vs 22.0 degrees, respectively; P = 0.02). After adjusting for sex and QTc interval, odds of TdP increased by a factor of 3.2 for each 1 SD change in SVG azimuth from the control group mean (95% confidence interval 1.07-9.14; P = .04). QTc was not significant in the multivariable analysis (P = .20).

CONCLUSION

SVG azimuth is correlated with a history of drug-induced TdP independent of QTc. GEH measurement may help identify patients at high risk for drug-induced arrhythmias.

Bringing Critical Race Praxis Into the Study of Electrophysiological Substrate of Sudden Cardiac Death: The ARIC Study

Background Race is an established risk factor for sudden cardiac death (SCD). We sought to determine whether the association of electrophysiological substrate with SCD varies between black and white individuals. Methods and Results Participants from the ARIC (Atherosclerosis Risk in Communities) study with analyzable ECGs (n=14 408; age, 54±6 years; 74% white) were included. Electrophysiological substrate was characterized by ECG metrics. Two competing outcomes were adjudicated: SCD and non-SCD. Interaction of ECG metrics with race was studied in Cox proportional hazards and Fine-Gray competing risk models, adjusted for prevalent cardiovascular disease, risk factors, and incident nonfatal cardiovascular disease. At the baseline visit, adjusted for age, sex, and study center, blacks had larger spatial ventricular gradient magnitude (0.30 mV; 95% CI, 0.25-0.34 mV), sum absolute QRST integral (18.4 mV*ms; 95% CI, 13.7-23.0 mV*ms), and Cornell voltage (0.30 mV; 95% CI, 0.25-0.35 mV) than whites. Over a median follow-up of 24.4 years, SCD incidence was higher in blacks (2.86 per 1000 person-years; 95% CI, 2.50-3.28 per 1000 person-years) than whites (1.37 per 1000 person-years; 95% CI, 1.22-1.53 per 1000 person-years). Blacks with hypertension had the highest rate of SCD: 4.26 (95% CI, 3.66-4.96) per 1000 person-years. Race did not modify an association of ECG variables with SCD, except QRS-T angle. Spatial QRS-T angle was associated with SCD in whites (hazard ratio, 1.38; 95% CI, 1.25-1.53) and hypertension-free blacks (hazard ratio, 1.52; 95% CI, 1.09-2.12), but not in blacks with hypertension (hazard ratio, 1.15; 95% CI, 0.99-1.32) (P-interaction=0.004). Conclusions Race did not modify associations of electrophysiological substrate with SCD and non-SCD. Electrophysiological substrate does not explain racial disparities in SCD rate.

Dynamic predictive accuracy of electrocardiographic biomarkers of sudden cardiac death within a survival framework: the Atherosclerosis Risk in Communities (ARIC) study

BACKGROUND

The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD).

METHODS

Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n = 15,716; 55% female, 73% white, age 54.2 ± 5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was the competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using a survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured.

RESULTS

Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303-0.75). SVG elevation more accurately predicted SCD if the ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526-0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515-0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% of SCD events were reclassified from low or intermediate risk to a high-risk category. QRS-T angle was the strongest long-term predictor of SCD (AUC 0.710; 95%CI 0.668-0.753 for ECG recorded within 10 years before SCD).

CONCLUSION

Short-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.

Changes in global electrical heterogeneity associated with dofetilide, quinidine, ranolazine, and verapamil

BACKGROUND

Electrocardiographic (ECG) markers of antiarrhythmic drug (AAD) activity could be used to optimize efficacy and minimize toxicity. Vectorcardiographic global electrical heterogeneity (GEH) is associated with ventricular arrhythmias and sudden death, but it is unclear how GEH measurements change in response to AADs.

OBJECTIVE

The purpose of this study was to characterize acute effects of AADs on GEH measurements.

METHODS

We analyzed double-blind placebo-controlled trial data from healthy volunteers given 1 dose of placebo, dofetilide, quinidine, ranolazine, or verapamil on subsequent visits. Serial ECGs and plasma drug concentrations were collected. Vectorcardiographic GEH parameters (spatial ventricular gradient [SVG], spatial QRST angle, sum absolute QRST integral, and SVG-QRS peak angle) were measured. Placebo-corrected change from baseline was regressed on drug concentration stratified by sex using linear mixed effects models.

RESULTS

Among 22 persons (11 (50%) male median age 27 ± 5 years), 5232 ECGs were analyzed. Dofetilide and quinidine were associated with significant changes in more GEH parameters (5) compared with verapamil (2) and ranolazine (1). The most notable change occurred in SVG azimuth, with largest changes (degrees per unit normalized drug concentration) in dofetilide (6.1; 95% confidence interval [CI] 4.2-8.0) and quinidine (9.4; 95% CI 6.7-12.0), and smaller effects in verapamil (4.4; 95% CI 2.9-5.9) and ranolazine (5.4; 95% CI 3.5-7.3). AAD-induced GEH changes significantly differed in men and women.

CONCLUSION

AADs change GEH measurements. These changes, which differ by sex, are likely driven by alterations in ion channel function and dispersion of depolarization or repolarization. GEH measurement may allow early assessment of favorable or adverse AAD effects.

Into the Wild: GWAS Exploration of Non-coding RNAs

Genome-wide association studies (GWAS) have proven a fundamental tool to identify common variants associated to complex traits, thus contributing to unveil the genetic components of human disease. Besides, the advent of GWAS contributed to expose unexpected findings that urged to redefine the framework of population genetics. First, loci identified by GWAS had small effect sizes and could only explain a fraction of the predicted heritability of the traits under study. Second, the majority of GWAS hits mapped within non-coding regions (such as intergenic or intronic regions) where new functional RNA species (such as lncRNAs or circRNAs) have started to emerge. Bigger cohorts, meta-analysis and technical improvements in genotyping allowed identification of an increased number of genetic variants associated to coronary artery disease (CAD) and cardiometabolic traits. The challenge remains to infer causal mechanisms by which these variants influence cardiovascular disease development. A tendency to assign potential causal variants preferentially to coding genes close to lead variants contributed to disregard the role of non-coding elements. In recent years, in parallel to an increased knowledge of the non-coding genome, new studies started to characterize disease-associated variants located within non-coding RNA regions. The upcoming of databases integrating single-nucleotide polymorphisms (SNPs) and non-coding RNAs together with novel technologies will hopefully facilitate the discovery of causal non-coding variants associated to disease. This review attempts to summarize the current knowledge of genetic variation within non-coding regions with a focus on long non-coding RNAs that have widespread impact in cardiometabolic diseases.

Vectorcardiogram in athletes: The Sun Valley Ski Study

BACKGROUND

Global electrical heterogeneity (GEH) is associated with sudden cardiac death (SCD) in adults of 45 years and above. However, GEH has not been previously measured in young athletes. The goal of this study was to establish a reference for vectorcardiograpic (VCG) metrics in male and female athletes.

METHODS

Skiers (n = 140; mean age 19.2 ± 3.5 years; 66% male, 94% white; 53% professional athletes) were enrolled in a prospective cohort. Resting 12-lead ECGs were interpreted per the International ECG criteria. Associations of age, sex, and athletic performance with GEH were studied.

RESULTS

In age and training level-adjusted analyses, male sex was associated with a larger T vector [T peak magnitude +186 (95% CI 106-266) µV] and a wider spatial QRS-T angle [+28.2 (17.3-39.2)°] as compared to women. Spatial QRS-T angle in the ECG left ventricular hypertrophy (LVH) voltage group (n = 21; 15%) and normal ECG group did not differ (67.7 ± 25.0 vs. 66.8 ± 28.2; p = 0.914), suggesting that ECG LVH voltage in athletes reflects physiological remodeling. In contrast, skiers with right ventricular hypertrophy (RVH) voltage (n = 26, 18.6%) had wider QRS-T angle (92.7 ± 29.6 vs. 66.8 ± 28.2°; p = 0.001), larger SAI QRST (194.9 ± 30.2 vs. 157.8 ± 42.6 mV × ms; p < 0.0001), but similar peak SVG vector magnitude (1976 ± 548 vs. 1939 ± 395 µV; p = 0.775) as compared to the normal ECG group. Better athletic performance was associated with the narrower QRS-T angle. Each 10% worsening in an athlete's Federation Internationale de' Ski downhill ranking percentile was associated with an increase in spatial QRS-T angle by 2.1 (95% CI 0.3-3.9) degrees (p = 0.013).

CONCLUSION

Vectorcardiograpic adds nuances to ECG phenomena in athletes.

The Reproducibility of Global Electrical Heterogeneity ECG Measurements

BACKGROUND

Global electrical heterogeneity (GEH) is a useful predictor of adverse clinical outcomes. However, reproducibility of GEH measurements on 10-second routine clinical ECG is unknown.

METHODS

Data of the prospective cohort study of incident hemodialysis patients (n=253; mean age 54.6±13.5y; 56% male; 79% African American) were analysed. Two random 10-second segments of 5-minute ECG recording in sinus rhythm were compared. GEH was measured as spatial QRS-T angle, spatial ventricular gradient (SVG) magnitude and direction (azimuth and elevation), and a scalar value of SVG measured by (1) sum absolute QRST integral (SAI QRST), and (2) QT integral on vector magnitude signal (iVM_QT). Bland-Altman analysis was used to calculate agreement.

RESULTS

For all studied vectorcardiographic metrics, agreement was substantial (Lin's concordance coefficient >0.98), and precision was perfect (>99.99%). 95% limits of agreement were ±14° for spatial QRS-T angle, ±13° for SVG azimuth, ±4° for SVG elevation, ±14 mV*ms for SVG magnitude, and ±17 mV*ms for SAI QRST. SAI QRST and iVM_QT were in substantial agreement with each other.

CONCLUSION

Reproducibility of a 10-second automated GEH ECG measurements was substantial, and precision was perfect.

Global Electrical Heterogeneity: Mechanisms and Clinical Significance

This review summarizes recent findings and discusses a clinical significance of a vectorcardiographic (VCG) Global electrical heterogeneity (GEH). GEH concept is based on the concept of the spatial ventricular gradient (SVG), which is a global measure of the dispersion of total recovery time. We quantify GEH by measuring five features of the SVG vector (SVG magnitude, direction (azimuth and elevation), a scalar value, and spatial QRS-T angle) on orthogonal XYZ ECG. In analysis of more than 20,000 adults we showed that GEH is independently associated with sudden cardiac death (SCD) after adjustment for demographics, cardiovascular disease (time-updated incident non-fatal cardiovascular events [coronary heart disease, heart failure, stroke, atrial fibrillation, use of beta-blockers], and known risk factors [cholesterol, triglycerides, physical activity index, smoking, diabetes, obesity, hypertension, anti-hypertensive medications, creatinine, alcohol intake, left ventricular ejection fraction, and time-updated ECG metrics (heart rate, QTc, QRS duration, ECG-left ventricular hypertrophy, bundle branch block or interventricular conduction delay)]. This finding suggests that GEH represents an independent electrophysiological substrate of SCD.