Integration of genetic fine-mapping and multi-omics data reveals candidate effector genes for hypertension.

Genome-wide association studies of blood pressure (BP) have identified >1,000 loci, but the effector genes and biological pathways at these loci are mostly unknown. Using published association summary statistics, we conducted annotation-informed fine-mapping incorporating tissue-specific chromatin segmentation and colocalization to identify causal variants and candidate effector genes for systolic BP, diastolic BP, and pulse pressure. We observed 532 distinct signals associated with ≥2 BP traits and 84 with all three. For >20% of signals, a single variant accounted for >75% posterior probability, 65 were missense variants in known (SLC39A8, ADRB2, and DBH) and previously unreported BP candidate genes (NRIP1 and MMP14). In disease-relevant tissues, we colocalized >80 and >400 distinct signals for each BP trait with cis-eQTLs and regulatory regions from promoter capture Hi-C, respectively. Integrating mouse, human disorder, gene expression and tissue abundance data, and literature review, we provide consolidated evidence for 436 BP candidate genes for future functional validation and discover several potential drug targets.

Prognostic Significance of Different Ventricular Ectopic Burdens During Submaximal Exercise in Asymptomatic UK Biobank Subjects.

BACKGROUND: The consequences of exercise-induced premature ventricular contractions (PVCs) in asymptomatic individuals remain unclear. This study aimed to assess the association between PVC burdens during submaximal exercise and major adverse cardiovascular events (MI/HF/LTVA: myocardial infarction [MI], heart failure [HF], and life-threatening ventricular arrhythmia [LTVA]), and all-cause mortality. Additional end points were MI, LTVA, HF, and cardiovascular mortality. METHODS: A neural network was developed to count PVCs from ECGs recorded during exercise (6 minutes) and recovery (1 minute) in 48 315 asymptomatic participants from UK Biobank. Associations were estimated using multivariable Cox proportional hazard models. Explorative studies were conducted in subgroups with cardiovascular magnetic resonance imaging data (n=6290) and NT-proBNP (N-terminal Pro-B-type natriuretic peptide) levels (n=4607) to examine whether PVC burden was associated with subclinical cardiomyopathy. RESULTS: Mean age was 56.8±8.2 years; 51.1% of the participants were female; and median follow-up was 12.6 years. Low PVC counts during exercise and recovery were both associated with MI/HF/LTVA risk, independently of clinical factors: adjusted hazard ratio (HR), 1.2 (1-5 exercise PVCs, P<0.001) and HR, 1.3 (1-5 recovery PVCs, P<0.001). Risks were higher with increasing PVC count: HR, 1.8 (>20 exercise PVCs, P<0.001) and HR, 1.6 (>5 recovery PVCs, P<0.001). A similar trend was observed for all-cause mortality, although associations were only significant for high PVC burdens: HRs, 1.6 (>20 exercise PVCs, P<0.001) and 1.5 (>5 recovery PVCs, P<0.001). Complex PVC rhythms were associated with higher risk compared with PVC count alone. PVCs were also associated with incident HF, LTVA, and cardiovascular mortality, but not MI. In the explorative studies, high PVC burden was associated with larger left ventricular volumes, lower ejection fraction, and higher levels of NT-proBNP compared with participants without PVCs. CONCLUSIONS: In this cohort of middle-aged and older adults, PVC count during submaximal exercise and recovery were both associated with MI/HF/LTVA, all-cause mortality, HF, LTVAs, and cardiovascular mortality, independent of clinical and exercise test factors, indicating an incremental increase in risk as PVC count rises. Complex PVC rhythms were associated with higher risk compared with PVC count alone. Underlying mechanisms may include the presence of subclinical cardiomyopathy.

Fine mapping of candidate effector genes for heart rate.

An elevated resting heart rate (RHR) is associated with increased cardiovascular mortality. Genome-wide association studies (GWAS) have identified > 350 loci. Uniquely, in this study we applied genetic fine-mapping leveraging tissue specific chromatin segmentation and colocalization analyses to identify causal variants and candidate effector genes for RHR. We used RHR GWAS summary statistics from 388,237 individuals of European ancestry from UK Biobank and performed fine mapping using publicly available genomic annotation datasets. High-confidence causal variants (accounting for > 75% posterior probability) were identified, and we collated candidate effector genes using a multi-omics approach that combined evidence from colocalisation with molecular quantitative trait loci (QTLs), and long-range chromatin interaction analyses. Finally, we performed druggability analyses to investigate drug repurposing opportunities. The fine mapping pipeline indicated 442 distinct RHR signals. For 90 signals, a single variant was identified as a high-confidence causal variant, of which 22 were annotated as missense. In trait-relevant tissues, 39 signals colocalised with cis-expression QTLs (eQTLs), 3 with cis-protein QTLs (pQTLs), and 75 had promoter interactions via Hi-C. In total, 262 candidate genes were highlighted (79% had promoter interactions, 15% had a colocalised eQTL, 8% had a missense variant and 1% had a colocalised pQTL), and, for the first time, enrichment in nervous system pathways. Druggability analyses highlighted ACHE, CALCRL, MYT1 and TDP1 as potential targets. Our genetic fine-mapping pipeline prioritised 262 candidate genes for RHR that warrant further investigation in functional studies, and we provide potential therapeutic targets to reduce RHR and cardiovascular mortality.

Frequency, Penetrance, and Variable Expressivity of Dilated Cardiomyopathy-Associated Putative Pathogenic Gene Variants in UK Biobank Participants.

BACKGROUND: There is a paucity of data regarding the phenotype of dilated cardiomyopathy (DCM) gene variants in the general population. We aimed to determine the frequency and penetrance of DCM-associated putative pathogenic gene variants in a general adult population, with a focus on the expression of clinical and subclinical phenotype, including structural, functional, and arrhythmic disease features. METHODS: UK Biobank participants who had undergone whole exome sequencing, ECG, and cardiovascular magnetic resonance imaging were selected for study. Three variant-calling strategies (1 primary and 2 secondary) were used to identify participants with putative pathogenic variants in 44 DCM genes. The observed phenotype was graded DCM (clinical or cardiovascular magnetic resonance diagnosis); early DCM features, including arrhythmia or conduction disease, isolated ventricular dilation, and hypokinetic nondilated cardiomyopathy; or phenotype-negative. RESULTS: Among 18 665 individuals included in the study, 1463 (7.8%) possessed ≥1 putative pathogenic variant in 44 DCM genes by the main variant calling strategy. A clinical diagnosis of DCM was present in 0.34% and early DCM features in 5.7% of individuals with putative pathogenic variants. ECG and cardiovascular magnetic resonance analysis revealed evidence of subclinical DCM in an additional 1.6% and early DCM features in an additional 15.9% of individuals with putative pathogenic variants. Arrhythmias or conduction disease (15.2%) were the most common early DCM features, followed by hypokinetic nondilated cardiomyopathy (4%). The combined clinical/subclinical penetrance was ≤30% with all 3 variant filtering strategies. Clinical DCM was slightly more prevalent among participants with putative pathogenic variants in definitive/strong evidence genes as compared with those with variants in moderate/limited evidence genes. CONCLUSIONS: In the UK Biobank, ≈1 of 6 of adults with putative pathogenic variants in DCM genes exhibited early DCM features potentially associated with DCM genotype, most commonly manifesting with arrhythmias in the absence of substantial ventricular dilation or dysfunction.

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.

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

Sudden cardiac death is responsible for half of all deaths from cardiovascular disease. The analysis of the electrophysiological substrate for arrhythmias is crucial for optimal risk stratification. A prolonged T-peak-to-Tend (Tpe) interval on the electrocardiogram is an independent predictor of increased arrhythmic risk, and Tpe changes with heart rate are even stronger predictors. However, our understanding of the electrophysiological mechanisms supporting these risk factors is limited. We conducted genome-wide association studies (GWASs) for resting Tpe and Tpe response to exercise and recovery in ∼30,000 individuals, followed by replication in independent samples (∼42,000 for resting Tpe and ∼22,000 for Tpe response to exercise and recovery), all from UK Biobank. Fifteen and one single-nucleotide variants for resting Tpe and Tpe response to exercise, respectively, were formally replicated. In a full dataset GWAS, 13 further loci for resting Tpe, 1 for Tpe response to exercise and 1 for Tpe response to exercise were genome-wide significant (p ≤ 5 × 10-8). Sex-specific analyses indicated seven additional loci. In total, we identify 32 loci for resting Tpe, 3 for Tpe response to exercise and 3 for Tpe response to recovery modulating ventricular repolarization, as well as cardiac conduction and contraction. Our findings shed light on the genetic basis of resting Tpe and Tpe response to exercise and recovery, unveiling plausible candidate genes and biological mechanisms underlying ventricular excitability.

Deep palmar phenotyping in atopic eczema: patterns associated with filaggrin variants, disease severity and barrier function in a South Asian population.

BACKGROUND: Hyperlinear palms are described as a feature of loss-of-function (LoF) variants in filaggrin (FLG). OBJECTIVES: To explore the phenotype of participants (age < 31 years) with atopic eczema of Bangladeshi ancestry from East London and investigate which factors best associate with LoF FLG variants. METHODS: A cross-sectional study with participants recruited between May 2018 and December 2020. Patterns of palmar linearity were categorized and modelled with the Eczema Area and Severity Index (EASI), transepidermal water loss (TEWL), skin hydration (SH) and LoF FLG variants. RESULTS: There were 506 complete cases available. Five palm patterns were noted. The 'prominent diamond' pattern associated best with EASI [marginal effects (ME) 2.53, 95% confidence interval (CI) 1.74-3.67], SH (ME 0.85, 95% CI 0.78-0.96) and TEWL (ME 1.32, 95% CI 1.11-1.62). Using five palm patterns had some ability to discriminate LoF FLG variants [area under the receiver operator characteristic (AUROC) 76.32%, 95% CI 71.91-80.73], improving to 77.99% (73.70-82.28) with the addition of SH. In subgroup analysis with only fine perpendicular/prominent diamond patterns the AUROC was 89.11% (95% CI 84.02-94.19). CONCLUSIONS: This was a single-centre study design with humans classifying clinical patterns. The stability of temperature and humidity was not guaranteed across TEWL and SH measurements despite using a climate-controlled room. Palm patterns associate with EASI and TEWL. The fine perpendicular/prominent diamond patterns are markers to detect the absence/presence of LoF FLG variants, respectively.

Interleukin-1 receptor antagonist, mode of analgesia and risk of Caesarean delivery after onset of labour: a Mendelian randomisation analysis.

BACKGROUND: Lower circulating levels of the anti-inflammatory cytokine interleukin-1 receptor antagonist (IL-1ra) are associated with intrapartum inflammation and epidural analgesia-related maternal fever, both of which increase the rate of obstetric interventions. We hypothesised that genetic variants determining IL-1ra levels would be associated with Caesarean delivery rates after the onset of labour. METHODS: We performed Mendelian randomisation analyses in parous women ≥16 yr old who received either non-neuraxial or neuraxial analgesia for their first two labours (UK Biobank). We used an established genetic score (calculated as 0-4, determined by the presence/absence of rs6743376 and rs1542176 alleles), in which the complete absence of both alleles causes the lowest IL-1ra levels. The primary outcome was Caesarean delivery after the onset of labour (odds ratio [OR]: 95% confidence intervals). RESULTS: There were 7731 women (mean [standard deviation] age at first birth: 25 [5] yr) who had complete genetic scores and delivery data. For women who received non-neuraxial analgesia, Caesarean delivery rates were different across allele scores (χ2=12.4; P=0.015): 104/596 (17.4%) women with zero allele score underwent Caesarean delivery, compared with 654/5015 (13.0%) with allele score ≥1 (OR 1.41; 1.12-1.77). For women who had neuraxial analgesia, Caesarean delivery was not different across allele scores, ranging from 18.1% to 20.8% (χ2=0.29; P=0.99). Caesarean delivery was independent of type of analgesia for 818/7731 (10.6%) women with zero allele scores (OR 0.93; 0.63-1.39), but was higher in women receiving neuraxial analgesia with allele scores ≥1 (OR 1.55; 1.35-1.79; P<0.001). CONCLUSIONS: Mendelian randomisation analysis suggests that higher IL-1ra levels are associated with reduced Caesarean delivery rate. Neuraxial analgesia appears to disrupt this link. CLINICAL TRIAL REGISTRATION: UK Biobank study 62745.

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 ß-adrenergic mechanisms.

Premature atrial and ventricular contractions detected on wearable-format electrocardiograms and prediction of cardiovascular events.

Aims: Wearable devices are transforming the electrocardiogram (ECG) into a ubiquitous medical test. This study assesses the association between premature ventricular and atrial contractions (PVCs and PACs) detected on wearable-format ECGs (15 s single lead) and cardiovascular outcomes in individuals without cardiovascular disease (CVD). Methods and results: Premature atrial contractions and PVCs were identified in 15 s single-lead ECGs from N = 54 016 UK Biobank participants (median age, interquartile range, age 58, 50-63 years, 54% female). Cox regression models adjusted for traditional risk factors were used to determine associations with atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), stroke, life-threatening ventricular arrhythmias (LTVAs), and mortality over a period of 11.5 (11.4-11.7) years. The strongest associations were found between PVCs (prevalence 2.2%) and HF (hazard ratio, HR, 95% confidence interval = 2.09, 1.58-2.78) and between PACs (prevalence 1.9%) and AF (HR = 2.52, 2.11-3.01), with shorter prematurity further increasing risk. Premature ventricular contractions and PACs were also associated with LTVA (P < 0.05). Associations with MI, stroke, and mortality were significant only in unadjusted models. In a separate UK Biobank sub-study sample [UKB-2, N = 29,324, age 64, 58-60 years, 54% female, follow-up 3.5 (2.6-4.8) years] used for independent validation, after adjusting for risk factors, PACs were associated with AF (HR = 1.80, 1.12-2.89) and PVCs with HF (HR = 2.32, 1.28-4.22). Conclusion: In middle-aged individuals without CVD, premature contractions identified in 15 s single-lead ECGs are strongly associated with an increased risk of AF and HF. These data warrant further investigation to assess the role of wearable ECGs for early cardiovascular risk stratification.

Long-term association of ultra-short heart rate variability with cardiovascular events.

Heart rate variability (HRV) is a cardiac autonomic marker with predictive value in cardiac patients. Ultra-short HRV (usHRV) can be measured at scale using standard and wearable ECGs, but its association with cardiovascular events in the general population is undetermined. We aimed to validate usHRV measured using ≤ 15-s ECGs (using RMSSD, SDSD and PHF indices) and investigate its association with atrial fibrillation, major adverse cardiac events, stroke and mortality in individuals without cardiovascular disease. In the National Survey for Health and Development (n = 1337 participants), agreement between 15-s and 6-min HRV, assessed with correlation analysis and Bland-Altman plots, was very good for RMSSD and SDSD and good for PHF. In the UK Biobank (n = 51,628 participants, 64% male, median age 58), after a median follow-up of 11.5 (11.4-11.7) years, incidence of outcomes ranged between 1.7% and 4.3%. Non-linear Cox regression analysis showed that reduced usHRV from 15-, 10- and 5-s ECGs was associated with all outcomes. Individuals with low usHRV (< 20th percentile) had hazard ratios for outcomes between 1.16 and 1.29, p < 0.05, with respect to the reference group. In conclusion, usHRV from ≤ 15-s ECGs correlates with standard short-term HRV and predicts increased risk of cardiovascular events in a large population-representative cohort.

Predicting left ventricular hypertrophy from the 12-lead electrocardiogram in the UK Biobank imaging study using machine learning.

Aims: Left ventricular hypertrophy (LVH) is an established, independent predictor of cardiovascular disease. Indices derived from the electrocardiogram (ECG) have been used to infer the presence of LVH with limited sensitivity. This study aimed to classify LVH defined by cardiovascular magnetic resonance (CMR) imaging using the 12-lead ECG for cost-effective patient stratification. Methods and results: We extracted ECG biomarkers with a known physiological association with LVH from the 12-lead ECG of 37 534 participants in the UK Biobank imaging study. Classification models integrating ECG biomarkers and clinical variables were built using logistic regression, support vector machine (SVM) and random forest (RF). The dataset was split into 80% training and 20% test sets for performance evaluation. Ten-fold cross validation was applied with further validation testing performed by separating data based on UK Biobank imaging centres. QRS amplitude and blood pressure (P < 0.001) were the features most strongly associated with LVH. Classification with logistic regression had an accuracy of 81% [sensitivity 70%, specificity 81%, Area under the receiver operator curve (AUC) 0.86], SVM 81% accuracy (sensitivity 72%, specificity 81%, AUC 0.85) and RF 72% accuracy (sensitivity 74%, specificity 72%, AUC 0.83). ECG biomarkers enhanced model performance of all classifiers, compared to using clinical variables alone. Validation testing by UK Biobank imaging centres demonstrated robustness of our models. Conclusion: A combination of ECG biomarkers and clinical variables were able to predict LVH defined by CMR. Our findings provide support for the ECG as an inexpensive screening tool to risk stratify patients with LVH as a prelude to advanced imaging.

Genome-Wide Analysis of Left Ventricular Maximum Wall Thickness in the UK Biobank Cohort Reveals a Shared Genetic Background With Hypertrophic Cardiomyopathy.

BACKGROUND: Left ventricular maximum wall thickness (LVMWT) is an important biomarker of left ventricular hypertrophy and provides diagnostic and prognostic information in hypertrophic cardiomyopathy (HCM). Limited information is available on the genetic determinants of LVMWT. METHODS: We performed a genome-wide association study of LVMWT measured from the cardiovascular magnetic resonance examinations of 42 176 European individuals. We evaluated the genetic relationship between LVMWT and HCM by performing pairwise analysis using the data from the Hypertrophic Cardiomyopathy Registry in which the controls were randomly selected from UK Biobank individuals not included in the cardiovascular magnetic resonance sub-study. RESULTS: Twenty-one genetic loci were discovered at P<5×10-8. Several novel candidate genes were identified including PROX1, PXN, and PTK2, with known functional roles in myocardial growth and sarcomere organization. The LVMWT genetic risk score is predictive of HCM in the Hypertrophic Cardiomyopathy Registry (odds ratio per SD: 1.18 [95% CI, 1.13-1.23]) with pairwise analyses demonstrating a moderate genetic correlation (rg=0.53) and substantial loci overlap (19/21). CONCLUSIONS: Our findings provide novel insights into the genetic underpinning of LVMWT and highlight its shared genetic background with HCM, supporting future endeavours to elucidate the genetic etiology of HCM.

Association of Longer Leukocyte Telomere Length With Cardiac Size, Function, and Heart Failure.

Importance: Longer leukocyte telomere length (LTL) is associated with a lower risk of adverse cardiovascular outcomes. The extent to which variation in LTL is associated with intermediary cardiovascular phenotypes is unclear. Objective: To evaluate the associations between LTL and a diverse set of cardiovascular imaging phenotypes. Design, Setting, and Participants: This is a population-based cross-sectional study of UK Biobank participants recruited from 2006 to 2010. LTL was measured using a quantitative polymerase chain reaction method. Cardiovascular measurements were derived from cardiovascular magnetic resonance using machine learning. The median (IQR) duration of follow-up was 12.0 (11.3-12.7) years. The associations of LTL with imaging measurements and incident heart failure (HF) were evaluated by multivariable regression models. Genetic associations between LTL and significantly associated traits were investigated by mendelian randomization. Data were analyzed from January to May 2023. Exposure: LTL. Main Outcomes and Measures: Cardiovascular imaging traits and HF. Results: Of 40 459 included participants, 19 529 (48.3%) were men, and the mean (SD) age was 55.1 (7.6) years. Longer LTL was independently associated with a pattern of positive cardiac remodeling (higher left ventricular mass, larger global ventricular size and volume, and higher ventricular and atrial stroke volumes) and a lower risk of incident HF (LTL fourth quartile vs first quartile: hazard ratio, 0.86; 95% CI, 0.81-0.91; P = 1.8 × 10-6). Mendelian randomization analysis suggested a potential causal association between LTL and left ventricular mass, global ventricular volume, and left ventricular stroke volume. Conclusions and Relevance: In this cross-sectional study, longer LTL was associated with a larger heart with better cardiac function in middle age, which could potentially explain the observed lower risk of incident HF.

Predicted Deleterious Variants in Cardiomyopathy Genes Prognosticate Mortality and Composite Outcomes in UK Biobank.

BACKGROUND: Inherited cardiomyopathies present with broad variation of phenotype. Data are limited regarding genetic screening strategies and outcomes associated with predicted deleterious variants in cardiomyopathy-associated genes in the general population. OBJECTIVES: The authors aimed to determine the risk of mortality and composite cardiomyopathy-related outcomes associated with predicted deleterious variants in cardiomyopathy-associated genes in the UK Biobank. METHODS: Using whole exome sequencing data, variants in dilated, hypertrophic, and arrhythmogenic right ventricular cardiomyopathy-associated genes with at least moderate evidence of disease causality according to ClinGen Expert Panel curations were annotated using REVEL (≥0.65) and ANNOVAR (predicted loss-of-function) considering gene-disease mechanisms. Genotype-positive and genotype-negative groups were compared using time-to-event analyses for the primary (all-cause mortality) and secondary outcomes (diagnosis of cardiomyopathy; composite outcome of diagnosis of cardiomyopathy, heart failure, arrhythmia, stroke, and death). RESULTS: Among 200,619 participants (age at recruitment 56.46 ± 8.1 years), 5,292 (2.64%) were found to host ≥1 predicted deleterious variants in cardiomyopathy-associated genes (CMP-G+). After adjusting for age and sex, CMP-G+ individuals had higher risk for all-cause mortality (HR: 1.13 [95% CI: 1.01-1.25]; P = 0.027), increased risk for being diagnosed with cardiomyopathy later in life (HR: 5.75 [95% CI: 4.58-7.23]; P < 0.0001), and elevated risk for composite outcome (HR: 1.29 [95% CI: 1.20-1.39]; P < 0.0001) than CMP-G- individuals. The higher risk for being diagnosed with cardiomyopathy and composite outcomes in the genotype-positive subjects remained consistent across all cardiomyopathy subgroups. CONCLUSIONS: Adults with predicted deleterious variants in cardiomyopathy-associated genes exhibited a slightly higher risk of mortality and a significantly increased risk of developing cardiomyopathy, and cardiomyopathy-related composite outcomes, in comparison with genotype-negative controls.

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.

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.

Improving explainability of deep neural network-based electrocardiogram interpretation using variational auto-encoders.

Aims: Deep neural networks (DNNs) perform excellently in interpreting electrocardiograms (ECGs), both for conventional ECG interpretation and for novel applications such as detection of reduced ejection fraction (EF). Despite these promising developments, implementation is hampered by the lack of trustworthy techniques to explain the algorithms to clinicians. Especially, currently employed heatmap-based methods have shown to be inaccurate. Methods and results: We present a novel pipeline consisting of a variational auto-encoder (VAE) to learn the underlying factors of variation of the median beat ECG morphology (the FactorECG), which are subsequently used in common and interpretable prediction models. As the ECG factors can be made explainable by generating and visualizing ECGs on both the model and individual level, the pipeline provides improved explainability over heatmap-based methods. By training on a database with 1.1 million ECGs, the VAE can compress the ECG into 21 generative ECG factors, most of which are associated with physiologically valid underlying processes. Performance of the explainable pipeline was similar to 'black box' DNNs in conventional ECG interpretation [area under the receiver operating curve (AUROC) 0.94 vs. 0.96], detection of reduced EF (AUROC 0.90 vs. 0.91), and prediction of 1-year mortality (AUROC 0.76 vs. 0.75). Contrary to the 'black box' DNNs, our pipeline provided explainability on which morphological ECG changes were important for prediction. Results were confirmed in a population-based external validation dataset. Conclusions: Future studies on DNNs for ECGs should employ pipelines that are explainable to facilitate clinical implementation by gaining confidence in artificial intelligence and making it possible to identify biased models.

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.