Thirty loci identified for heart rate response to exercise and recovery implicate autonomic nervous system

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.

Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease

The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.

Genetic polymorphisms associated with adverse pregnancy outcomes in nulliparas

Adverse pregnancy outcomes (APOs) affect a large proportion of pregnancies and represent an important cause of morbidity and mortality worldwide. Yet the pathophysiology of APOs is poorly understood, limiting our ability to prevent and treat these conditions. To search for genetic markers of maternal risk for four APOs, we performed multi-ancestry genome-wide association studies (GWAS) for pregnancy loss, gestational length, gestational diabetes, and preeclampsia. We clustered participants by their genetic ancestry and focused our analyses on three sub-cohorts with the largest sample sizes: European, African, and Admixed American. Association tests were carried out separately for each sub-cohort and then meta-analyzed together. Two novel loci were significantly associated with an increased risk of pregnancy loss: a cluster of SNPs located downstream of the TRMU gene (top SNP: rs142795512), and the SNP rs62021480 near RGMA. In the GWAS of gestational length we identified two new variants, rs2550487 and rs58548906 near WFDC1 and AC005052.1, respectively. Lastly, three new loci were significantly associated with gestational diabetes (top SNPs: rs72956265, rs10890563, rs79596863), located on or near ZBTB20, GUCY1A2, and RPL7P20, respectively. Fourteen loci previously correlated with preterm birth, gestational diabetes, and preeclampsia were found to be associated with these outcomes as well.

Genetic architecture of cardiac dynamic flow volumes

Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.

Role of Genetic Variation in Transcriptional Regulatory Elements in Heart Rhythm

Genetic predisposition to cardiac arrhythmias has been a field of intense investigation. Research initially focused on rare hereditary arrhythmias, but over the last two decades, the role of genetic variation (single nucleotide polymorphisms) in heart rate, rhythm, and arrhythmias has been taken into consideration as well. In particular, genome-wide association studies have identified hundreds of genomic loci associated with quantitative electrocardiographic traits, atrial fibrillation, and less common arrhythmias such as Brugada syndrome. A significant number of associated variants have been found to systematically localize in non-coding regulatory elements that control the tissue-specific and temporal transcription of genes encoding transcription factors, ion channels, and other proteins. However, the identification of causal variants and the mechanism underlying their impact on phenotype has proven difficult due to the complex tissue-specific, time-resolved, condition-dependent, and combinatorial function of regulatory elements, as well as their modest conservation across different model species. In this review, we discuss research efforts aimed at identifying and characterizing-trait-associated variant regulatory elements and the molecular mechanisms underlying their impact on heart rate or rhythm.

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.

Heart rate recovery after orthostatic challenge and cardiopulmonary exercise testing in older individuals: prospective multicentre observational cohort study

Background

Impaired vagal function in older individuals, quantified by the 'gold standard' delayed heart rate recovery after maximal exercise (HRRexercise), is an independent predictor of cardiorespiratory capacity and mortality (particularly when HRR ≤12 beats min-1). Heart rate also often declines after orthostatic challenge (HRRorthostatic), but the mechanism remains unclear. We tested whether HRRorthostatic reflects similar vagal autonomic characteristics as HRRexercise.

Methods

Prospective multicentre cohort study of subjects scheduled for cardiopulmonary exercise testing (CPET) as part of routine care. Before undergoing CPET, heart rate was measured with participants seated for 3 min, before standing for 3 min (HRRorthostatic). HRRexercise 1 min after the end of CPET was recorded. The primary outcome was the correlation between mean heart rate change every 10 s for 1 min after peak heart rate was attained on standing and after exercise for each participant. Secondary outcomes were HRRorthostatic and peak VO2 compared between individuals with HRRexercise <12 beats min-1.

Results

A total of 87 participants (mean age: 64 yr [95%CI: 61-66]; 48 (55%) females) completed both tests. Mean heart rate change every 10 s for 1 min after peak heart rate after standing and exercise was significantly correlated (R2=0.81; P<0.0001). HRRorthostatic was unchanged in individuals with HRRexercise ≤12 beats min-1 (n=27), but was lower when HRRexercise >12 beats min-1 (n=60; mean difference: 3 beats min-1 [95% confidence interval 1-5 beats min-1]; P<0.0001). Slower HRRorthostatic was associated with lower peak VO2 (mean difference: 3.7 ml kg-1 min-1 [95% confidence interval 0.7-6.8 ml kg-1 min-1]; P=0.039).

Conclusion

Prognostically significant heart rate recovery after exhaustive exercise is characterised by quantitative differences in heart rate recovery after orthostatic challenge. These data suggest that orthostatic challenge is a valid, simple test indicating vagal impairment.

Clinical trial registration

researchregistry6550.

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.

Phenotypic but not genetically predicted heart rate variability associated with all-cause mortality

Low heart rate variability (HRV) has been widely reported as a predictor for increased mortality. However, the molecular mechanisms are poorly understood. Therefore, this study aimed to identify novel genetic loci associated with HRV and assess the association of phenotypic HRV and genetically predicted HRV with mortality. In a GWAS of 46,075 European ancestry individuals from UK biobank, we identified 17 independent genome-wide significant genetic variants in 16 loci associated with HRV traits. Notably, eight of these loci (RNF220, GNB4, LINCR-002, KLHL3/HNRNPA0, CHRM2, KCNJ5, MED13L, and C160rf72) have not been reported previously. In a prospective phenotypic relationship between HRV and mortality during a median follow-up of seven years, individuals with lower HRV had higher risk of dying from any cause. Genetically predicted HRV, as determined by the genetic risk scores, was not associated with mortality. To the best of our knowledge, the findings provide novel biological insights into the mechanisms underlying HRV. These results also underline the role of the cardiac autonomic nervous system, as indexed by HRV, in predicting mortality.

Genome-wide association study on coordination and agility in 461 Chinese Han males

There is growing evidence that genetic factors can influence human athletic performance. In many sports performances, excellent coordination and agility are the keys to mastery. However, few studies have been devoted to identifying genetic influences on athletic performance. Methods: We generated a derived measure of coordination and agility from the data of hexagonal jumps and T-runs and conducted genome-wide association and meta-analysis studies focused on coordination and agility. Results: The phenotypic correlation and genetic covariance analysis indicated that hexagonal jumps and T-runs were possibly influenced by the same set of genetic factors (R = 0.27, genetic covariance = 0.59). Meta-analysis identified rs117047321 genome-wide significant association (N = 143, P < 10E-5) with coordination and agility, and this association was replicated in the replication group (N = 318, P < 0.05). The CG genotype samples of this single nucleotide polymorphism (SNP) required a longer average movement time than the CC genotype samples, and the CG genotype only exists in Asia, which may belong to the East Asia-specific variation. This SNP is located on MYO5B, which is highly expressed in tissues such as the brain, heart, and muscle, suggesting that this locus might be a genetic factor related to human energy metabolism. Conclusion: Our study indicated that genetic factors can affect the athletic performance of coordination and agility. These findings may provide valuable insights for using genetic factors to evaluate sports characteristics.

Spatially resolved multiomics of human cardiac niches

The function of a cell is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system1. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions to provide mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.

Genome-wide association studies: utility and limitations for research in physiology

Physiological systems are subject to interindividual variation encoded by genetics. Genome-wide association studies (GWAS) operate by surveying thousands of genetic variants from a substantial number of individuals and assessing their association to a trait of interest, be it a physiological variable, a molecular phenotype (e.g. gene expression), or even a disease or condition. Through a myriad of methods, GWAS downstream analyses then explore the functional consequences of each variant and attempt to ascertain a causal relationship to the phenotype of interest, as well as to delve into its links to other traits. This type of investigation allows mechanistic insights into physiological functions, pathological disturbances and shared biological processes between traits (i.e. pleiotropy). An exciting example is the discovery of a new thyroid hormone transporter (SLC17A4) and hormone metabolising enzyme (AADAT) from a GWAS on free thyroxine levels. Therefore, GWAS have substantially contributed with insights into physiology and have been shown to be useful in unveiling the genetic control underlying complex traits and pathological conditions; they will continue to do so with global collaborations and advances in genotyping technology. Finally, the increasing number of trans-ancestry GWAS and initiatives to include ancestry diversity in genomics will boost the power for discoveries, making them also applicable to non-European populations.

Observational and genetic evidence support a relationship between cardiac autonomic function and blood pressure

Background

It is unclear how cardiac autonomic function, as indicated by heart rate (HR), heart rate variability (HRV), HR increase during exercise, and HR recovery after exercise, is related to blood pressure (BP). We aimed to examine the observational and genetic evidence for a potential causal effect of these HR(V) traits on BP.

Methods

We performed multivariable adjusted linear regression using Lifelines and UK Biobank cohorts to investigate the relationship between HR(V) traits and BP. Linkage disequilibrium score regression was conducted to examine genetic correlations. We used two-sample Mendelian randomization (2SMR) to examine potential causal relations between HR(V) traits and BP.

Results

Observational analyses showed negative associations of all HR(V) traits with BP, except for HR, which was positively associated. Genetic correlations were directionally consistent with the observational associations, but most significant genetic correlations between HR(V) traits and BP were limited to diastolic blood pressure (DBP). 2SMR analyses suggested a potentially causal relationship between HR(V) traits and DBP but not systolic blood pressure (SBP). No reverse effect of BP on HR(V) traits was found. One standard deviation (SD) unit increase in HR was associated with a 1.82 mmHg elevation of DBP. In contrast, one ln(ms) unit increase of the root mean square of the successive differences (RMSSD) and corrected RMSSD (RMSSDc), decreased DBP by 1.79 and 1.83 mmHg, respectively. For HR increase and HR recovery at 50 s, every additional SD increase was associated with a lower DBP by 2.05 and 1.47 mmHg, respectively. Results of secondary analyses with pulse pressure as outcome were inconsistent between observational and 2SMR analyses, as well as between HR(V) traits, and therefore inconclusive.

Conclusion

Both observational and genetic evidence show strong associations between indices of cardiac autonomic function and DBP, suggesting that a larger relative contribution of the sympathetic versus the parasympathetic nervous system to cardiac function may cause elevated DBP.

Associations of schizophrenia with arrhythmic disorders and electrocardiogram traits: an in-depth genetic exploration of population samples

Background

An important contributor to the decreased life expectancy of individuals with schizophrenia is sudden cardiac death. While arrhythmic disorders play an important role in this, the nature of the relation between schizophrenia and arrhythmia is not fully understood.

Methods

We leveraged summary-level data of large-scale genome-wide association studies of schizophrenia (53,386 cases 77,258 controls), arrhythmic disorders (atrial fibrillation, 55,114 cases 482,295 controls; Brugada syndrome, 2,820 cases 10,001 controls) and electrocardiogram traits (heart rate (variability), PR interval, QT interval, JT interval, and QRS duration, n=46,952-293,051). First, we examined shared genetic liability by assessing global and local genetic correlations and conducting functional annotation. Next, we explored bidirectional causal relations between schizophrenia and arrhythmic disorders and electrocardiogram traits using Mendelian randomization.

Outcomes

There was no evidence for global genetic correlations, except between schizophrenia and Brugada (rg=0·14, p=4·0E-04). In contrast, strong positive and negative local genetic correlations between schizophrenia and all cardiac traits were found across the genome. In the strongest associated regions, genes related to immune system and viral response mechanisms were overrepresented. Mendelian randomization indicated a causal, increasing effect of liability to schizophrenia on Brugada syndrome (OR=1·15, p=0·009) and heart rate during activity (beta=0·25, p=0·015).

Interpretation

While there was little evidence for global genetic correlations, specific genomic regions and biological pathways important for both schizophrenia and arrhythmic disorders and electrocardiogram traits emerged. The putative causal effect of liability to schizophrenia on Brugada warrants increased cardiac monitoring and potentially early medical intervention in patients with schizophrenia.

Funding

European Research Council Starting Grant.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

Genetic variants associated with syncope implicate neural and autonomic processes

AIMS

Syncope is a common and clinically challenging condition. In this study, the genetics of syncope were investigated to seek knowledge about its pathophysiology and prognostic implications.

METHODS AND RESULTS

This genome-wide association meta-analysis included 56 071 syncope cases and 890 790 controls from deCODE genetics (Iceland), UK Biobank (United Kingdom), and Copenhagen Hospital Biobank Cardiovascular Study/Danish Blood Donor Study (Denmark), with a follow-up assessment of variants in 22 412 cases and 286 003 controls from Intermountain (Utah, USA) and FinnGen (Finland). The study yielded 18 independent syncope variants, 17 of which were novel. One of the variants, p.Ser140Thr in PTPRN2, affected syncope only when maternally inherited. Another variant associated with a vasovagal reaction during blood donation and five others with heart rate and/or blood pressure regulation, with variable directions of effects. None of the 18 associations could be attributed to cardiovascular or other disorders. Annotation with regard to regulatory elements indicated that the syncope variants were preferentially located in neural-specific regulatory regions. Mendelian randomization analysis supported a causal effect of coronary artery disease on syncope. A polygenic score (PGS) for syncope captured genetic correlation with cardiovascular disorders, diabetes, depression, and shortened lifespan. However, a score based solely on the 18 syncope variants performed similarly to the PGS in detecting syncope risk but did not associate with other disorders.

CONCLUSION

The results demonstrate that syncope has a distinct genetic architecture that implicates neural regulatory processes and a complex relationship with heart rate and blood pressure regulation. A shared genetic background with poor cardiovascular health was observed, supporting the importance of a thorough assessment of individuals presenting with syncope.

Genome-Wide Association Analysis of Over 170,000 Individuals from the UK Biobank Identifies Seven Loci Associated with Dietary Approaches to Stop Hypertension (DASH) Diet

Diet is a modifiable risk factor for common chronic diseases and mental health disorders, and its effects are under partial genetic control. To estimate the impact of diet on individual health, most epidemiological and genetic studies have focused on individual aspects of dietary intake. However, analysing individual food groups in isolation does not capture the complexity of the whole diet pattern. Dietary indices enable a holistic estimation of diet and account for the intercorrelations between food and nutrients. In this study we performed the first ever genome-wide association study (GWA) including 173,701 individuals from the UK Biobank to identify genetic variants associated with the Dietary Approaches to Stop Hypertension (DASH) diet. DASH was calculated using the 24 h-recall questionnaire collected by UK Biobank. The GWA was performed using a linear mixed model implemented in BOLT-LMM. We identified seven independent single-nucleotide polymorphisms (SNPs) associated with DASH. Significant genetic correlations were observed between DASH and several educational traits with a significant enrichment for genes involved in the AMP-dependent protein kinase (AMPK) activation that controls the appetite by regulating the signalling in the hypothalamus. The colocalization analysis implicates genes involved in body mass index (BMI)/obesity and neuroticism (ARPP21, RP11-62H7.2, MFHAS1, RHEBL1). The Mendelian randomisation analysis suggested that increased DASH score, which reflect a healthy diet style, is causal of lower glucose, and insulin levels. These findings further our knowledge of the pathways underlying the relationship between diet and health outcomes. They may have significant implications for global public health and provide future dietary recommendations for the prevention of common chronic diseases.

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.

Deep learning on resting electrocardiogram to identify impaired heart rate recovery

Background and Objective

Postexercise heart rate recovery (HRR) is an important indicator of cardiac autonomic function and abnormal HRR is associated with adverse outcomes. We hypothesized that deep learning on resting electrocardiogram (ECG) tracings may identify individuals with impaired HRR.

Methods

We trained a deep learning model (convolutional neural network) to infer HRR based on resting ECG waveforms (HRR_pred) among UK Biobank participants who had undergone exercise testing. We examined the association of HRR_pred with incident cardiovascular disease using Cox models, and investigated the genetic architecture of HRR_pred in genome-wide association analysis.

Results

Among 56,793 individuals (mean age 57 years, 51% women), the HRR_pred model was moderately correlated with actual HRR (r = 0.48, 95% confidence interval [CI] 0.47-0.48). Over a median follow-up of 10 years, we observed 2060 incident diabetes mellitus (DM) events, 862 heart failure events, and 2065 deaths. Higher HRR_pred was associated with lower risk of DM (hazard ratio [HR] 0.79 per 1 standard deviation change, 95% CI 0.76-0.83), heart failure (HR 0.89, 95% CI 0.83-0.95), and death (HR 0.83, 95% CI 0.79-0.86). After accounting for resting heart rate, the association of HRR_pred with incident DM and all-cause mortality were similar. Genetic determinants of HRR_pred included known heart rate, cardiac conduction system, cardiomyopathy, and metabolic trait loci.

Conclusion

Deep learning-derived estimates of HRR using resting ECG independently associated with future clinical outcomes, including new-onset DM and all-cause mortality. Inferring postexercise heart rate response from a resting ECG may have potential clinical implications and impact on preventive strategies warrants future study.

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.

The genetic case for cardiorespiratory fitness as a clinical vital sign and the routine prescription of physical activity in healthcare

BACKGROUND

Cardiorespiratory fitness (CRF) and physical activity (PA) are well-established predictors of morbidity and all-cause mortality. However, CRF is not routinely measured and PA not routinely prescribed as part of standard healthcare. The American Heart Association (AHA) recently presented a scientific case for the inclusion of CRF as a clinical vital sign based on epidemiological and clinical observation. Here, we leverage genetic data in the UK Biobank (UKB) to strengthen the case for CRF as a vital sign and make a case for the prescription of PA.

METHODS

We derived two CRF measures from the heart rate data collected during a submaximal cycle ramp test: CRF-vo2max, an estimate of the participants' maximum volume of oxygen uptake, per kilogram of body weight, per minute; and CRF-slope, an estimate of the rate of increase of heart rate during exercise. Average PA over a 7-day period was derived from a wrist-worn activity tracker. After quality control, 70,783 participants had data on the two derived CRF measures, and 89,683 had PA data. We performed genome-wide association study (GWAS) analyses by sex, and post-GWAS techniques to understand genetic architecture of the traits and prioritise functional genes for follow-up.

RESULTS

We found strong evidence that genetic variants associated with CRF and PA influenced genetic expression in a relatively small set of genes in the heart, artery, lung, skeletal muscle and adipose tissue. These functionally relevant genes were enriched among genes known to be associated with coronary artery disease (CAD), type 2 diabetes (T2D) and Alzheimer's disease (three of the top 10 causes of death in high-income countries) as well as Parkinson's disease, pulmonary fibrosis, and blood pressure, heart rate, and respiratory phenotypes. Genetic variation associated with lower CRF and PA was also correlated with several disease risk factors (including greater body mass index, body fat and multiple obesity phenotypes); a typical T2D profile (including higher insulin resistance, higher fasting glucose, impaired beta-cell function, hyperglycaemia, hypertriglyceridemia); increased risk for CAD and T2D; and a shorter lifespan.

CONCLUSIONS

Genetics supports three decades of evidence for the inclusion of CRF as a clinical vital sign. Given the genetic, clinical and epidemiological evidence linking CRF and PA to increased morbidity and mortality, regular measurement of CRF as a marker of health and routine prescription of PA could be a prudent strategy to support public health.

The many faces of the E3 ubiquitin ligase, RNF220, in neural development and beyond

Ubiquitin modification plays important roles in many cellular processes that are fundamental for vertebrate embryo development, such as cell division, differentiation, and migration. Aberrant function or deregulation of ubiquitination enzymes can cause developmental disorders, cancer progression, and neurodegenerative diseases in humans. RING finger protein 220 (RNF220) is an evolutionarily conserved RING-type ubiquitin E3 ligase. Recent studies have revealed the roles and mechanisms of RNF220 and its partner protein, zinc finger C4H2-type containing protein (ZC4H2), in embryonic development and human diseases. Using mouse and zebrafish models, it has been shown that RNF220 regulates sonic hedgehog (Shh) signaling via Gli and embryonic ectoderm development (EED), a polycomb repressive complex 2 (PRC2) component, during ventral neural patterning and cerebellum development. In addition, RNF220 also regulates the development and functions of central noradrenergic and motor neurons in mice. By stabilizing β-catenin and signal transducer and activator of transcription 1 (STAT1), RNF220 is also involved in Wnt and interferon (IFN)-STAT1 signaling and thus the regulation of tumorigenesis and immune response, respectively. In humans, both RNF220 and ZC4H2 mutations have been reported to be associated with diseases accompanied by complicated neural defects. In this review, we summarize the current knowledge of RNF220 with special emphasis on its roles and mechanisms of action in signal transduction, vertebrate neural development, and related human disorders.

The genetics of human performance

Human physiology is likely to have been selected for endurance physical activity. However, modern humans have become largely sedentary, with physical activity becoming a leisure-time pursuit for most. Whereas inactivity is a strong risk factor for disease, regular physical activity reduces the risk of chronic disease and mortality. Although substantial epidemiological evidence supports the beneficial effects of exercise, comparatively little is known about the molecular mechanisms through which these effects operate. Genetic and genomic analyses have identified genetic variation associated with human performance and, together with recent proteomic, metabolomic and multi-omic analyses, are beginning to elucidate the molecular genetic mechanisms underlying the beneficial effects of physical activity on human health.

Transcriptional and Epigenetic Landscape of Cardiac Pacemaker Cells: Insights Into Cellular Specialization in the Sinoatrial Node

Cardiac pacemaker cells differentiate and functionally specialize early in embryonic development through activation of critical gene regulatory networks. In general, cellular specification and differentiation require that combinations of cell type-specific transcriptional regulators activate expression of key effector genes by binding to DNA regulatory elements including enhancers and promoters. However, because genomic DNA is tightly packaged by histones that must be covalently modified in order to render DNA regulatory elements and promoters accessible for transcription, the process of development and differentiation is intimately connected to the epigenetic regulation of chromatin accessibility. Although the difficulty of obtaining sufficient quantities of pure populations of pacemaker cells has limited progress in this field, the advent of low-input genomic technologies has the potential to catalyze a rapid growth of knowledge in this important area. The goal of this review is to outline the key transcriptional networks that control pacemaker cell development, with particular attention to our emerging understanding of how chromatin accessibility is modified and regulated during pacemaker cell differentiation. In addition, we will discuss the relevance of these findings to adult sinus node function, sinus node diseases, and origins of genetic variation in heart rhythm. Lastly, we will outline the current challenges facing this field and promising directions for future investigation.

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.

Genetic insight into sick sinus syndrome

Aims

The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development.

Methods and results

We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1–1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10⁻²⁰), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05).

Conclusion

We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.

Whole Genome Interpretation for a Family of Five

Although best practices have emerged on how to analyse and interpret personal genomes, the utility of whole genome screening remains underdeveloped. A large amount of information can be gathered from various types of analyses via whole genome sequencing including pathogenicity screening, genetic risk scoring, fitness, nutrition, and pharmacogenomic analysis. We recognize different levels of confidence when assessing the validity of genetic markers and apply rigorous standards for evaluation of phenotype associations. We illustrate the application of this approach on a family of five. By applying analyses of whole genomes from different methodological perspectives, we are able to build a more comprehensive picture to assist decision making in preventative healthcare and well-being management. Our interpretation and reporting outputs provide input for a clinician to develop a healthcare plan for the individual, based on genetic and other healthcare data.

No Clinically Relevant Effect of Heart Rate Increase and Heart Rate Recovery During Exercise on Cardiovascular Disease: A Mendelian Randomization Analysis

BACKGROUND

Reduced heart rate (HR) increase (HRI), recovery (HRR), and higher resting HR are associated with cardiovascular (CV) disease, but causal inferences have not been deduced. We investigated causal effects of HRI, HRR, and resting HR on CV risk, all-cause mortality (ACM), atrial fibrillation (AF), coronary artery disease (CAD), and ischemic stroke (IS) using Mendelian Randomization.

METHODS

11 variants for HRI, 11 for HRR, and two sets of 46 and 414 variants for resting HR were obtained from four genome-wide association studies (GWASs) on UK Biobank. We performed a lookup on GWASs for CV risk and ACM in UK Biobank (N = 375,367, 5.4% cases and N = 393,165, 4.4% cases, respectively). For CAD, AF, and IS, we used publicly available summary statistics. We used a random-effects inverse-variance weighted (IVW) method and sensitivity analyses to estimate causality.

RESULTS

IVW showed a nominally significant effect of HRI on CV events (odds ratio [OR] = 1.0012, P = 4.11 × 10-2) and on CAD and AF. Regarding HRR, IVW was not significant for any outcome. The IVW method indicated statistically significant associations of resting HR with AF (OR = 0.9825, P = 9.8 × 10-6), supported by all sensitivity analyses, and a nominally significant association with IS (OR = 0.9926, P = 9.82 × 10-3).

CONCLUSION

Our findings suggest no strong evidence of an association between HRI and HRR and any outcome and confirm prior work reporting a highly significant effect of resting HR on AF. Future research is required to explore HRI and HRR associations further using more powerful predictors, when available.

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

•

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

•

These errors influence the classification of clinically relevant abnormal values.

•

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

•

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.

Genome-Wide Analysis Identifies an Essential Human TBX3 Pacemaker Enhancer

RATIONALE

The development and function of the pacemaker cardiomyocytes of the sinoatrial node (SAN), the leading pacemaker of the heart, are tightly controlled by a conserved network of transcription factors, including TBX3 (T-box transcription factor 3), ISL1 (ISL LIM homeobox 1), and SHOX2 (short stature homeobox 2). Yet, the regulatory DNA elements (REs) controlling target gene expression in the SAN pacemaker cells have remained undefined.

OBJECTIVE

Identification of the regulatory landscape of human SAN-like pacemaker cells and functional assessment of SAN-specific REs potentially involved in pacemaker cell gene regulation.

METHODS AND RESULTS

We performed Assay for Transposase-Accessible Chromatin using sequencing on human pluripotent stem cell-derived SAN-like pacemaker cells and ventricle-like cells and identified thousands of putative REs specific for either human cell type. We validated pacemaker cell-specific elements in the SHOX2 and TBX3 loci. CRISPR-mediated homozygous deletion of the mouse ortholog of a noncoding region with candidate pacemaker-specific REs in the SHOX2 locus resulted in selective loss of Shox2 expression from the developing SAN and embryonic lethality. Putative pacemaker-specific REs were identified up to 1 Mbp upstream of TBX3 in a region close to MED13L harboring variants associated with heart rate recovery after exercise. The orthologous region was deleted in mice, which resulted in selective loss of expression of Tbx3 from the SAN and (cardiac) ganglia and in neonatal lethality. Expression of Tbx3 was maintained in other tissues including the atrioventricular conduction system, lungs, and liver. Heterozygous adult mice showed increased SAN recovery times after pacing. The human REs harboring the associated variants robustly drove expression in the SAN of transgenic mouse embryos.

CONCLUSIONS

We provided a genome-wide collection of candidate human pacemaker-specific REs, including the loci of SHOX2, TBX3, and ISL1, and identified a link between human genetic variants influencing heart rate recovery after exercise and a variant RE with highly conserved function, driving SAN expression of TBX3.

ATAC-Seq Reveals an Isl1 Enhancer That Regulates Sinoatrial Node Development and Function

RATIONALE

Cardiac pacemaker cells (PCs) in the sinoatrial node (SAN) have a distinct gene expression program that allows them to fire automatically and initiate the heartbeat. Although critical SAN transcription factors, including Isl1 (Islet-1), Tbx3 (T-box transcription factor 3), and Shox2 (short-stature homeobox protein 2), have been identified, the cis-regulatory architecture that governs PC-specific gene expression is not understood, and discrete enhancers required for gene regulation in the SAN have not been identified.

OBJECTIVE

To define the epigenetic profile of PCs using comparative ATAC-seq (assay for transposase-accessible chromatin with sequencing) and to identify novel enhancers involved in SAN gene regulation, development, and function.

METHODS AND RESULTS

We used ATAC-seq on sorted neonatal mouse SAN to compare regions of accessible chromatin in PCs and right atrial cardiomyocytes. PC-enriched assay for transposase-accessible chromatin peaks, representing candidate SAN regulatory elements, were located near established SAN genes and were enriched for distinct sets of TF (transcription factor) binding sites. Among several novel SAN enhancers that were experimentally validated using transgenic mice, we identified a 2.9-kb regulatory element at the Isl1 locus that was active specifically in the cardiac inflow at embryonic day 8.5 and throughout later SAN development and maturation. Deletion of this enhancer from the genome of mice resulted in SAN hypoplasia and sinus arrhythmias. The mouse SAN enhancer also directed reporter activity to the inflow tract in developing zebrafish hearts, demonstrating deep conservation of its upstream regulatory network. Finally, single nucleotide polymorphisms in the human genome that occur near the region syntenic to the mouse enhancer exhibit significant associations with resting heart rate in human populations.

CONCLUSIONS

(1) PCs have distinct regions of accessible chromatin that correlate with their gene expression profile and contain novel SAN enhancers, (2) cis-regulation of Isl1 specifically in the SAN depends upon a conserved SAN enhancer that regulates PC development and SAN function, and (3) a corresponding human ISL1 enhancer may regulate human SAN function.

The effects of polygenic risk for psychiatric disorders and smoking behaviour on psychotic experiences in UK Biobank

While psychotic experiences are core symptoms of mental health disorders like schizophrenia, they are also reported by 5-10% of the population. Both smoking behaviour and genetic risk for psychiatric disorders have been associated with psychotic experiences, but the interplay between these factors remains poorly understood. We tested whether smoking status, maternal smoking around birth, and number of packs smoked/year were associated with lifetime occurrence of three psychotic experiences phenotypes: delusions (n = 2067), hallucinations (n = 6689), and any psychotic experience (delusions or hallucinations; n = 7803) in 157,366 UK Biobank participants. We next calculated polygenic risk scores for schizophrenia (PRSSCZ), bipolar disorder (PRSBP), major depression (PRSDEP) and attention deficit hyperactivity disorder (PRSADHD) in 144,818 UK Biobank participants of European ancestry to assess whether association between smoking and psychotic experiences was attenuated after adjustment of diagnosis of psychiatric disorders and the PRSs. Finally, we investigated whether smoking exacerbates the effects of genetic predisposition on the psychotic phenotypes in gene-environment interaction models. Smoking status, maternal smoking, and number of packs smoked/year were associated with psychotic experiences (p < 1.77 × 10-5). Except for packs smoked/year, effects were attenuated but remained significant after adjustment for diagnosis of psychiatric disorders and PRSs (p < 1.99 × 10-3). Gene-environment interaction models showed the effects of PRSDEP and PRSADHD (but not PRSSCZ or PRSBP) on delusions (but not hallucinations) were significantly greater in current smokers compared to never smokers (p < 0.002). There were no significant gene-environment interactions for maternal smoking nor for number of packs smoked/year. Our results suggest that both genetic risk of psychiatric disorders and smoking status may have independent and synergistic effects on specific types of psychotic experiences.

Translating GWAS-identified loci for cardiac rhythm and rate using an in vivo image- and CRISPR/Cas9-based approach

A meta-analysis of genome-wide association studies (GWAS) identified eight loci that are associated with heart rate variability (HRV), but candidate genes in these loci remain uncharacterized. We developed an image- and CRISPR/Cas9-based pipeline to systematically characterize candidate genes for HRV in live zebrafish embryos. Nine zebrafish orthologues of six human candidate genes were targeted simultaneously in eggs from fish that transgenically express GFP on smooth muscle cells (Tg[acta2:GFP]), to visualize the beating heart. An automated analysis of repeated 30 s recordings of beating atria in 381 live, intact zebrafish embryos at 2 and 5 days post-fertilization highlighted genes that influence HRV (hcn4 and si:dkey-65j6.2 [KIAA1755]); heart rate (rgs6 and hcn4); and the risk of sinoatrial pauses and arrests (hcn4). Exposure to 10 or 25 µM ivabradine—an open channel blocker of HCNs—for 24 h resulted in a dose-dependent higher HRV and lower heart rate at 5 days post-fertilization. Hence, our screen confirmed the role of established genes for heart rate and rhythm (RGS6 and HCN4); showed that ivabradine reduces heart rate and increases HRV in zebrafish embryos, as it does in humans; and highlighted a novel gene that plays a role in HRV (KIAA1755).

Trait-associated noncoding variant regions affect TBX3 regulation and cardiac conduction

Genome-wide association studies have implicated common genomic variants in the gene desert upstream of TBX3 in cardiac conduction velocity. Whether these noncoding variants affect expression of TBX3 or neighboring genes and how they affect cardiac conduction is not understood. Here, we use high-throughput STARR-seq to test the entire 1.3 Mb human and mouse TBX3 locus, including two cardiac conduction-associated variant regions, for regulatory function. We identified multiple accessible and functional regulatory DNA elements that harbor variants affecting their activity. Both variant regions drove gene expression in the cardiac conduction tissue in transgenic reporter mice. Genomic deletion from the mouse genome of one of the regions caused increased cardiac expression of only Tbx3, PR interval shortening and increased QRS duration. Combined, our findings address the mechanistic link between trait-associated variants in the gene desert, TBX3 regulation and cardiac conduction.

Genetic Approaches for Sports Performance: How Far Away Are We?

Humans vary in their ‘natural ability’ related to sports performance. One facet of natural ability reflects so-called intrinsic ability or the ability to do well with minimal training. A second facet of natural ability is how rapidly an individual adapts to training; this is termed trainability. A third facet is the upper limit achievable after years of prolonged intense training; this represents both intrinsic ability and also trainability. There are other features of natural ability to consider, for example body size, because some events, sports, or positions favor participants of different sizes. In this context, the physiological determinants of elite endurance performance, especially running and cycling, are well known and can be used as a template to discuss these general issues. The key determinants of endurance performance include maximal oxygen uptake \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\dot{V}{\text{O}}_{2\hbox{max} } )$$\end{document}(V˙O2max), the lactate threshold, and running economy (efficiency in the case of cycling or other sports). In this article, I use these physiological determinants to explore what is known about the genetics of endurance performance. My main conclusion is that at this time there are very few, if any, obvious relationships between these key physiological determinants of performance and DNA sequence variation. Several potential reasons for this lack of relationship will be discussed.

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.

Transethnic Genome-Wide Association Study Provides Insights in the Genetic Architecture and Heritability of Long QT Syndrome

Supplemental Digital Content is available in the text.

Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility.

Cardiovascular Predictive Value and Genetic Basis of Ventricular Repolarization Dynamics

BACKGROUND

Early prediction of cardiovascular risk in the general population remains an important issue. The T-wave morphology restitution (TMR), an ECG marker quantifying ventricular repolarization dynamics, is strongly associated with cardiovascular mortality in patients with heart failure. Our aim was to evaluate the cardiovascular prognostic value of TMR in a UK middle-aged population and identify any genetic contribution.

METHODS

We analyzed ECG recordings from 55 222 individuals from a UK middle-aged population undergoing an exercise stress test in UK Biobank (UKB). TMR was used to measure ventricular repolarization dynamics, exposed in this cohort by exercise (TMR during exercise, TMR^ex) and recovery from exercise (TMR during recovery, TMR^rec). The primary end point was cardiovascular events; secondary end points were all-cause mortality, ventricular arrhythmias, and atrial fibrillation with median follow-up of 7 years. Genome-wide association studies for TMR^ex and TMR^rec were performed, and genetic risk scores were derived and tested for association in independent samples from the full UKB cohort (N=360 631).

RESULTS

A total of 1743 (3.2%) individuals in UKB who underwent the exercise stress test had a cardiovascular event, and TMR^rec was significantly associated with cardiovascular events (hazard ratio, 1.11; P=5×10^-7), independent of clinical variables and other ECG markers. TMR^rec was also associated with all-cause mortality (hazard ratio, 1.10) and ventricular arrhythmias (hazard ratio, 1.16). We identified 12 genetic loci in total for TMR^ex and TMR^rec, of which 9 are associated with another ECG marker. Individuals in the top 20% of the TMR^rec genetic risk score were significantly more likely to have a cardiovascular event in the full UKB cohort (18 997, 5.3%) than individuals in the bottom 20% (hazard ratio, 1.07; P=6×10^-3).

CONCLUSIONS

TMR and TMR genetic risk scores are significantly associated with cardiovascular risk in a UK middle-aged population, supporting the hypothesis that increased spatio-temporal heterogeneity of ventricular repolarization is a substrate for cardiovascular risk and the validity of TMR as a cardiovascular risk predictor.

Functionally oriented analysis of cardiometabolic traits in a trans-ethnic sample

Interpretation of genetic association results is difficult because signals often lack biological context. To generate hypotheses of the functional genetic etiology of complex cardiometabolic traits, we estimated the genetically determined component of gene expression from common variants using PrediXcan (1) and determined genes with differential predicted expression by trait. PrediXcan imputes tissue-specific expression levels from genetic variation using variant-level effect on gene expression in transcriptome data. To explore the value of imputed genetically regulated gene expression (GReX) models across different ancestral populations, we evaluated imputed expression levels for predictive accuracy genome-wide in RNA sequence data in samples drawn from European-ancestry and African-ancestry populations and identified substantial predictive power using European-derived models in a non-European target population. We then tested the association of GReX on 15 cardiometabolic traits including blood lipid levels, body mass index, height, blood pressure, fasting glucose and insulin, RR interval, fibrinogen level, factor VII level and white blood cell and platelet counts in 15 755 individuals across three ancestry groups, resulting in 20 novel gene-phenotype associations reaching experiment-wide significance across ancestries. In addition, we identified 18 significant novel gene-phenotype associations in our ancestry-specific analyses. Top associations were assessed for additional support via query of S-PrediXcan (2) results derived from publicly available genome-wide association studies summary data. Collectively, these findings illustrate the utility of transcriptome-based imputation models for discovery of cardiometabolic effect genes in a diverse dataset.

Genetics and the heart rate response to exercise

The acute heart rate response to exercise, i.e., heart rate increase during and heart rate recovery after exercise, has often been associated with all-cause and cardiovascular mortality. The long-term response of heart rate to exercise results in favourable changes in chronotropic function, including decreased resting and submaximal heart rate as well as increased heart rate recovery. Both the acute and long-term heart rate response to exercise have been shown to be heritable. Advances in genetic analysis enable researchers to investigate this hereditary component to gain insights in possible molecular mechanisms underlying interindividual differences in the heart rate response to exercise. In this review, we comprehensively searched candidate gene, linkage, and genome-wide association studies that investigated the heart rate response to exercise. A total of ten genes were associated with the acute heart rate response to exercise in candidate gene studies. Only one gene (CHRM2), related to heart rate recovery, was replicated in recent genome-wide association studies (GWASs). Additional 17 candidate causal genes were identified for heart rate increase and 26 for heart rate recovery in these GWASs. Nine of these genes were associated with both acute increase and recovery of the heart rate during exercise. These genes can be broadly categorized into four categories: (1) development of the nervous system (CCDC141, PAX2, SOX5, and CAV2); (2) prolongation of neuronal life span (SYT10); (3) cardiac development (RNF220 and MCTP2); (4) cardiac rhythm (SCN10A and RGS6). Additional 10 genes were linked to long-term modification of the heart rate response to exercise, nine with heart rate increase and one with heart rate recovery. Follow-up will be essential to get functional insights in how candidate causal genes affect the heart rate response to exercise. Future work will be required to translate these findings to preventive and therapeutic applications.

The hypertension advantage and natural selection: Since type 2 diabetes associates with co-morbidities and premature death, why have the genetic variants remained in the human genome?

Type 2 diabetes is a major public health crisis around the world. It is estimated that more than 300 million people worldwide have type 2 diabetes. Furthermore, the World Health Organization estimates that deaths from the complications of diabetes will increase by two thirds between 2008 and 2030. Since type 2 diabetes is a major public health crisis, why have the genetic variants for diabetes not been removed from the genome by natural selection? We hypothesize that insulin resistance, a predisposition to type 2 diabetes, and the associated elevation in sympathetic nervous system activity and arterial blood pressure provided an advantage to humans who lived as hunter-gatherers. Specifically, sympathetic hyperactivity stimulates the renin-angiotensin aldosterone system, promotes sodium reabsorption, and increases blood volume, heart rate, stroke volume and peripheral vascular resistance, thus inducing hypertension. The hypertension in turn provides a hemodynamic advantage for hunter-gatherers. Specifically, sympathetic hyperactivity and increased blood pressure increases blood flow delivery to working muscles by increasing cardiac output and shunting blood from non-active tissue. This natural selection for hypertension occurred during the time in human evolutionary history when the lifespan of most individuals was probably 30-40 years, and morbidity and mortality from cardiovascular disorders was limited. Thus, the selection pressure for elevation in sympathetic nervous system activity and blood pressure provided an advantage for hunting and gathering that would be greater than the selection pressure exerted by the manifestations of cardiovascular disease in aged individuals.

Genetic and epigenetic sex-specific adaptations to endurance exercise

In recent years, the interest in personalised interventions such as medicine, nutrition, and exercise is rapidly rising to maximize health outcomes and ensure the most appropriate treatments. Exercising regularly is recommended for both healthy and diseased populations to improve health. However, there are sex-specific adaptations to exercise that often are not taken into consideration. While endurance exercise training alters the human skeletal muscle epigenome and subsequent gene expression, it is still unknown whether it does so differently in men and women, potentially leading to sex-specific physiological adaptations. Elucidating sex differences in genetics, epigenetics, gene regulation and expression in response to exercise will have great health implications, as it may enable gene targets in future clinical interventions and may better individualised interventions. This review will cover this topic and highlight the recent findings of sex-specific genetic, epigenetic, and gene expression studies, address the gaps in the field, and offer recommendations for future research.

Genes Whose Gain or Loss-of-Function Increases Endurance Performance in Mice: A Systematic Literature Review

Endurance is not only a key factor in many sports but endurance-related variables are also associated with good health and low mortality. Twin and family studies suggest that several endurance-associated traits are ≈50% inherited. However, we still poorly understand what DNA sequence variants contribute to endurance heritability. To address this issue, we conducted a systematic review to identify genes whose experimental loss or gain-of-function increases endurance capacity in mice. We found 31 genes including two isoforms of Ppargc1a whose manipulation increases running or swimming endurance performance by up to 1800%. Genes whose gain-of-function increases endurance are Adcy5, Adcy8, Hk2, Il15, Mef2c, Nr4a3, Pck1 (Pepck), Ppard, Ppargc1a (both the a and b isoforms of the protein Pgc-1α), Ppargc1b, Ppp3ca (calcineurin), Scd1, Slc5a7, Tfe3, Tfeb, Trib3 & Trpv1. Genes whose loss-of-function increases endurance in mice are Actn3, Adrb2, Bdkrb2, Cd47, Crym, Hif1a, Myoz1, Pappa, Pknox1, Pten, Sirt4, Thbs1, Thra, and Tnfsf12. Of these genes, human DNA sequence variants of ACTN3, ADCY5, ADRB2, BDKRB2, HIF1A, PPARD, PPARGC1A, PPARGC1B, and PPP3CA are also associated with endurance capacity and/or VO₂max trainability suggesting evolutionary conservation between mice and humans. Bioinformatical analyses show that there are numerous amino acid or copy number-changing DNA variants of endurance genes in humans, suggesting that genetic variation of endurance genes contributes to the variation of human endurance capacity, too. Moreover, several of these genes/proteins change their expression or phosphorylation in skeletal muscle or the heart after endurance exercise, suggesting a role in the adaptation to endurance exercise.