Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders

Mechanisms Underlying Sinus Node Dysfunction in a Rat Model of Genetic Atrial Cardiomyopathy

BACKGROUND

Sinoatrial node (SAN) dysfunction is commonly associated with atrial dysrhythmia (tachy-brady syndrome) and is a particularly important feature of inherited atrial cardiomyopathies leading to artificial pacemaker implantation. Essential MYL4 (myosin light chain-4) is an atrial-selective protein that associates with the myosin light chain and participates importantly in cardiacmuscle contraction. MYL4 gene variants encoding dysfunctional versions of MYL4 cause familial atrial cardiomyopathy with a high incidence of early SAN dysfunction (SND) and pacemaker requirement. In this study, we used a rat line, genetically modified to express an E11K gene mutation responsible for familial atrial cardiomyopathy, to address the mechanisms underlying SND.

METHODS

Cardiac structure and function were assessed by echocardiography and in vivo telemetry recording. SAN function was studied in vivo with intracardiac electrophysiology and ex vivo with optical mapping. Mechanisms underlying SND were interrogated in vitro with the use of voltage and current clamp with tight-seal patch-clamp and Ca2+ imaging of isolated SAN cardiomyocytes. Gene expression was assessed by quantitative polymerase chain reaction, and fibrosis was determined with Masson's trichrome stain.

RESULTS

Mutant Myl4-p.E11K+/+ rats exhibited worse SAN function compared with wild-type controls. In vivo, SND was demonstrated by ≈63% increase in sinus node recovery time compared with wild type. In vitro, SAN conduction velocity was reduced by ≈ 50% for Myl4-p.E11K+/+ compared with wild type. Isolated SAN cells showed ≈50% reduction in funny current and L-type Ca2+-current densities. Dysregulation of Ca2+ homeostasis was observed in Myl4-p.E11K+/+, with ≈30% slower time to peak and Ca2+ decay. Masson's trichrome staining showed ≈45% increase in SAN region collagen deposition in Myl4-p.E11K+/+.

CONCLUSIONS

Myl4-p.E11K+/+ mutation causes progressive SND with aging, as a result of extensive abnormalities in the underlying determinants of SAN function, including ion-channel properties, Ca2+-homeostasis, and SAN structure. These observations provide new insights into the mechanisms of SAN abnormality in atrial cardiomyopathy.

Natural genetic variation quantitatively regulates heart rate and dimension

The polygenic contribution to heart development and function along the health-disease continuum remains unresolved. To gain insight into the genetic basis of quantitative cardiac phenotypes, we utilize highly inbred Japanese rice fish models, Oryzias latipes, and Oryzias sakaizumii. Employing automated quantification of embryonic heart rates as core metric, we profiled phenotype variability across five inbred strains. We observed maximal phenotypic contrast between individuals of the HO5 and the HdrR strain. HO5 showed elevated heart rates associated with embryonic ventricular hypoplasia and impaired adult cardiac function. This contrast served as the basis for genome-wide mapping. In an F2 segregation population of 1192 HO5 x HdrR embryos, we mapped 59 loci (173 genes) associated with heart rate. Experimental validation of the top 12 candidate genes by gene editing revealed their causal and distinct impact on heart rate, development, ventricle size, and arrhythmia. Our study uncovers new diagnostic and therapeutic targets for developmental and electrophysiological cardiac diseases and provides a novel scalable approach to investigate the intricate genetic architecture of the vertebrate heart.

The role of genetic polymorphisms in KCNN2 in cardiovascular complications in patients with renal failure

Patients with end-stage renal disease (ESRD) are at a higher risk of cardiovascular (CV) complications and mortality compared to the general population. This study aimed to investigate the genetic polymorphisms of KCNN2, a key gene encoding a subtype of small-conductance calcium-activated potassium (SK) channels, which regulate an important SK current pathway potentially involved in the development of CV complications, particularly arrhythmias, in ESRD patients. A total of 169 ESRD patients were enrolled in this study. The patients were divided into two groups based on the presence of CV complications: Group I, consisting of 84 patients without CV complications, and Group II, comprising 85 patients with CV complications. Twelve tagging single nucleotide polymorphisms (tSNPs) in KCNN2 were examined. Polymerase chain reaction (PCR) was performed, and genotyping was correlated with CV complications in each group. The TC and CC genotypes of rs10076582, and the GT and TT genotypes of rs11738819 in the KCNN2 gene, were associated with an increased risk of CV complications in ESRD patients. After adjusting for potential risk factors, these associations remained significant. Additionally, KCNN2 haplotypes with the allele combinations GGCCCTCCGAG and AGTCCTCCGGT were significantly associated with a higher risk of CV complications in ESRD patients. In conclusion, our findings report that specific genetic polymorphisms in the KCNN2 gene, particularly the rs10076582 and rs11738819 variants, as well as GGCCCTCCGAG and AGTCCTCCGGT haplotypes, are significantly associated with an increased risk of cardiovascular complications in ESRD patients. These genetic markers may serve as potential biomarkers for identifying individuals at high risk of cardiovascular complications in this vulnerable population.

Rapid and accurate multi-phenotype imputation for millions of individuals

Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains challenging. In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms. We demonstrate by extensive simulations that PIXANT is reliable, robust and highly resource-efficient. We then apply PIXANT to the UKB data of 277,301 unrelated White British citizens and 425 traits, and GWAS is subsequently performed on the imputed phenotypes, 18.4% more GWAS loci are identified than before imputation (8710 vs 7355). The increased statistical power of GWAS identified some additional candidate genes affecting heart rate, such as RNF220, SCN10A, and RGS6, suggesting that the use of imputed phenotype data from a large cohort may lead to the discovery of additional candidate genes for complex traits.

The impact of common and rare genetic variants on bradyarrhythmia development

To broaden our understanding of bradyarrhythmias and conduction disease, we performed common variant genome-wide association analyses in up to 1.3 million individuals and rare variant burden testing in 460,000 individuals for sinus node dysfunction (SND), distal conduction disease (DCD) and pacemaker (PM) implantation. We identified 13, 31 and 21 common variant loci for SND, DCD and PM, respectively. Four well-known loci (SCN5A/SCN10A, CCDC141, TBX20 and CAMK2D) were shared for SND and DCD, while others were more specific for SND or DCD. SND and DCD showed a moderate genetic correlation (rg = 0.63). Cardiomyocyte-expressed genes were enriched for contributions to DCD heritability. Rare-variant analyses implicated LMNA for all bradyarrhythmia phenotypes, SMAD6 and SCN5A for DCD and TTN, MYBPC3 and SCN5A for PM. These results show that variation in multiple genetic pathways (for example, ion channel function, cardiac developmental programs, sarcomeric structure and cellular homeostasis) appear critical to the development of bradyarrhythmias.

Use of mendelian randomization to assess the causal associations of circulating plasma proteins with 12-lead ECG parameters

BACKGROUND

Cardiac conduction disorders predispose individuals to arrhythmias, currently but the exact mechanisms of cardiac conduction remain elusive. The study sought to identify the causal association between circulating plasma proteins and electrocardiogram (ECG) traits, offer valuable biological insights and clinical guidance into cardiac conduction.

METHODS

Proteome-wide Mendelian randomization (MR) analysis was firstly conducted to assess causal associations between plasma proteins and five ECG traits, including P wave duration (PWD), QRS duration, PR, QT and RR intervals. Multiple sensitivity analyses were implemented. The reverse MR analysis, colocalization analysis and replication analysis were used to consolidate the reliability of our results. Then, we conducted mediation analysis to explore potential mechanism between plasma proteins and ECG traits. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to clarify the biological functions of target proteins. Finally, phenome-wide MR (Phe-MR) and drug databases were searched.

RESULTS

We identified 3 proteins (FAM151A, VEGF165, VEGF121) associated with PWD, 12 proteins (ABHD10, ADK, Cathepsin_S, DUSP13, Ephrin_A3, MAPRE2, OMG, PAM, PMM1, SH3BGRL3, TCP4, SYT11) linked to PR interval, 1 protein (PKC_A) related to QRS duration, and 2 proteins (MXRA7, SVEP1) associated with QT interval. A significant causal effects of ECG traits on them was not found in reverse MR. Colocalization and replication analyses strengthened our findings further. The impacts were partly mediated by anthropometric measures. Enrichment analysis of target proteins mainly enriched for multiple key pathways such as regulation of hydrolase activity and fibronectin binding. Through drug databases searching, 5 identified proteins (VEGFA, ADK, PAM, Cathepsin_S, PKC_A) were considered druggable.

CONCLUSIONS

We discovered significant causal associations between genetically predicted levels of 18 plasma proteins and ECG traits. These results highlight the importance of circulating plasma proteins in cardiac conduction and open up the possibility of novel arrhythmia drug development.

Associations of the serum n-6 PUFA concentrations with exercise-induced myocardial ischaemia in middle-aged and older men

n-6 PUFA, especially linoleic acid (LA) but also arachidonic acid (AA), have been inversely associated with CHD. However, mechanisms underlying these associations are not fully known. We investigated the associations of the serum concentrations of total n-6 PUFA, LA, AA, γ-linolenic acid (GLA) and dihomo-γ-linolenic acid (DGLA), with the odds of myocardial ischaemia during exercise, a predictor of future cardiac events. A total of 1871 men without a history of CHD from the Kuopio Ischaemic Heart Disease Risk Factor Study (KIHD) aged 42-60 years were included. All participants performed a maximal symptom-limited exercise stress test, using an electrically braked bicycle ergometer. Multivariable-adjusted logistic regression was used to assess the OR for exercise-induced myocardial ischaemia in quartiles of the serum n-6 PUFA concentrations. After multivariable adjustment, men in the highest v. the lowest serum AA concentration had 50 % lower odds for exercise-induced myocardial ischaemia (OR 0·50, 95 % CI 0·34, 0·76; P-trend across quartiles < 0·001). For the other PUFA, the OR (95 % CI) were 1·00 (0·69, 1·46; P-trend = 0·89) for LA, 1·07 (0·75, 1·53; P-trend = 0·40) for GLA and 0·74 (0·51, 1·07; P-trend = 0·16) for DGLA. Among the n-6 PUFA, higher serum concentration of AA was associated with lower odds for myocardial ischaemia during an exercise test in middle-aged and older men. This may provide one mechanism for the previously observed possible cardioprotective properties of AA. Our findings also suggest that n-6 PUFA should not be considered as one homogenous group.

Single-cell transcriptome analysis reveals CD34 as a marker of human sinoatrial node pacemaker cardiomyocytes

The sinoatrial node regulates the heart rate throughout life. Failure of this primary pacemaker results in life-threatening, slow heart rhythm. Despite its critical function, the cellular and molecular composition of the human sinoatrial node is not resolved. Particularly, no cell surface marker to identify and isolate sinoatrial node pacemaker cells has been reported. Here we use single-nuclei/cell RNA sequencing of fetal and human pluripotent stem cell-derived sinoatrial node cells to reveal that they consist of three subtypes of pacemaker cells: Core Pacemaker, Sinus Venosus, and Transitional Cells. Our study identifies a host of sinoatrial node pacemaker markers including MYH11, BMP4, and the cell surface antigen CD34. We demonstrate that sorting for CD34+ cells from stem cell differentiation cultures enriches for sinoatrial node cells exhibiting a functional pacemaker phenotype. This sinoatrial node pacemaker cell surface marker is highly valuable for stem cell-based disease modeling, drug discovery, cell replacement therapies, and the targeted delivery of therapeutics to sinoatrial node cells in vivo using antibody-drug conjugates.

Genetic evidence for T-wave area from 12-lead electrocardiograms to monitor cardiovascular diseases in patients taking diabetes medications

Aims Many studies indicated use of diabetes medications can influence the electrocardiogram (ECG), which remains the simplest and fastest tool for assessing cardiac functions. However, few studies have explored the role of genetic factors in determining the relationship between the use of diabetes medications and ECG trace characteristics (ETC). Methods Genome-wide association studies (GWAS) were performed for 168 ETCs extracted from the 12-lead ECGs of 42,340 Europeans in the UK Biobank. The genetic correlations, causal relationships, and phenotypic relationships of these ETCs with medication usage, as well as the risk of cardiovascular diseases (CVDs), were estimated by linkage disequilibrium score regression (LDSC), Mendelian randomization (MR), and regression model, respectively. Results The GWAS identified 124 independent single nucleotide polymorphisms (SNPs) that were study-wise and genome-wide significantly associated with at least one ETC. Regression model and LDSC identified significant phenotypic and genetic correlations of T-wave area in lead aVR (aVR_T-area) with usage of diabetes medications (ATC code: A10 drugs, and metformin), and the risks of ischemic heart disease (IHD) and coronary atherosclerosis (CA). MR analyses support a putative causal effect of the use of diabetes medications on decreasing aVR_T-area, and on increasing risk of IHD and CA. ConclusionPatients taking diabetes medications are prone to have decreased aVR_T-area and an increased risk of IHD and CA. The aVR_T-area is therefore a potential ECG marker for pre-clinical prediction of IHD and CA in patients taking diabetes medications.

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.

Dual color optogenetic tool enables heart arrest, bradycardic, and tachycardic pacing in Drosophila melanogaster

In order to facilitate cardiovascular research to develop non-invasive optical heart pacing methods, we have generated a double-transgenic Drosophila melanogaster (fruit fly) model suitable for optogenetic pacing. We created a fly stock with both excitatory H134R-ChR2 and inhibitory eNpHR2.0 opsin transgenes. Opsins were expressed in the fly heart using the Hand-GAL4 driver. Here we describe Hand > H134R-ChR2; eNpHR2.0 model characterization including bi-directional heart control (activation and inhibition) upon illumination of light with distinct wavelengths. Optical control and real-time visualization of the heart function were achieved non-invasively using an integrated light stimulation and optical coherence microscopy (OCM) system. OCM produced high-speed and high-resolution imaging; simultaneously, the heart function was modulated by blue (470 nm) or red (617 nm) light pulses causing tachycardia, bradycardia and restorable cardiac arrest episodes in the same animal. The irradiance power levels and illumination schedules were optimized to achieve successful non-invasive bi-directional heart pacing in Drosophila larvae and pupae.

Symptomatic bradyarrhythmias in the athlete-Underlying mechanisms and treatments

Bradyarrhythmias including sinus bradycardia and atrioventricular (AV) block are frequently encountered in endurance athletes especially at night. While these are well tolerated by the young athlete, there is evidence that generally from the fifth decade of life onward, such arrhythmias can degenerate into pathological symptomatic bradycardia requiring pacemaker therapy. For many years, athletic bradycardia and AV block have been attributed to high vagal tone, but work from our group has questioned this widely held assumption and demonstrated a role for intrinsic electrophysiological remodeling of the sinus node and the AV node. In this article, we argue that bradyarrhythmias in the veteran athlete arise from the cumulative effects of exercise training, the circadian rhythm and aging on the electrical activity of the nodes. We consider contemporary strategies for the treatment of symptomatic bradyarrhythmias in athletes and highlight potential therapies resulting from our evolving mechanistic understanding of this phenomenon.

Genetic and polygenic investigation of heart rate variability to identify biomarkers associated with Anxiety disorders

Given that anxiety disorders (AD) are associated with reduced vagally-mediated heart rate variability (HRV), genetic variants related to HRV may provide insight into anxiety etiology. This study used polygenic risk scores (PRS) to explore the genetic overlap between AD and HRV, and investigated whether HRV-related polymorphisms influence anxiety risk. Resting vagally-mediated HRV was measured using a wearable device in 188 European individuals (AD=101, healthy controls=87). AD PRS was tested for association with resting HRV, and HRV PRS for association with AD. We also investigated 15 significant hits from an HRV genome-wide association study (GWAS) for association with resting HRV and AD and if this association is mediated through resting HRV. The AD PRS and HRV PRS showed nominally significant associations with resting HRV and anxiety disorders, respectively. HRV GWAS variants associated with resting HRV were rs12980262 (NDUFA11), rs2680344 (HCN4), rs4262 and rs180238 (GNG11), and rs10842383 (LINC00477). Mediation analyses revealed that NDUFA11 rs12980262 A-carriers and GNG11 rs180238 and rs4262 C-carriers had higher anxiety risk through lower HRV. This study supports an anxiety-HRV genetic relationship, with HRV-related genetic variants translating to AD. This study encourages exploration of HRV genetics to understand mechanisms and identify novel treatment targets for anxiety.

Exploring the impact of electrocardiographic parameters on the risk of common arrhythmias: a two-sample Mendelian randomization study

Background

Observational studies have shown that heart rate (HR), heart rate variability (HRV), P-wave terminal force, P-wave duration, T-wave amplitude and PR interval are associated with risk factors for atrial fibrillation (AF) or bradycardia. Arrhythmias are associated with many causes of hospitalization. However, observational studies are susceptible to confounding factors that have not yet been identified. The objective of this study was to clarify the causal relationships by Mendelian randomization analysis.

Methods

We conducted a two-sample and multivariate Mendelian randomization (MVMR) analysis using genome-wide association study (GWAS) data from a European population to assess the total and direct causal effects of HR, three HRV traits, P-wave terminal force, P-wave duration, T-wave top amplitude in five-lead modes, and the PR interval on the risk of AF (N=191,205), bradycardia (N=463,010), and supraventricular tachycardia (SVT) (N=463,010).

Results

The results of the univariate MR analysis revealed the following significant causal effects: the higher the genetically predicted PR interval, the lower the risk of AF; the higher the HR and T-wave top amplitude (aVR leads and V3 + V4 + aVL leads), the lower the risk of bradycardia; and the higher HR and the lower PR interval, the higher the risk of SVT. The multivariate MR results indicated that the HRV_standard deviation of the normal-to-normal (SDNN) interval had an independent causal effect on the risk of AF [odds ratio (OR): 0.515; 95% confidence interval (CI): 0.278-0.954; P=0.03], and the T-wave top amplitude in the aVR leads (OR: 0.998; 95% CI: 0.996-0.999; P<0.001) and the HRV_SDNN (OR: 0.988; 95% CI: 0.976-1.000; P=0.045) had independent causal effects on the risk of bradycardia.

Conclusions

The HRV_SDNN had an independent causal effect on AF, while the HRV_SDNN and T-wave top amplitude in the aVR leads had independent causal effects on bradycardia, which suggests that some of the electrocardiographic parameters have preventive effects on the incidence of AF and bradycardia.

Causal effect of beta-blockers on the risk of lung cancer: a Mendelian randomization study

Background

It remains uncertain whether there is a causal association of the use of beta-blockers (BBs) on lung cancer risk. We used a two-sample Mendelian randomization (MR) approach to identify the causal association of BBs and lung cancer risk.

Methods

Twenty-two BB-related single-nucleotide polymorphisms (SNPs) were obtained from the UK Biobank as the instrumental variables (IVs). Genetic summary data information of lung cancer was extracted from the International Lung Cancer Consortium, with a total of 11,348 cases and 15,861 controls. We adopted the inverse-variance weighted (IVW) approach to conduct the MR analyses. Egger-intercept analysis was further performed as sensitivity analysis for pleiotropy evaluation. Additionally, we investigated whether BBs could causally affect the risk of lung cancer through their pharmacological effects.

Results

The current IVW analysis suggested a decreased lung cancer risk in BB users [odds ratio (OR) =0.83; 95% confidence interval (CI): 0.73-0.95; P<0.01]. Results of Egger-intercept analysis demonstrated that no pleiotropy was found (P=0.94), which suggested the robustness of the causality. However, there was little evidence that pharmacological effects mediate the association between BBs and lung cancer.

Conclusions

The current analysis suggested that BBs could decrease the risk of lung cancer but may be not via its pharmacological effects. Further research is in need for elucidating the underlying mechanisms.

Natural genetic variation quantitatively regulates heart rate and dimension

The polygenic contribution to heart development and function along the health-disease continuum remains unresolved. To gain insight into the genetic basis of quantitative cardiac phenotypes, we utilize highly inbred Japanese rice fish models, Oryzias latipes, and Oryzias sakaizumii. Employing automated quantification of embryonic heart rates as core metric, we profiled phenotype variability across five inbred strains. We observed maximal phenotypic contrast between individuals of the HO5 and the HdrR strain. HO5 showed elevated heart rates associated with embryonic ventricular hypoplasia and impaired adult cardiac function. This contrast served as the basis for genome-wide mapping. In a segregation population of 1192 HO5 x HdrR F2 embryos, we mapped 59 loci (173 genes) associated with heart rate. Experimental validation of the top 12 candidate genes in loss-of-function models revealed their causal and distinct impact on heart rate, development, ventricle size, and arrhythmia. Our study uncovers new diagnostic and therapeutic targets for developmental and electrophysiological cardiac diseases and provides a novel scalable approach to investigate the intricate genetic architecture of the vertebrate heart.

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 Studies of Retinal Vessel Tortuosity Identify Numerous Novel Loci Revealing Genes and Pathways Associated With Ocular and Cardiometabolic Diseases

Purpose

To identify novel susceptibility loci for retinal vascular tortuosity, to better understand the molecular mechanisms modulating this trait, and reveal causal relationships with diseases and their risk factors.

Design

Genome-wide Association Studies (GWAS) of vascular tortuosity of retinal arteries and veins followed by replication meta-analysis and Mendelian randomization (MR).

Participants

We analyzed 116 639 fundus images of suitable quality from 63 662 participants from 3 cohorts, namely the UK Biobank (n = 62 751), the Swiss Kidney Project on Genes in Hypertension (n = 397), and OphtalmoLaus (n = 512).

Methods

Using a fully automated retina image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, we computed the median arterial, venous and combined vessel tortuosity measured by the distance factor (the length of a vessel segment over its chord length), as well as by 6 alternative measures that integrate over vessel curvature. We then performed the largest GWAS of these traits to date and assessed gene set enrichment using the novel high-precision statistical method PascalX.

Main Outcome Measure

We evaluated the genetic association of retinal tortuosity, measured by the distance factor.

Results

Higher retinal tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, metacohort. We estimated heritability at ∼25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 116 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that retinal tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, MR revealed causal effects between tortuosity, body mass index, and low-density lipoprotein.

Conclusions

Several alleles associated with retinal vessel tortuosity suggest a common genetic architecture of this trait with ocular diseases (glaucoma, myopia), cardiovascular diseases, and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images.

Financial Disclosures

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Genetic insights into resting heart rate and its role in cardiovascular disease

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

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.

Genome and atrial fibrillation

Atrial fibrillation (AF), the most common type of arrhythmia, can cause several adverse effects, such as stroke, heart failure, and cognitive dysfunction, also in addition to reducing quality of life and increasing mortality. Evidence suggests that AF is caused by a combination of genetic and clinical predispositions. In line with this, genetic studies on AF have progressed significantly through linkage studies, genome-wide association studies, use of polygenic risk scores, and studies on rare coding variations, gradually elucidating the relationship between genes and the pathogenesis and prognosis of AF. This article will review current trends in genetic analysis concerning AF.

The role of P21-activated kinase (Pak1) in sinus node function

Sinoatrial node (SAN) dysfunction (SND) and atrial arrhythmia frequently occur simultaneously with a hazard ratio of 4.2 for new onset atrial fibrillation (AF) in SND patients. In the atrial muscle attenuated activity of p21-activated kinase 1 (Pak1) increases the risk for AF by enhancing NADPH oxidase 2 dependent production of reactive oxygen species (ROS). However, the role of Pak1 dependent ROS regulation in SAN function has not yet been determined. We hypothesize that Pak1 activity maintains SAN activity by regulating the expression of the hyperpolarization activated cyclic nucleotide gated cation channel (HCN). To determine Pak1 dependent changes in heart rate (HR) regulation we quantified the intrinsic sinus rhythm in wild type (WT) and Pak1 deficient (Pak1-/-) mice of both sexes in vivo and in isolated Langendorff perfused hearts. Pak1-/- hearts displayed an attenuated HR in vivo after autonomic blockage and in isolated hearts. The contribution of the Ca2+ clock to pacemaker activity remained unchanged, but Ivabradine (3 μM), a blocker of HCN channels that are a membrane clock component, eliminated the differences in SAN activity between WT and Pak1-/- hearts. Reduced HCN4 expression was confirmed in Pak1-/- right atria. The reduced HCN activity in Pak1-/- could be rescued by class II HDAC inhibition (LMK235), ROS scavenging (TEMPOL) or attenuation of Extracellular Signal-Regulated Kinase (ERK) 1/2 activity (SCH772984). No sex specific differences in Pak1 dependent SAN regulation were determined. Our results establish Pak1 as a class II HDAC regulator and a potential therapeutic target to attenuate SAN bradycardia and AF susceptibility.

The opportunities and challenges of using Drosophila to model human cardiac diseases

The Drosophila heart tube seems simple, yet it has notable anatomic complexity and contains highly specialized structures. In fact, the development of the fly heart tube much resembles that of the earliest stages of mammalian heart development, and the molecular-genetic mechanisms driving these processes are highly conserved between flies and humans. Combined with the fly's unmatched genetic tools and a wide variety of techniques to assay both structure and function in the living fly heart, these attributes have made Drosophila a valuable model system for studying human heart development and disease. This perspective focuses on the functional and physiological similarities between fly and human hearts. Further, it discusses current limitations in using the fly, as well as promising prospects to expand the capabilities of Drosophila as a research model for studying human cardiac diseases.

Conventional and genetic associations between resting heart rate, cardiac morphology and function as assessed by magnetic resonance imaging: Insights from the UK biobank population study

Aim

To examine the direction, strength and causality of the associations of resting heart rate (RHR) with cardiac morphology and function in 20,062 UK Biobank participants.

Methods and results

Participants underwent cardiac magnetic resonance (CMR) and we extracted CMR biventricular structural and functional metrics using automated pipelines. Multivariate linear regression adjusted for the main cardiovascular risk factors and Two-sample Mendelian Randomization analyses were performed to assess the potential relationship, grouped by heart rate and stratified by sex. Each 10 beats per minute increase in RHR was linked with smaller ventricular structure (lower biventricular end-diastolic volume and end-systolic volume), poorer left ventricular (LV) function (lower LV ejection fraction, global longitude strain and global function index) and unhealthy pattern of LV remodeling (higher values of myocardial contraction fraction), but there is no statistical difference in LV wall thickness. These trends are more pronounced among males and consistent with the causal effect direction of genetic variants interpretation. These observations reflect that RHR has an independent and broad impact on LV remodeling, however, genetically-predicted RHR is not statistically related to heart failure.

Conclusion

We demonstrate higher RHR cause smaller ventricular chamber volume, poorer systolic function and unhealthy cardiac remodeling pattern. Our findings provide effective evidence for the potential mechanism of cardiac remodeling and help to explore the potential scope or benefit of intervention.

Toxicity assessment of hexafluoropropylene oxide-dimer acid on morphology, heart physiology, and gene expression during zebrafish (Danio rerio) development

Hexafluoropropylene oxide-dimer acid (HFPO-DA) is one of the emerging replacements for the "forever" carcinogenic and toxic long-chain PFAS. HFPO-DA is a polymerization aid used for manufacturing fluoropolymers, whose global distribution and undetermined toxic properties are a concern regarding human and ecological health. To assess embryotoxic potential, zebrafish embryos were exposed to HFPO-DA at concentrations of 0.5-20,000 mg/L at 24-, 48-, and 72-h post-fertilization (hpf). Heart rate increased significantly in embryos exposed to 2 mg/L and 10 mg/L HFPO-DA across all time points. Spinal deformities and edema phenotypes were evident among embryos exposed to 1000-16,000 mg/L HFPO-DA at 72 hpf. A median lethal concentration (LC₅₀) was derived as 7651 mg/L at 72 hpf. Shallow RNA sequencing analysis of 9465 transcripts identified 38 consistently differentially expressed genes at 0.5 mg/L, 1 mg/L, 2 mg/L, and 10 mg/L HFPO-DA exposures. Notably, seven downregulated genes were associated with visual response, and seven upregulated genes were expressed in or regulated the cardiovascular system. This study identifies biological targets and molecular pathways affected during animal development by an emerging, potentially problematic, and ubiquitous industrial chemical.

Identifying shared genetic factors underlying epilepsy and congenital heart disease in Europeans

Epilepsy (EP) and congenital heart disease (CHD) are two apparently unrelated diseases that nevertheless display substantial mutual comorbidity. Thus, while congenital heart defects are associated with an elevated risk of developing epilepsy, the incidence of epilepsy in CHD patients correlates with CHD severity. Although genetic determinants have been postulated to underlie the comorbidity of EP and CHD, the precise genetic etiology is unknown. We performed variant and gene association analyses on EP and CHD patients separately, using whole exomes of genetically identified Europeans from the UK Biobank and Mount Sinai BioMe Biobank. We prioritized biologically plausible candidate genes and investigated the enriched pathways and other identified comorbidities by biological proximity calculation, pathway analyses, and gene-level phenome-wide association studies. Our variant- and gene-level results point to the Voltage-Gated Calcium Channels (VGCC) pathway as being a unifying framework for EP and CHD comorbidity. Additionally, pathway-level analyses indicated that the functions of disease-associated genes partially overlap between the two disease entities. Finally, phenome-wide association analyses of prioritized candidate genes revealed that cerebral blood flow and ulcerative colitis constitute the two main traits associated with both EP and CHD.

Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction

Atrial fibrillation (AF) is a common cardiac arrhythmia resulting in increased risk of stroke. Despite highly heritable etiology, our understanding of the genetic architecture of AF remains incomplete. Here we performed a genome-wide association study in the Japanese population comprising 9,826 cases among 150,272 individuals and identified East Asian-specific rare variants associated with AF. A cross-ancestry meta-analysis of >1 million individuals, including 77,690 cases, identified 35 new susceptibility loci. Transcriptome-wide association analysis identified IL6R as a putative causal gene, suggesting the involvement of immune responses. Integrative analysis with ChIP-seq data and functional assessment using human induced pluripotent stem cell-derived cardiomyocytes demonstrated ERRg as having a key role in the transcriptional regulation of AF-associated genes. A polygenic risk score derived from the cross-ancestry meta-analysis predicted increased risks of cardiovascular and stroke mortalities and segregated individuals with cardioembolic stroke in undiagnosed AF patients. Our results provide new biological and clinical insights into AF genetics and suggest their potential for clinical applications.

Role of G-Proteins and GPCRs in Cardiovascular Pathologies

Cell signaling is a fundamental process that enables cells to survive under various ecological and environmental contexts and imparts tolerance towards stressful conditions. The basic machinery for cell signaling includes a receptor molecule that senses and receives the signal. The primary form of the signal might be a hormone, light, an antigen, an odorant, a neurotransmitter, etc. Similarly, heterotrimeric G-proteins principally provide communication from the plasma membrane G-protein-coupled receptors (GPCRs) to the inner compartments of the cells to control various biochemical activities. G-protein-coupled signaling regulates different physiological functions in the targeted cell types. This review article discusses G-proteins' signaling and regulation functions and their physiological relevance. In addition, we also elaborate on the role of G-proteins in several cardiovascular diseases, such as myocardial ischemia, hypertension, atherosclerosis, restenosis, stroke, and peripheral artery disease.

Associations of common genetic risk variants of the muscarinic acetylcholine receptor M2 with cardiac autonomic dysfunction in patients with schizophrenia

OBJECTIVES

Decreased vagal modulation, which has consistently been observed in schizophrenic patients, might contribute to increased cardiac mortality in schizophrenia. Previously, associations between CHRM2 (Cholinergic Receptor Muscarinic 2) and cardiac autonomic features have been reported. Here, we tested for possible associations between these polymorphisms and heart rate variability in patients with schizophrenia.

METHODS

A total of three single nucleotide polymorphisms (SNPs) in CHRM2 (rs73158705 A>G, rs8191992 T>A and rs2350782 T>C) that achieved significance (p < 5 * 10^-8) in genome-wide association studies for cardiac autonomic features were genotyped in 88 drug-naïve patients, 61 patients receiving antipsychotic medication and 144 healthy controls. Genotypes were analysed for associations with parameters of heart rate variability and complexity, in each diagnostic group.

RESULTS

We observed a significantly altered heart rate variability in unmedicated patients with identified genetic risk status in rs73158705 A>G, rs8191992 T>A and rs2350782 T>C as compared to genotype non-risk status. In patients receiving antipsychotic medication and healthy controls, these associations were not observed.

DISCUSSION

We report novel candidate genetic associations with cardiac autonomic dysfunction in schizophrenia, but larger cohorts are required for replication.

Animal models and animal-free innovations for cardiovascular research: current status and routes to be explored. Consensus document of the ESC Working Group on Myocardial Function and the ESC Working Group on Cellular Biology of the Heart

Cardiovascular diseases represent a major cause of morbidity and mortality, necessitating research to improve diagnostics, and to discover and test novel preventive and curative therapies, all of which warrant experimental models that recapitulate human disease. The translation of basic science results to clinical practice is a challenging task, in particular for complex conditions such as cardiovascular diseases, which often result from multiple risk factors and comorbidities. This difficulty might lead some individuals to question the value of animal research, citing the translational 'valley of death', which largely reflects the fact that studies in rodents are difficult to translate to humans. This is also influenced by the fact that new, human-derived in vitro models can recapitulate aspects of disease processes. However, it would be a mistake to think that animal models do not represent a vital step in the translational pathway as they do provide important pathophysiological insights into disease mechanisms particularly on an organ and systemic level. While stem cell-derived human models have the potential to become key in testing toxicity and effectiveness of new drugs, we need to be realistic, and carefully validate all new human-like disease models. In this position paper, we highlight recent advances in trying to reduce the number of animals for cardiovascular research ranging from stem cell-derived models to in situ modelling of heart properties, bioinformatic models based on large datasets, and state-of-the-art animal models, which show clinically relevant characteristics observed in patients with a cardiovascular disease. We aim to provide a guide to help researchers in their experimental design to translate bench findings to clinical routine taking the replacement, reduction, and refinement (3R) as a guiding concept.

GJA1 gene polymorphism is a genetic predictor of recurrence after pulmonary vein isolation in patients with paroxysmal atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) and recurrence of AF after pulmonary vein isolation (PVI) have been linked to sinus node dysfunction.

OBJECTIVE

The purpose of this study was to investigate the association between the heart rate-associated single nucleotide polymorphisms (SNPs) identified in genome-wide association studies and recurrence of AF after PVI.

METHODS

In this study, patients with paroxysmal AF who underwent initial PVI, including 522 patients for screening and 172 patients for replication, were recruited and 21 heart rate-associated SNPs identified in genome-wide association studies were genotyped. The association between these SNPs and the recurrence of AF was investigated.

RESULTS

Throughout the follow-up period of 21 ± 12 months, 119 patients with paroxysmal AF (22.8%) exhibited AF recurrences in the screening set. The rate of AF recurrence was significantly associated with the minor allele C of the gap junction alpha-1 protein (GJA1) rs1015451 (additive model: odds ratio 2.07; P = 9.32 × 10^-7), but not with other SNPs. This association was confirmed in the replication set (allelic model: odds ratio 1.81; P = 2.70 × 10^-2). Multivariate analysis revealed that the recurrence of AF after AF ablation was independently related to the GJA1 SNP rs1015451 additive model, duration of AF >1 year, AF from non-pulmonary vein foci, and thicker interventricular septum.

CONCLUSION

The GJA1 SNP rs1015451, coding for a gap junction protein (connexin-43), may be considered a novel genetic marker for AF recurrence after PVI.

Slowing Heart Rate Protects Against Pathological Cardiac Hypertrophy

We aimed to determine the pathophysiological impact of heart rate (HR) slowing on cardiac function. We have recently developed a murine model in which it is possible to conditionally delete the stimulatory heterotrimeric G-protein (Gα_s) in the sinoatrial (SA) node after the addition of tamoxifen using cre-loxP technology. The addition of tamoxifen leads to bradycardia. We used this approach to examine the physiological and pathophysiological effects of HR slowing. We first looked at the impact on exercise performance by running the mice on a treadmill. After the addition of tamoxifen, mice with conditional deletion of Gα_s in the SA node ran a shorter distance at a slower speed. Littermate controls preserved their exercise capacity after tamoxifen. Results consistent with impaired cardiac capacity in the mutants were also obtained with a dobutamine echocardiographic stress test. We then examined if HR reduction influenced pathological cardiac hypertrophy using two models: ligation of the left anterior descending coronary artery for myocardial infarction and abdominal aortic banding for hypertensive heart disease. In littermate controls, both procedures resulted in cardiac hypertrophy. However, induction of HR reduction prior to surgical intervention significantly ameliorated the hypertrophy. In order to assess potential protein kinase pathways that may be activated in the left ventricle by relative bradycardia, we used a phospho-antibody array and this revealed selective activation of phosphoinositide-3 kinase. In conclusion, HR reduction protects against pathological cardiac hypertrophy but limits physiological exercise capacity.

The Athlete's Heart-Challenges and Controversies: JACC Focus Seminar 4/4

Regular exercise promotes structural, functional, and electrical remodeling of the heart, often referred to as the "athlete's heart," with intense endurance sports being associated with the greatest degree of cardiac remodeling. However, the extremes of exercise-induced cardiac remodeling are potentially associated with uncommon side effects. Atrial fibrillation is more common among endurance athletes and there is speculation that other arrhythmias may also be more prevalent. It is yet to be determined whether this arrhythmic susceptibility is a result of extreme exercise remodeling, genetic predisposition, or other factors. Gender may have the greatest influence on the cardiac response to exercise, but there has been far too little research directed at understanding differences in the sportsman's vs sportswoman's heart. Here in part 4 of a 4-part seminar series, the controversies and ambiguities regarding the athlete's heart, and in particular, its arrhythmic predisposition, genetic, and gender influences are reviewed in depth.

Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOL

BACKGROUND

Obstructive Sleep Apnoea (OSA) often co-occurs with cardiometabolic and pulmonary diseases. This study is to apply genetic analysis methods to explain the associations between OSA and related phenotypes.

METHODS

In the Hispanic Community Healthy Study/Study of Latinos, we estimated genetic correlations ρ_g between the respiratory event index (REI) and 54 anthropometric, glycemic, cardiometabolic, and pulmonary phenotypes. We used summary statistics from published genome-wide association studies to construct Polygenic Risk Scores (PRSs) representing the genetic basis of each correlated phenotype (ρ_g>0.2 and p-value<0.05), and of OSA. We studied the association of the PRSs of the correlated phenotypes with both REI and OSA (REI≥5), and the association of OSA PRS with the correlated phenotypes. Causal relationships were tested using Mendelian Randomization (MR) analysis.

FINDINGS

The dataset included 11,155 participants, 31.03% with OSA. 22 phenotypes were genetically correlated with REI. 10 PRSs covering obesity and fat distribution (BMI, WHR, WHRadjBMI), blood pressure (DBP, PP, MAP), glycaemic control (fasting insulin, HbA1c, HOMA-B) and insomnia were associated with REI and/or OSA. OSA PRS was associated with BMI, WHR, DBP and glycaemic traits (fasting insulin, HbA1c, HOMA-B and HOMA-IR). MR analysis identified robust causal effects of BMI and WHR on OSA, and probable causal effects of DBP, PP, and HbA1c on OSA/REI.

INTERPRETATION

There are shared genetic underpinnings of anthropometric, blood pressure, and glycaemic phenotypes with OSA, with evidence for causal relationships between some phenotypes.

FUNDING

Described in Acknowledgments.

Identification and single-base gene-editing functional validation of a cis-EPO variant as a genetic predictor for EPO-increasing therapies

Hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHIs) are currently under clinical development for treating anemia in chronic kidney disease (CKD), but it is important to monitor their cardiovascular safety. Genetic variants can be used as predictors to help inform the potential risk of adverse effects associated with drug treatments. We therefore aimed to use human genetics to help assess the risk of adverse cardiovascular events associated with therapeutically altered EPO levels to help inform clinical trials studying the safety of HIF-PHIs. By performing a genome-wide association meta-analysis of EPO (n = 6,127), we identified a cis-EPO variant (rs1617640) lying in the EPO promoter region. We validated this variant as most likely causal in controlling EPO levels by using genetic and functional approaches, including single-base gene editing. Using this variant as a partial predictor for therapeutic modulation of EPO and large genome-wide association data in Mendelian randomization tests, we found no evidence (at p < 0.05) that genetically predicted long-term rises in endogenous EPO, equivalent to a 2.2-unit increase, increased risk of coronary artery disease (CAD, OR [95% CI] = 1.01 [0.93, 1.07]), myocardial infarction (MI, OR [95% CI] = 0.99 [0.87, 1.15]), or stroke (OR [95% CI] = 0.97 [0.87, 1.07]). We could exclude increased odds of 1.15 for cardiovascular disease for a 2.2-unit EPO increase. A combination of genetic and functional studies provides a powerful approach to investigate the potential therapeutic profile of EPO-increasing therapies for treating anemia in CKD.

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 (HRRpred) among UK Biobank participants who had undergone exercise testing. We examined the association of HRRpred with incident cardiovascular disease using Cox models, and investigated the genetic architecture of HRRpred in genome-wide association analysis.

Results

Among 56,793 individuals (mean age 57 years, 51% women), the HRRpred 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 HRRpred 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 HRRpred with incident DM and all-cause mortality were similar. Genetic determinants of HRRpred 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.

Prediction of type 2 diabetes mellitus onset using logistic regression-based scorecards

Background

Type 2 diabetes (T2D) accounts for ~90% of all cases of diabetes, resulting in an estimated 6.7 million deaths in 2021, according to the International Diabetes Federation. Early detection of patients with high risk of developing T2D can reduce the incidence of the disease through a change in lifestyle, diet, or medication. Since populations of lower socio-demographic status are more susceptible to T2D and might have limited resources or access to sophisticated computational resources, there is a need for accurate yet accessible prediction models.

Methods

In this study, we analyzed data from 44,709 nondiabetic UK Biobank participants aged 40-69, predicting the risk of T2D onset within a selected time frame (mean of 7.3 years with an SD of 2.3 years). We started with 798 features that we identified as potential predictors for T2D onset. We first analyzed the data using gradient boosting decision trees, survival analysis, and logistic regression methods. We devised one nonlaboratory model accessible to the general population and one more precise yet simple model that utilizes laboratory tests. We simplified both models to an accessible scorecard form, tested the models on normoglycemic and prediabetes subcohorts, and compared the results to the results of the general cohort. We established the nonlaboratory model using the following covariates: sex, age, weight, height, waist size, hip circumference, waist-to-hip ratio, and body mass index. For the laboratory model, we used age and sex together with four common blood tests: high-density lipoprotein (HDL), gamma-glutamyl transferase, glycated hemoglobin, and triglycerides. As an external validation dataset, we used the electronic medical record database of Clalit Health Services.

Results

The nonlaboratory scorecard model achieved an area under the receiver operating curve (auROC) of 0.81 (95% confidence interval [CI] 0.77-0.84) and an odds ratio (OR) between the upper and fifth prevalence deciles of 17.2 (95% CI 5-66). Using this model, we classified three risk groups, a group with 1% (0.8-1%), 5% (3-6%), and the third group with a 9% (7-12%) risk of developing T2D. We further analyzed the contribution of the laboratory-based model and devised a blood test model based on age, sex, and the four common blood tests noted above. In this scorecard model, we included age, sex, glycated hemoglobin (HbA1c%), gamma glutamyl-transferase, triglycerides, and HDL cholesterol. Using this model, we achieved an auROC of 0.87 (95% CI 0.85-0.90) and a deciles' OR of ×48 (95% CI 12-109). Using this model, we classified the cohort into four risk groups with the following risks: 0.5% (0.4-7%); 3% (2-4%); 10% (8-12%); and a high-risk group of 23% (10-37%) of developing T2D. When applying the blood tests model using the external validation cohort (Clalit), we achieved an auROC of 0.75 (95% CI 0.74-0.75). We analyzed several additional comprehensive models, which included genotyping data and other environmental factors. We found that these models did not provide cost-efficient benefits over the four blood test model. The commonly used German Diabetes Risk Score (GDRS) and Finnish Diabetes Risk Score (FINDRISC) models, trained using our data, achieved an auROC of 0.73 (0.69-0.76) and 0.66 (0.62-0.70), respectively, inferior to the results achieved by the four blood test model and by the anthropometry models.

Conclusions

The four blood test and anthropometric models outperformed the commonly used nonlaboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset.

Funding

The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.

Observational and Genetic Associations of Modifiable Risk Factors with Aortic Valve Stenosis: A Prospective Cohort Study of 0.5 Million Participants

Background: Observational studies have shown that modifiable risk factors are associated with aortic valve stenosis (AVS). However, the causality behind these associations remains largely unknown. Objectives: To explore the associations of modifiable risk factors, including metabolic factors, biochemical measures, education, and lifestyles with AVS and their potential causal associations. Methods: We enrolled 361,930 British white people with genetic data in the UK biobank. Cox proportional risk regression models were used to estimate the hazard ratios between 28 modifiable risk factors and AVS. We used genetic instruments for modifiable risk factors to determine the potential causal relationships using a one-sample Mendelian randomization (MR) approach. Results: A total of 1602 participants developed AVS during an 8.4-year follow-up. Observational analyses showed higher adiposity, blood pressure, heart rate, low-density lipoprotein, urate, C-reactive protein, creatinine, albumin, and glycated hemoglobin, but lower serum vitamin D, and education, unhealthy lifestyle, and poor sleep quality were related to a higher risk of AVS after adjusting for the Bonferroni correction (p < 0.0013). Genetically predicted 1-SD higher levels of body mass index [HR: 1.09, 95% CI: 1.03 to 1.16], body fat percentage (1.17, 1.03 to 1.33), triglyceride (TG) [1.08, 1.00 to 1.16], low-density lipoprotein (LDL) (1.15, 1.08 to 1.21) and serum total cholesterol (TC) (1.13, 1.02 to 1.25) were associated with a higher risk of AVS, respectively. Genetically determined per category higher insomnia (1.32, 1.13 to 1.55) was also associated with AVS. The abovementioned genetic associations with the incident AVS showed an increasing relationship pattern. Conclusions: This study provides strong evidence for the potential causal roles of cardiometabolic factors in developing AVS, highlighting that an idea of metabolic status through a healthy lifestyle may help prevent AVS.

Resting heart rate and incident atrial fibrillation: A stratified Mendelian randomization in the AFGen consortium

Background

Both elevated and low resting heart rates are associated with atrial fibrillation (AF), suggesting a U-shaped relationship. However, evidence for a U-shaped causal association between genetically-determined resting heart rate and incident AF is limited. We investigated potential directional changes of the causal association between genetically-determined resting heart rate and incident AF.

Method and results

Seven cohorts of the AFGen consortium contributed data to this meta-analysis. All participants were of European ancestry with known AF status, genotype information, and a heart rate measurement from a baseline electrocardiogram (ECG). Three strata of instrumental variable-free resting heart rate were used to assess possible non-linear associations between genetically-determined resting heart rate and the logarithm of the incident AF hazard rate: <65; 65–75; and >75 beats per minute (bpm). Mendelian randomization analyses using a weighted resting heart rate polygenic risk score were performed for each stratum.

We studied 38,981 individuals (mean age 59±10 years, 54% women) with a mean resting heart rate of 67±11 bpm. During a mean follow-up of 13±5 years, 4,779 (12%) individuals developed AF. A U-shaped association between the resting heart rate and the incident AF-hazard ratio was observed. Genetically-determined resting heart rate was inversely associated with incident AF for instrumental variable-free resting heart rates below 65 bpm (hazard ratio for genetically-determined resting heart rate, 0.96; 95% confidence interval, 0.94–0.99; p = 0.01). Genetically-determined resting heart rate was not associated with incident AF in the other two strata.

Conclusions

For resting heart rates below 65 bpm, our results support an inverse causal association between genetically-determined resting heart rate and incident AF.

Genome-wide association study reveals novel genetic loci: a new polygenic risk score for mitral valve prolapse

AIMS

Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder.

METHODS AND RESULTS

We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors.

CONCLUSION

We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention.

The HERITAGE Family Study: A Review of the Effects of Exercise Training on Cardiometabolic Health, with Insights into Molecular Transducers

The aim of the HERITAGE Family Study was to investigate individual differences in response to a standardized endurance exercise program, the role of familial aggregation, and the genetics of response levels of cardiorespiratory fitness and cardiovascular disease and diabetes risk factors. Here we summarize the findings and their potential implications for cardiometabolic health and cardiorespiratory fitness. It begins with overviews of background and planning, recruitment, testing and exercise program protocol, quality control measures, and other relevant organizational issues. A summary of findings is then provided on cardiorespiratory fitness, exercise hemodynamics, insulin and glucose metabolism, lipid and lipoprotein profiles, adiposity and abdominal visceral fat, blood levels of steroids and other hormones, markers of oxidative stress, skeletal muscle morphology and metabolic indicators, and resting metabolic rate. These summaries document the extent of the individual differences in response to a standardized and fully monitored endurance exercise program and document the importance of familial aggregation and heritability level for exercise response traits. Findings from genomic markers, muscle gene expression studies, and proteomic and metabolomics explorations are reviewed, along with lessons learned from a bioinformatics-driven analysis pipeline. The new opportunities being pursued in integrative -omics and physiology have extended considerably the expected life of HERITAGE and are being discussed in relation to the original conceptual model of the study.

Separating the direct effects of traits on atherosclerotic cardiovascular disease from those mediated by type 2 diabetes

AIMS/HYPOTHESIS

Type 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes.

METHODS

Our main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD.

RESULTS

Eight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%).

CONCLUSIONS/INTERPRETATION

Most traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual's liability to type 2 diabetes.

Computational estimates of annular diameter reveal genetic determinants of mitral valve function and disease

The fibrous annulus of the mitral valve plays an important role in valvular function and cardiac physiology, while normal variation in the size of cardiovascular anatomy may share a genetic link with common and rare disease. We derived automated estimates of mitral valve annular diameter in the 4-chamber view from 32,220 MRI images from the UK Biobank at ventricular systole and diastole as the basis for GWAS. Mitral annular dimensions corresponded to previously described anatomical norms, and GWAS inclusive of 4 population strata identified 10 loci, including possibly novel loci (GOSR2, ERBB4, MCTP2, MCPH1) and genes related to cardiac contractility (BAG3, TTN, RBFOX1). ATAC-Seq of primary mitral valve tissue localized multiple variants to regions of open chromatin in biologically relevant cell types and rs17608766 to an algorithmically predicted enhancer element in GOSR2. We observed strong genetic correlation with measures of contractility and mitral valve disease and clinical correlations with heart failure, cerebrovascular disease, and ventricular arrhythmias. Polygenic scoring of mitral valve annular diameter in systole was predictive of risk mitral valve prolapse across 4 cohorts. In summary, genetic and clinical studies of mitral valve annular diameter revealed genetic determinants of mitral valve biology, while highlighting clinical associations. Polygenic determinants of mitral valve annular diameter may represent an independent risk factor for mitral prolapse. Overall, computationally estimated phenotypes derived at scale from medical imaging represent an important substrate for genetic discovery and clinical risk prediction.

CRISPR-Cas9 induces large structural variants at on-target and off-target sites in vivo that segregate across generations

CRISPR-Cas9 genome editing has potential to cure diseases without current treatments, but therapies must be safe. Here we show that CRISPR-Cas9 editing can introduce unintended mutations in vivo, which are passed on to the next generation. By editing fertilized zebrafish eggs using four guide RNAs selected for off-target activity in vitro, followed by long-read sequencing of DNA from >1100 larvae, juvenile and adult fish across two generations, we find that structural variants (SVs), i.e., insertions and deletions ≥50 bp, represent 6% of editing outcomes in founder larvae. These SVs occur both at on-target and off-target sites. Our results also illustrate that adult founder zebrafish are mosaic in their germ cells, and that 26% of their offspring carries an off-target mutation and 9% an SV. Hence, pre-testing for off-target activity and SVs using patient material is advisable in clinical applications, to reduce the risk of unanticipated effects with potentially large implications.

Human Genomics and Drug Development

Insights into the genetic basis of human disease are helping to address some of the key challenges in new drug development including the very high rates of failure. Here we review the recent history of an emerging, genomics-assisted approach to pharmaceutical research and development, and its relationship to Mendelian randomization (MR), a well-established analytical approach to causal inference. We demonstrate how human genomic data linked to pharmaceutically relevant phenotypes can be used for (1) drug target identification (mapping relevant drug targets to diseases), (2) drug target validation (inferring the likely effects of drug target perturbation), (3) evaluation of the effectiveness and specificity of compound-target engagement (inferring the extent to which the effects of a compound are exclusive to the target and distinguishing between on-target and off-target compound effects), and (4) the selection of end points in clinical trials (the diseases or conditions to be evaluated as trial outcomes). We show how genomics can help identify indication expansion opportunities for licensed drugs and repurposing of compounds developed to clinical phase that proved safe but ineffective for the original intended indication. We outline statistical and biological considerations in using MR for drug target validation (drug target MR) and discuss the obstacles and challenges for scaled applications of these genomics-based approaches.

Myocardial Function in Offspring Aged 5 to 8 Years of Pregnancy Complicated by Severe Preeclampsia Measured by Two-Dimensional Speckle-Tracking Echocardiography

Objective: This study aimed to quantitatively assess myocardial strain in preterm children aged 5 to 8 years of pregnancy complicated by severe preeclampsia (PE) by two-dimensional (2D) speckle tracking echocardiography.

Method: A cohort study of 23 preterm children delivered by severe PE pregnant women from 2010 to 2012 in the First Affiliated Hospital of Soochow University was carried out. 23 preterm children from uneventful pregnancies in the same period served as controls. Myocardial functions including left ventricular longitudinal strain, radial strain, circumferential strain, and right ventricular longitudinal strain were evaluated by conventional Doppler, tissue Doppler imaging, and 2D speckle-tracking echocardiography (2D STE). All examinations were performed by an experienced ultrasonographer using the VIVID E9 (GE Healthcare) machine, according to standard techniques.

Results: Children aged 5–8 years delivered from severe PE presented less weight (24.41 vs. 20.89 kg, P < 0.05), shorter height (124.1 vs 115.6 cm, P < 0.05) and faster heart rates (84 vs. 93 bpm, P < 0.05) compared to offspring of normotensive women. There were no significant differences in global left ventricular longitudinal strain, radial strain, circumferential strain, and right ventricular longitudinal strain between the children in the experimental group and the control group (P > 0.05).

Conclusion: Exposure to the intrauterine environment of severe PE during the fetal period did not have a significant impact on cardiac structure in premature children at 5–8 years old, but they had a higher resting heart rate which may be associated with cardiovascular disease in the long run.

In vivo identification and validation of novel potential predictors for human cardiovascular diseases

Genetics crucially contributes to cardiovascular diseases (CVDs), the global leading cause of death. Since the majority of CVDs can be prevented by early intervention there is a high demand for the identification of predictive causative genes. While genome wide association studies (GWAS) correlate genes and CVDs after diagnosis and provide a valuable resource for such causative candidate genes, often preferentially those with previously known or suspected function are addressed further. To tackle the unaddressed blind spot of understudied genes, we particularly focused on the validation of human heart phenotype-associated GWAS candidates with little or no apparent connection to cardiac function. Building on the conservation of basic heart function and underlying genetics from fish to human we combined CRISPR/Cas9 genome editing of the orthologs of human GWAS candidates in isogenic medaka with automated high-throughput heart rate analysis. Our functional analyses of understudied human candidates uncovered a prominent fraction of heart rate associated genes from adult human patients impacting on the heart rate in embryonic medaka already in the injected generation. Following this pipeline, we identified 16 GWAS candidates with potential diagnostic and predictive power for human CVDs.