Clonal haematopoiesis of indeterminate potential predicts incident cardiac arrhythmias.

BACKGROUND AND AIMS: Clonal haematopoiesis of indeterminate potential (CHIP), the age-related expansion of blood cells with preleukemic mutations, is associated with atherosclerotic cardiovascular disease and heart failure. This study aimed to test the association of CHIP with new-onset arrhythmias. METHODS: UK Biobank participants without prevalent arrhythmias were included. Co-primary study outcomes were supraventricular arrhythmias, bradyarrhythmias, and ventricular arrhythmias. Secondary outcomes were cardiac arrest, atrial fibrillation, and any arrhythmia. Associations of any CHIP [variant allele fraction (VAF) ≥ 2%], large CHIP (VAF ≥10%), and gene-specific CHIP subtypes with incident arrhythmias were evaluated using multivariable-adjusted Cox regression. Associations of CHIP with myocardial interstitial fibrosis [T1 measured using cardiac magnetic resonance (CMR)] were also tested. RESULTS: This study included 410 702 participants [CHIP: n = 13 892 (3.4%); large CHIP: n = 9191 (2.2%)]. Any and large CHIP were associated with multi-variable-adjusted hazard ratios of 1.11 [95% confidence interval (CI) 1.04-1.18; P = .001] and 1.13 (95% CI 1.05-1.22; P = .001) for supraventricular arrhythmias, 1.09 (95% CI 1.01-1.19; P = .031) and 1.13 (95% CI 1.03-1.25; P = .011) for bradyarrhythmias, and 1.16 (95% CI, 1.00-1.34; P = .049) and 1.22 (95% CI 1.03-1.45; P = .021) for ventricular arrhythmias, respectively. Associations were independent of coronary artery disease and heart failure. Associations were also heterogeneous across arrhythmia subtypes and strongest for cardiac arrest. Gene-specific analyses revealed an increased risk of arrhythmias across driver genes other than DNMT3A. Large CHIP was associated with 1.31-fold odds (95% CI 1.07-1.59; P = .009) of being in the top quintile of myocardial fibrosis by CMR. CONCLUSIONS: CHIP may represent a novel risk factor for incident arrhythmias, indicating a potential target for modulation towards arrhythmia prevention and treatment.

Monogenic and Polygenic Contributions to QTc Prolongation in the Population.

BACKGROUND: Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population. METHODS: We performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed. RESULTS: Fifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/decile of PRS=1.4 ms [95% CI, 1.3 to 1.5]; P=1.1×10-196). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS). CONCLUSIONS: QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

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-ß signalling molecules and spectrin ß. 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.

Worldwide differences in primary prevention implantable cardioverter defibrillator utilization and outcomes in hypertrophic cardiomyopathy.

AIMS: Risk stratification algorithms for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM) and regional differences in clinical practice have evolved over time. We sought to compare primary prevention implantable cardioverter defibrillator (ICD) implantation rates and associated clinical outcomes in US vs. non-US tertiary HCM centres within the international Sarcomeric Human Cardiomyopathy Registry. METHODS AND RESULTS: We included patients with HCM enrolled from eight US sites (n = 2650) and five non-US (n = 2660) sites and used multivariable Cox-proportional hazards models to compare outcomes between sites. Primary prevention ICD implantation rates in US sites were two-fold higher than non-US sites (hazard ratio (HR) 2.27 [1.89-2.74]), including in individuals deemed at high 5-year SCD risk (≥6%) based on the HCM risk-SCD score (HR 3.27 [1.76-6.05]). US ICD recipients also had fewer traditional SCD risk factors. Among ICD recipients, rates of appropriate ICD therapy were significantly lower in US vs. non-US sites (HR 0.52 [0.28-0.97]). No significant difference was identified in the incidence of SCD/resuscitated cardiac arrest among non-recipients of ICDs in US vs. non-US sites (HR 1.21 [0.74-1.97]). CONCLUSION: Primary prevention ICDs are implanted more frequently in patients with HCM in US vs. non-US sites across the spectrum of SCD risk. There was a lower rate of appropriate ICD therapy in US sites, consistent with a lower-risk population, and no significant difference in SCD in US vs. non-US patients who did not receive an ICD. Further studies are needed to understand what drives malignant arrhythmias, optimize ICD allocation, and examine the impact of different ICD utilization strategies on long-term outcomes in HCM.

Association of ABO blood group type with cardiovascular events in COVID-19.

Cardiovascular complications have been reported in patients with COVID-19. We sought to examine the association of ABO blood group type with cardiovascular complications in COVID-19. We examined 409 individuals enrolled in the COVID-19 Registry to Assess Frequency, Management, and Outcomes of Arterial and Venous Thromboembolic Complications (CORONA-VTE) who had ABO blood group data available. Multiple logistic regression was used to assess the association of ABO blood group types with three primary outcomes: major adverse cardiovascular events (MACE), major arterial and venous thrombosis and all-cause mortality. 201, 121, 61 and 26 individuals had blood group O, A, B and AB, respectively. In multivariable analysis, blood group A was associated with a 2.5-fold higher odds of MACE than blood group O (OR 2.47[1.18-5.18]). There was an effect suggesting a 2-fold higher odds of major thrombotic events in blood group A vs. O that did not reach statistical significance (OR 2.15 [0.89-5.20]). No association between blood group type and all-cause mortality was found. Compared with the other blood group types, blood group A was associated with an increased odds of MACE(ORA/non-A 2.18[1.11-4.29]), while blood group O was associated with lower odds of MACE(ORO/non-O 0.50[0.26-0.97]). In conclusion, blood group A was associated with an increased odds of MACE, whereas blood group O was associated with a reduction in the odds of MACE in patients with COVID-19. These findings may inform risk stratification of COVID-19 patients for cardiovascular complications. Additional studies are needed to validate our findings.

Baseline assessment and comparison of arterial anatomy, hyperemic flow, and skeletal muscle perfusion in peripheral artery disease: The Cardiovascular Cell Therapy Research Network "Patients with Intermittent Claudication Injected with ALDH Bright Cells" (CCTRN PACE) study.

BACKGROUND: Peripheral artery disease (PAD) is important to public health as a major contributor to cardiovascular morbidity and mortality. Recent developments in magnetic resonance imaging (MRI) techniques permit improved assessment of PAD anatomy and physiology, and may serve as surrogate end points after proangiogenic therapies. METHODS: The PACE study is a randomized, double-blind, placebo-controlled clinical trial designed to assess the physiologic impact and potential clinical efficacy of autologous bone marrow-derived ALDHbr stem cells. The primary MRI end points of the study are as follows: (1) total collateral count, (2) calf muscle plasma volume (a measure of capillary perfusion) by dynamic contrast-enhanced MRI, and (3) peak hyperemic popliteal flow by phase-contrast MRI (PC-MRI). RESULTS: The interreader and intrareader and test-retest results demonstrated good-to-excellent reproducibility (interclass correlation coefficient range 0.61-0.98) for all magnetic resonance measures. The PAD participants (n=82) had lower capillary perfusion measured by calf muscle plasma volume (3.8% vs 5.6%) and peak hyperemic popliteal flow (4.1 vs 13.5mL/s) as compared with the healthy participants (n=16), with a significant level of collateralization. CONCLUSIONS: Reproducibility of the MRI primary end points in PACE was very good to excellent. The PAD participants exhibited decreased calf muscle capillary perfusion as well as arterial flow reserve when compared with healthy participants. The MRI tools used in PACE may advance PAD science by enabling accurate measurement of PAD microvascular anatomy and perfusion before and after stem cell or other PAD therapies.

Cardiovascular Significance and Genetics of Epicardial and Pericardial Adiposity.

Importance: Epicardial and pericardial adipose tissue (EPAT) has been associated with cardiovascular diseases such as atrial fibrillation or flutter (AF) and coronary artery disease (CAD), but studies have been limited in sample size or drawn from selected populations. It has been suggested that the association between EPAT and cardiovascular disease could be mediated by local or paracrine effects. Objective: To evaluate the association of EPAT with prevalent and incident cardiovascular disease and to elucidate the genetic basis of EPAT in a large population cohort. Design, Setting, and Participants: A deep learning model was trained to quantify EPAT area from 4-chamber magnetic resonance images using semantic segmentation. Cross-sectional and prospective cardiovascular disease associations were evaluated, controlling for sex and age. Prospective associations were additionally controlled for abdominal visceral adipose tissue (VAT) volumes. A genome-wide association study was performed, and a polygenic score (PGS) for EPAT was examined in independent FinnGen cohort study participants. Data analyses were conducted from March 2022 to December 2023. Exposures: The primary exposures were magnetic resonance imaging-derived continuous measurements of epicardial and pericardial adipose tissue area and visceral adipose tissue volume. Main Outcomes and Measures: Prevalent and incident CAD, AF, heart failure (HF), stroke, and type 2 diabetes (T2D). Results: After exclusions, this study included 44 475 participants (mean [SD] age, 64.1 [7.7] years; 22 972 female [51.7%]) from the UK Biobank. Cross-sectional and prospective cardiovascular disease associations were evaluated for a mean (SD) of 3.2 (1.5) years of follow-up. Prospective associations were additionally controlled for abdominal VAT volumes for 38 527 participants. A PGS for EPAT was examined in 453 733 independent FinnGen cohort study participants. EPAT was positively associated with male sex (ß = +0.78 SD in EPAT; P < 3 × 10-324), age (Pearson r = 0.15; P = 9.3 × 10-229), body mass index (Pearson r = 0.47; P < 3 × 10-324), and VAT (Pearson r = 0.72; P < 3 × 10-324). EPAT was more elevated in prevalent HF (ß = +0.46 SD units) and T2D (ß = +0.56) than in CAD (ß = +0.23) or AF (ß = +0.18). EPAT was associated with incident HF (hazard ratio [HR], 1.29 per +1 SD in EPAT; 95% CI, 1.17-1.43), T2D (HR, 1.63; 95% CI, 1.51-1.76), and CAD (HR, 1.19; 95% CI, 1.11-1.28). However, the associations were no longer significant when controlling for VAT. Seven genetic loci were identified for EPAT, implicating transcriptional regulators of adipocyte morphology and brown adipogenesis (EBF1, EBF2, and CEBPA) and regulators of visceral adiposity (WARS2 and TRIB2). The EPAT PGS was associated with T2D (odds ratio [OR], 1.06; 95% CI, 1.05-1.07; P =3.6 × 10-44), HF (OR, 1.05; 95% CI, 1.04-1.06; P =4.8 × 10-15), CAD (OR, 1.04; 95% CI, 1.03-1.05; P =1.4 × 10-17), AF (OR, 1.04; 95% CI, 1.03-1.06; P =7.6 × 10-12), and stroke in FinnGen (OR, 1.02; 95% CI, 1.01-1.03; P =3.5 × 10-3) per 1 SD in PGS. Conclusions and Relevance: Results of this cohort study suggest that epicardial and pericardial adiposity was associated with incident cardiovascular diseases, but this may largely reflect a metabolically unhealthy adiposity phenotype similar to abdominal visceral adiposity.

Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping.

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems. In genome-wide association analyses, we identified 27, 18, 11 and 10 independent genetic loci associated with liver, pancreas, myocardial and renal cortex T1 time, respectively. There was a modest genetic correlation between the examined organs. Several loci overlapped across the examined organs implicating genes involved in a myriad of biologic pathways including metal ion transport (SLC39A8, HFE and TMPRSS6), glucose metabolism (PCK2), blood group antigens (ABO and FUT2), immune function (BANK1 and PPP3CA), inflammation (NFKB1) and mitosis (CENPE). Finally, we found that an increasing number of organs with T1 time falling in the top quintile was associated with increased mortality in the population. Individuals with a high burden of fibrosis in ≥3 organs had a 3-fold increase in mortality compared to those with a low burden of fibrosis across all examined organs in multivariable-adjusted analysis (hazard ratio = 3.31, 95% confidence interval 1.77-6.19; P = 1.78 × 10-4). By leveraging machine learning to quantify T1 time across multiple organs at scale, we uncovered new organ-specific and shared biologic pathways underlying fibrosis that may provide therapeutic targets.

Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.

Low absolute risk of thrombotic and cardiovascular events in outpatient pregnant women with COVID-19.

INTRODUCTION: Pregnancy may contribute to an excess risk of thrombotic or cardiovascular events. COVID-19 increases the risk of these events, although the risk is relatively limited among outpatients. We sought to determine whether outpatient pregnant women with COVID-19 are at a high risk for cardiovascular or thrombotic events. MATERIALS & METHODS: We analyzed pregnant outpatients with COVID-19 from the multicenter CORONA-VTE-Network registry. The main study outcomes were a composite of adjudicated venous or arterial thrombotic events, and a composite of adjudicated cardiovascular events. Events were assessed 90 days after the COVID-19 diagnosis and reported for non-pregnant women ≤45 years, and for men ≤45 years, as points of reference. RESULTS: Among 6585 outpatients, 169 were pregnant at diagnosis. By 90-day follow-up, two pregnant women during the third trimester had lower extremity venous thrombosis, one deep and one superficial vein thrombosis. The cumulative incidence of thrombotic events was 1.20 % (95 % confidence interval [CI]: 0.0 to 2.84 %). Respective rates were 0.47 % (95 % CI: 0.14 % to 0.79 %) among non-pregnant women, and 0.49 % (95 % CI: 0.06 % to 0.91 %) among men ≤45 years. No non-thrombotic cardiovascular events occurred in pregnant women. The rates of cardiovascular events were 0.53 % (95 % CI: 0.18 to 0.87) among non-pregnant women, and 0.68 % (95 % CI: 0.18 to 1.18) in men aged ≤45 years. CONCLUSIONS: Thrombotic and cardiovascular events are rare among outpatients with COVID-19. Although a higher event rate among outpatient pregnant women cannot be excluded, the absolute event rates are low and do not warrant population-wide cardiovascular interventions to optimize outcomes.

Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias.

BACKGROUND: Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT). METHODS: We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies. RESULTS: Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A, SCN10A, and TTN/CCDC141. Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals. CONCLUSIONS: Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility.

The Cardiovascular Impact and Genetics of Pericardial Adiposity.

Background: While previous studies have reported associations of pericardial adipose tissue (PAT) with cardiovascular diseases such as atrial fibrillation and coronary artery disease, they have been limited in sample size or drawn from selected populations. Additionally, the genetic determinants of PAT remain largely unknown. We aimed to evaluate the association of PAT with prevalent and incident cardiovascular disease and to elucidate the genetic basis of PAT in a large population cohort. Methods: A deep learning model was trained to quantify PAT area from four-chamber magnetic resonance images in the UK Biobank using semantic segmentation. Cross-sectional and prospective cardiovascular disease associations were evaluated, controlling for sex and age. A genome-wide association study was performed, and a polygenic score (PGS) for PAT was examined in 453,733 independent FinnGen study participants. Results: A total of 44,725 UK Biobank participants (51.7% female, mean [SD] age 64.1 [7.7] years) were included. PAT was positively associated with male sex (ß = +0.76 SD in PAT), age (r = 0.15), body mass index (BMI; r = 0.47) and waist-to-hip ratio (r = 0.55) (P < 1×10-230). PAT was more elevated in prevalent heart failure (ß = +0.46 SD units) and type 2 diabetes (ß = +0.56) than in coronary artery disease (ß = +0.22) or AF (ß = +0.18). PAT was associated with incident heart failure (HR = 1.29 per +1 SD in PAT [95% CI 1.17-1.43]) and type 2 diabetes (HR = 1.63 [1.51-1.76]) during a mean 3.2 (±1.5) years of follow-up; the associations remained significant when controlling for BMI. We identified 5 novel genetic loci for PAT and implicated transcriptional regulators of adipocyte morphology and brown adipogenesis (EBF1, EBF2 and CEBPA) and regulators of visceral adiposity (WARS2 and TRIB2). The PAT PGS was associated with T2D, heart failure, coronary artery disease and atrial fibrillation in FinnGen (ORs 1.03-1.06 per +1 SD in PGS, P < 2×10-10). Conclusions: PAT shares genetic determinants with abdominal adiposity and is an independent predictor of incident type 2 diabetes and heart failure.

Assessment of valvular function in over 47,000 people using deep learning-based flow measurements.

Valvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale. We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants. We calculated eight traits, including peak velocity, mean gradient, aortic valve area, forward stroke volume, mitral and aortic regurgitant volume, greatest average velocity, and ascending aortic diameter. We then computed sex-stratified reference ranges for these phenotypes in up to 31,909 healthy individuals. In healthy individuals, we found an annual decrement of 0.03cm 2 in the aortic valve area. Participants with mitral valve prolapse had a 1 standard deviation [SD] higher mitral regurgitant volume (P=9.6 × 10 -12 ), and those with aortic stenosis had a 4.5 SD-higher mean gradient (P=1.5 × 10 -431 ), validating the derived phenotypes' associations with clinical disease. Greater levels of ApoB, triglycerides, and Lp(a) assayed nearly 10 years prior to imaging were associated with higher gradients across the aortic valve. Metabolomic profiles revealed that increased glycoprotein acetyls were also associated with an increased aortic valve mean gradient (0.92 SD, P=2.1 x 10 -22 ). Finally, velocity-derived phenotypes were risk markers for aortic and mitral valve surgery even at thresholds below what is considered relevant disease currently. Using machine learning to quantify the rich phenotypic data of the UK Biobank, we report the largest assessment of valvular function and cardiovascular disease in the general population.

Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch.

BACKGROUND: Absence of a dicrotic notch on finger photoplethysmography is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease. However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident cardiovascular disease. METHODS: In 169 787 participants in the UK Biobank, we identified absent dicrotic notch on photoplethysmography and created a novel continuous trait reflecting notch smoothness using machine learning. Next, we determined the heritability, genetic basis, polygenic risk, and clinical relations for the binary absent notch trait and the newly derived continuous notch smoothness trait. RESULTS: Heritability of the continuous notch smoothness trait was 7.5%, compared with 5.6% for the binary absent notch trait. A genome-wide association study of notch smoothness identified 15 significant loci, implicating genes including NT5C2 (P=1.2×10-26), IGFBP3 (P=4.8×10-18), and PHACTR1 (P=1.4×10-13), compared with 6 loci for the binary absent notch trait. Notch smoothness stratified risk of incident myocardial infarction or coronary artery disease, stroke, heart failure, and aortic stenosis. A polygenic risk score for notch smoothness was associated with incident cardiovascular disease and all-cause death in UK Biobank participants without available photoplethysmography data. CONCLUSIONS: We found that a machine learning derived continuous trait reflecting dicrotic notch smoothness on photoplethysmography was heritable and associated with genes involved in vascular stiffness. Greater notch smoothness was associated with greater risk of incident cardiovascular disease. Raw digital phenotyping may identify individuals at risk for disease via specific genetic pathways.

Genetics of myocardial interstitial fibrosis in the human heart and association with disease.

Myocardial interstitial fibrosis is associated with cardiovascular disease and adverse prognosis. Here, to investigate the biological pathways that underlie fibrosis in the human heart, we developed a machine learning model to measure native myocardial T1 time, a marker of myocardial fibrosis, in 41,505 UK Biobank participants who underwent cardiac magnetic resonance imaging. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis. Genome-wide association analysis identified 11 independent loci associated with T1 time. The identified loci implicated genes involved in glucose transport (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Using a transforming growth factor ß1-mediated cardiac fibroblast activation assay, we found that 9 of the 11 loci consisted of genes that exhibited temporal changes in expression or open chromatin conformation supporting their biological relevance to myofibroblast cell state acquisition. By harnessing machine learning to perform large-scale quantification of myocardial interstitial fibrosis using cardiac imaging, we validate associations between cardiac fibrosis and disease, and identify new biologically relevant pathways underlying fibrosis.

Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass.

Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90th percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.

Major cardiovascular events after COVID-19, event rates post-vaccination, antiviral or anti-inflammatory therapy, and temporal trends: Rationale and methodology of the CORONA-VTE-Network study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with excess risk of cardiovascular and thrombotic events in the early post-infection period and during convalescence. Despite the progress in our understanding of cardiovascular complications, uncertainty persists with respect to more recent event rates, temporal trends, association between vaccination status and outcomes, and findings within vulnerable subgroups such as older adults (aged 65 years or older), or those undergoing hemodialysis. Sex-informed findings, including results among pregnant and breastfeeding women, as well as adjusted comparisons between male and female adults are similarly understudied. METHODS: Adult patients, aged ≥18 years, with polymerase chain reaction-confirmed COVID-19 who received inpatient or outpatient care at the participating centers of the registry are eligible for inclusion. A total of 10,000 patients have been included in this multicenter study, with Brigham and Women's Hospital (Boston, MA) serving as the coordinating center. Other sites include Beth Israel Deaconess Medical Center, Anne Arundel Medical Center, University of Virginia Medical Center, University of Colorado Health System, and Thomas Jefferson University Health System. Data elements will be ascertained manually for accuracy. The two main outcomes are 1) a composite of venous or arterial thrombotic events, and 2) a composite of major cardiovascular events, defined as venous or arterial thrombosis, myocarditis or heart failure with inpatient treatment, new atrial fibrillation/flutter, or cardiovascular death. Clinical outcomes are adjudicated by independent physicians. Vaccination status and time of inclusion in the study will be ascertained for subgroup-specific analyses. Outcomes are pre-specified to be reported separately for hospitalized patients versus those who were initially receiving outpatient care. Outcomes will be reported at 30-day and 90-day follow-up. Data cleaning at the sites and the data coordinating center and outcomes adjudication process are in-progress. CONCLUSIONS: The CORONA-VTE-Network study will share contemporary information related to rates of cardiovascular and thrombotic events in patients with COVID-19 overall, as well as within key subgroups, including by time of inclusion, vaccination status, patients undergoing hemodialysis, the elderly, and sex-informed analyses such as comparison of women and men, or among pregnant and breastfeeding women.

LMNA Variants and Risk of Adult-Onset Cardiac Disease.

BACKGROUND: Genetic variants in LMNA may cause cardiac disease, but population-level contributions of variants to cardiac disease burden are not well-characterized. OBJECTIVES: We sought to determine the frequency and contribution of rare LMNA variants to cardiomyopathy and arrhythmia risk among ambulatory adults. METHODS: We included 185,990 UK Biobank participants with whole-exome sequencing. We annotated rare loss-of-function and missense LMNA variants for functional effect using 30 in silico prediction tools. We assigned a predicted functional effect weight to each variant and calculated a score for each carrier. We tested associations between the LMNA score and arrhythmia (atrial fibrillation, bradyarrhythmia, ventricular arrhythmia) or cardiomyopathy outcomes (dilated cardiomyopathy and heart failure). We also examined associations for variants located upstream vs downstream of the nuclear localization signal. RESULTS: Overall, 1,167 (0.63%) participants carried an LMNA variant and 15,079 (8.11%) had an arrhythmia or cardiomyopathy event during a median follow-up of 10.9 years. The LMNA score was associated with arrhythmia or cardiomyopathy (OR: 2.21; P < 0.001) and the association was more significant when restricted to variants upstream of the nuclear localization signal (OR: 5.05; P < 0.001). The incidence rate of arrhythmia or cardiomyopathy was 8.43 per 1,000 person-years (95% CI: 6.73-10.12 per 1,000 person-years) among LMNA variant carriers and 6.38 per 1,000 person-years (95% CI: 6.27-6.50 per 1,000 person-years) among noncarriers. Only 3 (1.2%) of the variants were reported as pathogenic in ClinVar. CONCLUSIONS: Middle-aged adult carriers of rare missense or loss-of-function LMNA variants are at increased risk for arrhythmia and cardiomyopathy.

Wearable accelerometer-derived physical activity and incident disease.

Physical activity is regarded as favorable to health but effects across the spectrum of human disease are poorly quantified. In contrast to self-reported measures, wearable accelerometers can provide more precise and reproducible activity quantification. Using wrist-worn accelerometry data from the UK Biobank prospective cohort study, we test associations between moderate-to-vigorous physical activity (MVPA) - both total MVPA minutes and whether MVPA is above a guideline-based threshold of ≥150 min/week-and incidence of 697 diseases using Cox proportional hazards models adjusted for age, sex, body mass index, smoking, Townsend Deprivation Index, educational attainment, diet quality, alcohol use, blood pressure, anti-hypertensive use. We correct for multiplicity at a false discovery rate of 1%. We perform analogous testing using self-reported MVPA. Among 96,244 adults wearing accelerometers for one week (age 62 ± 8 years), MVPA is associated with 373 (54%) tested diseases over a median 6.3 years of follow-up. Greater MVPA is overwhelmingly associated with lower disease risk (98% of associations) with hazard ratios (HRs) ranging 0.70-0.98 per 150 min increase in weekly MVPA, and associations spanning all 16 disease categories tested. Overall, associations with lower disease risk are enriched for cardiac (16%), digestive (14%), endocrine/metabolic (10%), and respiratory conditions (8%) (chi-square p < 0.01). Similar patterns are observed using the guideline-based threshold of ≥150 MVPA min/week. Some of the strongest associations with guideline-adherent activity include lower risks of incident heart failure (HR 0.65, 95% CI 0.55-0.77), type 2 diabetes (HR 0.64, 95% CI 0.58-0.71), cholelithiasis (HR 0.61, 95% CI 0.54-0.70), and chronic bronchitis (HR 0.42, 95% CI 0.33-0.54). When assessed within 456,374 individuals providing self-reported MVPA, effect sizes for guideline-adherent activity are substantially smaller (e.g., heart failure HR 0.84, 95% CI 0.80-0.88). Greater wearable device-based physical activity is robustly associated with lower disease incidence. Future studies are warranted to identify potential mechanisms linking physical activity and disease, and assess whether optimization of measured activity can reduce disease risk.

Spatially Distinct Genetic Determinants of Aortic Dimensions Influence Risks of Aneurysm and Stenosis.

BACKGROUND: The left ventricular outflow tract (LVOT) and ascending aorta are spatially complex, with distinct pathologies and embryologic origins. Prior work examined the genetics of thoracic aortic diameter in a single plane. OBJECTIVES: We sought to elucidate the genetic basis for the diameter of the LVOT, aortic root, and ascending aorta. METHODS: Using deep learning, we analyzed 2.3 million cardiac magnetic resonance images from 43,317 UK Biobank participants. We computed the diameters of the LVOT, the aortic root, and at 6 locations of ascending aorta. For each diameter, we conducted a genome-wide association study and generated a polygenic score. Finally, we investigated associations between these scores and disease incidence. RESULTS: A total of 79 loci were significantly associated with at least 1 diameter. Of these, 35 were novel, and most were associated with 1 or 2 diameters. A polygenic score of aortic diameter approximately 13 mm from the sinotubular junction most strongly predicted thoracic aortic aneurysm (n = 427,016; mean HR: 1.42 per SD; 95% CI: 1.34-1.50; P = 6.67 × 10-21). A polygenic score predicting a smaller aortic root was predictive of aortic stenosis (n = 426,502; mean HR: 1.08 per SD; 95% CI: 1.03-1.12; P = 5 × 10-6). CONCLUSIONS: We detected distinct genetic loci underpinning the diameters of the LVOT, aortic root, and at several segments of ascending aorta. We spatially defined a region of aorta whose genetics may be most relevant to predicting thoracic aortic aneurysm. We further described a genetic signature that may predispose to aortic stenosis. Understanding genetic contributions to proximal aortic diameter may enable identification of individuals at risk for aortic disease and facilitate prioritization of therapeutic targets.