Molecular Choreography of Acute Exercise.

Acute physical activity leads to several changes in metabolic, cardiovascular, and immune pathways. Although studies have examined selected changes in these pathways, the system-wide molecular response to an acute bout of exercise has not been fully characterized. We performed longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including metabolome, lipidome, immunome, proteome, and transcriptome from 36 well-characterized volunteers, before and after a controlled bout of symptom-limited exercise. Time-series analysis revealed thousands of molecular changes and an orchestrated choreography of biological processes involving energy metabolism, oxidative stress, inflammation, tissue repair, and growth factor response, as well as regulatory pathways. Most of these processes were dampened and some were reversed in insulin-resistant participants. Finally, we discovered biological pathways involved in cardiopulmonary exercise response and developed prediction models revealing potential resting blood-based biomarkers of peak oxygen consumption.

Rare variant associations with plasma protein levels in the UK Biobank.

Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1-4. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype-protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort5. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene-protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.

The genetics of human performance.

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

Personal omics profiling reveals dynamic molecular and medical phenotypes.

Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

Video-based AI for beat-to-beat assessment of cardiac function.

Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular disease1, screening for cardiotoxicity2 and decisions regarding the clinical management of patients with a critical illness3. However, human assessment of cardiac function focuses on a limited sampling of cardiac cycles and has considerable inter-observer variability despite years of training4,5. Here, to overcome this challenge, we present a video-based deep learning algorithm-EchoNet-Dynamic-that surpasses the performance of human experts in the critical tasks of segmenting the left ventricle, estimating ejection fraction and assessing cardiomyopathy. Trained on echocardiogram videos, our model accurately segments the left ventricle with a Dice similarity coefficient of 0.92, predicts ejection fraction with a mean absolute error of 4.1% and reliably classifies heart failure with reduced ejection fraction (area under the curve of 0.97). In an external dataset from another healthcare system, EchoNet-Dynamic predicts the ejection fraction with a mean absolute error of 6.0% and classifies heart failure with reduced ejection fraction with an area under the curve of 0.96. Prospective evaluation with repeated human measurements confirms that the model has variance that is comparable to or less than that of human experts. By leveraging information across multiple cardiac cycles, our model can rapidly identify subtle changes in ejection fraction, is more reproducible than human evaluation and lays the foundation for precise diagnosis of cardiovascular disease in real time. As a resource to promote further innovation, we also make publicly available a large dataset of 10,030 annotated echocardiogram videos.

Deep learning to detect left ventricular structural abnormalities in chest X-rays.

BACKGROUND AND AIMS: Early identification of cardiac structural abnormalities indicative of heart failure is crucial to improving patient outcomes. Chest X-rays (CXRs) are routinely conducted on a broad population of patients, presenting an opportunity to build scalable screening tools for structural abnormalities indicative of Stage B or worse heart failure with deep learning methods. In this study, a model was developed to identify severe left ventricular hypertrophy (SLVH) and dilated left ventricle (DLV) using CXRs. METHODS: A total of 71 589 unique CXRs from 24 689 different patients completed within 1 year of echocardiograms were identified. Labels for SLVH, DLV, and a composite label indicating the presence of either were extracted from echocardiograms. A deep learning model was developed and evaluated using area under the receiver operating characteristic curve (AUROC). Performance was additionally validated on 8003 CXRs from an external site and compared against visual assessment by 15 board-certified radiologists. RESULTS: The model yielded an AUROC of 0.79 (0.76-0.81) for SLVH, 0.80 (0.77-0.84) for DLV, and 0.80 (0.78-0.83) for the composite label, with similar performance on an external data set. The model outperformed all 15 individual radiologists for predicting the composite label and achieved a sensitivity of 71% vs. 66% against the consensus vote across all radiologists at a fixed specificity of 73%. CONCLUSIONS: Deep learning analysis of CXRs can accurately detect the presence of certain structural abnormalities and may be useful in early identification of patients with LV hypertrophy and dilation. As a resource to promote further innovation, 71 589 CXRs with adjoining echocardiographic labels have been made publicly available.

Improved Cardiac Performance and Decreased Arrhythmia in Hypertrophic Cardiomyopathy With Non-ß-Blocking R-Enantiomer Carvedilol.

BACKGROUND: Hypercontractility and arrhythmia are key pathophysiologic features of hypertrophic cardiomyopathy (HCM), the most common inherited heart disease. ß-Adrenergic receptor antagonists (ß-blockers) are the first-line therapy for HCM. However, ß-blockers commonly selected for this disease are often poorly tolerated in patients, where heart-rate reduction and noncardiac effects can lead to reduced cardiac output and fatigue. Mavacamten, myosin ATPase inhibitor recently approved by the US Food and Drug Administration, has demonstrated the ability to ameliorate hypercontractility without lowering heart rate, but its benefits are so far limited to patients with left ventricular (LV) outflow tract obstruction, and its effect on arrhythmia is unknown. METHODS: We screened 21 ß-blockers for their impact on myocyte contractility and evaluated the antiarrhythmic properties of the most promising drug in a ventricular myocyte arrhythmia model. We then examined its in vivo effect on LV function by hemodynamic pressure-volume loop analysis. The efficacy of the drug was tested in vitro and in vivo compared with current therapeutic options (metoprolol, verapamil, and mavacamten) for HCM in an established mouse model of HCM (Myh6R403Q/+ and induced pluripotent stem cell (iPSC)-derived cardiomyocytes from patients with HCM (MYH7R403Q/+). RESULTS: We identified that carvedilol, a ß-blocker not commonly used in HCM, suppresses contractile function and arrhythmia by inhibiting RyR2 (ryanodine receptor type 2). Unlike metoprolol (a ß1-blocker), carvedilol markedly reduced LV contractility through RyR2 inhibition, while maintaining stroke volume through α1-adrenergic receptor inhibition in vivo. Clinically available carvedilol is a racemic mixture, and the R-enantiomer, devoid of ß-blocking effect, retains the ability to inhibit both α1-receptor and RyR2, thereby suppressing contractile function and arrhythmias without lowering heart rate and cardiac output. In Myh6R403Q/+ mice, R-carvedilol normalized hyperdynamic contraction, suppressed arrhythmia, and increased cardiac output better than metoprolol, verapamil, and mavacamten. The ability of R-carvedilol to suppress contractile function was well retained in MYH7R403Q/+ iPSC-derived cardiomyocytes. CONCLUSIONS: R-enantiomer carvedilol attenuates hyperdynamic contraction, suppresses arrhythmia, and at the same time, improves cardiac output without lowering heart rate by dual blockade of α1-adrenergic receptor and RyR2 in mouse and human models of HCM. This combination of therapeutic effects is unique among current therapeutic options for HCM and may particularly benefit patients without LV outflow tract obstruction.

Left Ventricular Systolic Dysfunction in Patients Diagnosed With Hypertrophic Cardiomyopathy During Childhood: Insights From the SHaRe Registry.

BACKGROUND: The development of left ventricular systolic dysfunction (LVSD) in hypertrophic cardiomyopathy (HCM) is rare but serious and associated with poor outcomes in adults. Little is known about the prevalence, predictors, and prognosis of LVSD in patients diagnosed with HCM as children. METHODS: Data from patients with HCM in the international, multicenter SHaRe (Sarcomeric Human Cardiomyopathy Registry) were analyzed. LVSD was defined as left ventricular ejection fraction <50% on echocardiographic reports. Prognosis was assessed by a composite of death, cardiac transplantation, and left ventricular assist device implantation. Predictors of developing incident LVSD and subsequent prognosis with LVSD were assessed using Cox proportional hazards models. RESULTS: We studied 1010 patients diagnosed with HCM during childhood (<18 years of age) and compared them with 6741 patients with HCM diagnosed as adults. In the pediatric HCM cohort, median age at HCM diagnosis was 12.7 years (interquartile range, 8.0-15.3), and 393 (36%) patients were female. At initial SHaRe site evaluation, 56 (5.5%) patients with childhood-diagnosed HCM had prevalent LVSD, and 92 (9.1%) developed incident LVSD during a median follow-up of 5.5 years. Overall LVSD prevalence was 14.7% compared with 8.7% in patients with adult-diagnosed HCM. Median age at incident LVSD was 32.6 years (interquartile range, 21.3-41.6) for the pediatric cohort and 57.2 years (interquartile range, 47.3-66.5) for the adult cohort. Predictors of developing incident LVSD in childhood-diagnosed HCM included age <12 years at HCM diagnosis (hazard ratio [HR], 1.72 [CI, 1.13-2.62), male sex (HR, 3.1 [CI, 1.88-5.2), carrying a pathogenic sarcomere variant (HR, 2.19 [CI, 1.08-4.4]), previous septal reduction therapy (HR, 2.34 [CI, 1.42-3.9]), and lower initial left ventricular ejection fraction (HR, 1.53 [CI, 1.38-1.69] per 5% decrease). Forty percent of patients with LVSD and HCM diagnosed during childhood met the composite outcome, with higher rates in female participants (HR, 2.60 [CI, 1.41-4.78]) and patients with a left ventricular ejection fraction <35% (HR, 3.76 [2.16-6.52]). CONCLUSIONS: Patients with childhood-diagnosed HCM have a significantly higher lifetime risk of developing LVSD, and LVSD emerges earlier than for patients with adult-diagnosed HCM. Regardless of age at diagnosis with HCM or LVSD, the prognosis with LVSD is poor, warranting careful surveillance for LVSD, especially as children with HCM transition to adult care.

Loss of function of FAM177A1, a Golgi complex localized protein, causes a novel neurodevelopmental disorder.

PURPOSE: The function of FAM177A1 and its relationship to human disease is largely unknown. Recent studies have demonstrated FAM177A1 to be a critical immune-associated gene. One previous case study has linked FAM177A1 to a neurodevelopmental disorder in four siblings. METHODS: We identified five individuals from three unrelated families with biallelic variants in FAM177A1. The physiological function of FAM177A1 was studied in a zebrafish model organism and human cell lines with loss-of-function variants similar to the affected cohort. RESULTS: These individuals share a characteristic phenotype defined by macrocephaly, global developmental delay, intellectual disability, seizures, behavioral abnormalities, hypotonia, and gait disturbance. We show that FAM177A1 localizes to the Golgi complex in mammalian and zebrafish cells. Intersection of the RNA-seq and metabolomic datasets from FAM177A1-deficient human fibroblasts and whole zebrafish larvae demonstrated dysregulation of pathways associated with apoptosis, inflammation, and negative regulation of cell proliferation. CONCLUSION: Our data sheds light on the emerging function of FAM177A1 and defines FAM177A1-related neurodevelopmental disorder as a new clinical entity.

Polygenic risk scores for the prediction of cardiometabolic disease.

Cardiometabolic diseases contribute more to global morbidity and mortality than any other group of disorders. Polygenic risk scores (PRSs), the weighted summation of individually small-effect genetic variants, represent an advance in our ability to predict the development and complications of cardiometabolic diseases. This article reviews the evidence supporting the use of PRS in seven common cardiometabolic diseases: coronary artery disease (CAD), stroke, hypertension, heart failure and cardiomyopathies, obesity, atrial fibrillation (AF), and type 2 diabetes mellitus (T2DM). Data suggest that PRS for CAD, AF, and T2DM consistently improves prediction when incorporated into existing clinical risk tools. In other areas such as ischaemic stroke and hypertension, clinical application appears premature but emerging evidence suggests that the study of larger and more diverse populations coupled with more granular phenotyping will propel the translation of PRS into practical clinical prediction tools.

Emery-Dreifuss muscular dystrophy Type 1 is associated with a high risk of malignant ventricular arrhythmias and end-stage heart failure.

BACKGROUND AND AIMS: Emery-Dreifuss muscular dystrophy (EDMD) is caused by variants in EMD (EDMD1) and LMNA (EDMD2). Cardiac conduction defects and atrial arrhythmia are common to both, but LMNA variants also cause end-stage heart failure (ESHF) and malignant ventricular arrhythmia (MVA). This study aimed to better characterize the cardiac complications of EMD variants. METHODS: Consecutively referred EMD variant-carriers were retrospectively recruited from 12 international cardiomyopathy units. MVA and ESHF incidences in male and female variant-carriers were determined. Male EMD variant-carriers with a cardiac phenotype at baseline (EMDCARDIAC) were compared with consecutively recruited male LMNA variant-carriers with a cardiac phenotype at baseline (LMNACARDIAC). RESULTS: Longitudinal follow-up data were available for 38 male and 21 female EMD variant-carriers [mean (SD) ages 33.4 (13.3) and 43.3 (16.8) years, respectively]. Nine (23.7%) males developed MVA and five (13.2%) developed ESHF during a median (inter-quartile range) follow-up of 65.0 (24.3-109.5) months. No female EMD variant-carrier had MVA or ESHF, but nine (42.8%) developed a cardiac phenotype at a median (inter-quartile range) age of 58.6 (53.2-60.4) years. Incidence rates for MVA were similar for EMDCARDIAC and LMNACARDIAC (4.8 and 6.6 per 100 person-years, respectively; log-rank P = .49). Incidence rates for ESHF were 2.4 and 5.9 per 100 person-years for EMDCARDIAC and LMNACARDIAC, respectively (log-rank P = .09). CONCLUSIONS: Male EMD variant-carriers have a risk of progressive heart failure and ventricular arrhythmias similar to that of male LMNA variant-carriers. Early implantable cardioverter defibrillator implantation and heart failure drug therapy should be considered in male EMD variant-carriers with cardiac disease.

Two epilepsy-associated variants in KCNA2 (KV 1.2) at position H310 oppositely affect channel functional expression.

Two KCNA2 variants (p.H310Y and p.H310R) were discovered in paediatric patients with epilepsy and developmental delay. KCNA2 encodes KV 1.2-channel subunits, which regulate neuronal excitability. Both gain and loss of KV 1.2 function cause epilepsy, precluding the prediction of variant effects; and while H310 is conserved throughout the KV -channel superfamily, it is largely understudied. We investigated both variants in heterologously expressed, human KV 1.2 channels by immunocytochemistry, electrophysiology and voltage-clamp fluorometry. Despite affecting the same channel, at the same position, and being associated with severe neurological disease, the two variants had diametrically opposite effects on KV 1.2 functional expression. The p.H310Y variant produced 'dual gain of function', increasing both cell-surface trafficking and activity, delaying channel closure. We found that the latter is due to the formation of a hydrogen bond that stabilizes the active state of the voltage-sensor domain. Additionally, H310Y abolished 'ball and chain' inactivation of KV 1.2 by KV ß1 subunits, enhancing gain of function. In contrast, p.H310R caused 'dual loss of function', diminishing surface levels by multiple impediments to trafficking and inhibiting voltage-dependent channel opening. We discuss the implications for KV -channel biogenesis and function, an emergent hotspot for disease-associated variants, and mechanisms of epileptogenesis. KEY POINTS: KCNA2 encodes the subunits of KV 1.2 voltage-activated, K+ -selective ion channels, which regulate electrical signalling in neurons. We characterize two KCNA2 variants from patients with developmental delay and epilepsy. Both variants affect position H310, highly conserved in KV channels. The p.H310Y variant caused 'dual gain of function', increasing both KV 1.2-channel activity and the number of KV 1.2 subunits on the cell surface. H310Y abolished 'ball and chain' (N-type) inactivation of KV 1.2 by KV ß1 subunits, enhancing the gain-of-function phenotype. The p.H310R variant caused 'dual loss of function', diminishing the presence of KV 1.2 subunits on the cell surface and inhibiting voltage-dependent channel opening. As H310Y stabilizes the voltage-sensor active conformation and abolishes N-type inactivation, it can serve as an investigative tool for functional and pharmacological studies.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Genomics Research with Undiagnosed Children: Ethical Challenges at the Boundaries of Research and Clinical Care.

OBJECTIVE: To explore the perspectives of parents of undiagnosed children enrolled in genomic diagnosis research regarding their motivations for enrolling their children, their understanding of the potential burdens and benefits, and the extent to which their experiences ultimately aligned with or diverged from their original expectations. STUDY DESIGN: In-depth interviews were conducted with parents, audio-recorded and transcribed. A structured codebook was applied to each transcript, after which iterative memoing was used to identify themes. RESULTS: Fifty-four parents participated, including 17 (31.5%) whose child received a diagnosis through research. Themes describing parents' expectations and experiences of genomic diagnosis research included (1) the extent to which parents' motivations for participation focused on their hope that it would directly benefit their child, (2) the ways in which parents' frustrations regarding the research process confused the dual clinical and research goals of their participation, and (3) the limited clinical benefits parents ultimately experienced for their children. CONCLUSIONS: Our results suggest that parents of undiagnosed children seeking enrollment in genomic diagnosis research are at risk of a form of therapeutic misconception-in this case, diagnostic misconception. These findings indicate the need to examine the processes and procedures associated with this research to communicate appropriately and balance the potential burdens and benefits of study participation.

Defining left ventricular remodeling using lean body mass allometry: a UK Biobank study.

PURPOSE: The geometric patterns of ventricular remodeling are determined using indexed left ventricular mass (LVM), end-diastolic volume (LVEDV) and concentricity, most often measured using the mass-to-volume ratio (MVR). The aims of this study were to validate lean body mass (LBM)-based allometric coefficients for scaling and to determine an index of concentricity that is independent of both volume and LBM. METHODS: Participants from the UK Biobank who underwent both CMR and dual-energy X-ray absorptiometry (DXA) during 2014-2015 were considered (n = 5064). We excluded participants aged ≥ 70 years or those with cardiometabolic risk factors. We determined allometric coefficients for scaling using linear regression of the logarithmically transformed ventricular remodeling parameters. We further defined a multiplicative allometric relationship for LV concentricity (LVC) adjusting for both LVEDV and LBM. RESULTS: A total of 1638 individuals (1057 female) were included. In subjects with lower body fat percentage (< 25% in males, < 35% in females, n = 644), the LBM allometric coefficients for scaling LVM and LVEDV were 0.85 ± 0.06 and 0.85 ± 0.03 respectively (R2 = 0.61 and 0.57, P < 0.001), with no evidence of sex-allometry interaction. While the MVR was independent of LBM, it demonstrated a negative association with LVEDV in (females: r = - 0.44, P < 0.001; males: - 0.38, P < 0.001). In contrast, LVC was independent of both LVEDV and LBM [LVC = LVM/(LVEDV0.40 × LBM0.50)] leading to increased overlap between LV hypertrophy and higher concentricity. CONCLUSIONS: We validated allometric coefficients for LBM-based scaling for CMR indexed parameters relevant for classifying geometric patterns of ventricular remodeling.

Phenotypic Expression, Natural History, and Risk Stratification of Cardiomyopathy Caused by Filamin C Truncating Variants.

BACKGROUND: Filamin C truncating variants (FLNCtv) cause a form of arrhythmogenic cardiomyopathy: the mode of presentation, natural history, and risk stratification of FLNCtv remain incompletely explored. We aimed to develop a risk profile for refractory heart failure and life-threatening arrhythmias in a multicenter cohort of FLNCtv carriers. METHODS: FLNCtv carriers were identified from 10 tertiary care centers for genetic cardiomyopathies. Clinical and outcome data were compiled. Composite outcomes were all-cause mortality/heart transplantation/left ventricle assist device (D/HT/LVAD), nonarrhythmic death/HT/LVAD, and sudden cardiac death/major ventricular arrhythmias. Previously established cohorts of 46 patients with LMNA and 60 with DSP-related arrhythmogenic cardiomyopathies were used for prognostic comparison. RESULTS: Eighty-five patients carrying FLNCtv were included (42±15 years, 53% men, 45% probands). Phenotypes were heterogeneous at presentation: 49% dilated cardiomyopathy, 25% arrhythmogenic left dominant cardiomyopathy, 3% arrhythmogenic right ventricular cardiomyopathy. Left ventricular ejection fraction was <50% in 64% of carriers and 34% had right ventricular fractional area changes (RVFAC=(right ventricular end-diastolic area - right ventricular end-systolic area)/right ventricular end-diastolic area) <35%. During follow-up (median time 61 months), 19 (22%) carriers experienced D/HT/LVAD, 13 (15%) experienced nonarrhythmic death/HT/LVAD, and 23 (27%) experienced sudden cardiac death/major ventricular arrhythmias. The sudden cardiac death/major ventricular arrhythmias incidence of FLNCtv carriers did not significantly differ from LMNA carriers and DSP carriers. In FLNCtv carriers, left ventricular ejection fraction was associated with the risk of D/HT/LVAD and nonarrhythmic death/HT/LVAD. CONCLUSIONS: Among patients referred to tertiary referral centers, FLNCtv arrhythmogenic cardiomyopathy is phenotypically heterogeneous and characterized by a high risk of life-threatening arrhythmias, which does not seem to be associated with the severity of left ventricular dysfunction.

SARS-CoV-2 RNAemia Predicts Clinical Deterioration and Extrapulmonary Complications from COVID-19.

BACKGROUND: The determinants of coronavirus disease 2019 (COVID-19) disease severity and extrapulmonary complications (EPCs) are poorly understood. We characterized relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNAemia and disease severity, clinical deterioration, and specific EPCs. METHODS: We used quantitative and digital polymerase chain reaction (qPCR and dPCR) to quantify SARS-CoV-2 RNA from plasma in 191 patients presenting to the emergency department with COVID-19. We recorded patient symptoms, laboratory markers, and clinical outcomes, with a focus on oxygen requirements over time. We collected longitudinal plasma samples from a subset of patients. We characterized the role of RNAemia in predicting clinical severity and EPCs using elastic net regression. RESULTS: Of SARS-CoV-2-positive patients, 23.0% (44 of 191) had viral RNA detected in plasma by dPCR, compared with 1.4% (2 of 147) by qPCR. Most patients with serial measurements had undetectable RNAemia within 10 days of symptom onset, reached maximum clinical severity within 16 days, and symptom resolution within 33 days. Initially RNAemic patients were more likely to manifest severe disease (odds ratio, 6.72 [95% confidence interval, 2.45-19.79]), worsening of disease severity (2.43 [1.07-5.38]), and EPCs (2.81 [1.26-6.36]). RNA loads were correlated with maximum severity (r = 0.47 [95% confidence interval, .20-.67]). CONCLUSIONS: dPCR is more sensitive than qPCR for the detection of SARS-CoV-2 RNAemia, which is a robust predictor of eventual COVID-19 severity and oxygen requirements, as well as EPCs. Because many COVID-19 therapies are initiated on the basis of oxygen requirements, RNAemia on presentation might serve to direct early initiation of appropriate therapies for the patients most likely to deteriorate.

Towards precision medicine.

There is great potential for genome sequencing to enhance patient care through improved diagnostic sensitivity and more precise therapeutic targeting. To maximize this potential, genomics strategies that have been developed for genetic discovery - including DNA-sequencing technologies and analysis algorithms - need to be adapted to fit clinical needs. This will require the optimization of alignment algorithms, attention to quality-coverage metrics, tailored solutions for paralogous or low-complexity areas of the genome, and the adoption of consensus standards for variant calling and interpretation. Global sharing of this more accurate genotypic and phenotypic data will accelerate the determination of causality for novel genes or variants. Thus, a deeper understanding of disease will be realized that will allow its targeting with much greater therapeutic precision.

Clinical characteristics and outcomes in childhood-onset hypertrophic cardiomyopathy.

AIMS: Childhood-onset hypertrophic cardiomyopathy (HCM) is far less common than adult-onset disease, thus natural history is not well characterized. We aim to describe the characteristics and outcomes of childhood-onset HCM. METHODS AND RESULTS: We performed an observational cohort study of 7677 HCM patients from the Sarcomeric Human Cardiomyopathy Registry (SHaRe). Hypertrophic cardiomyopathy patients were stratified by age at diagnosis [<1 year (infancy), 1-18 years (childhood), >18 years (adulthood)] and assessed for composite endpoints reflecting heart failure (HF), life-threatening ventricular arrhythmias, atrial fibrillation (AF), and an overall composite that also included stroke and death. Stratifying by age of diagnosis, 184 (2.4%) patients were diagnosed in infancy; 1128 (14.7%) in childhood; and 6365 (82.9%) in adulthood. Childhood-onset HCM patients had an ∼2%/year event rate for the overall composite endpoint, with ventricular arrhythmias representing the most common event in the 1st decade following baseline visit, but HF and AF becoming more common by the end of the 2nd decade. Sarcomeric variants were more common in childhood-onset HCM (63%) and carried a worse prognosis than non-sarcomeric disease, including a greater than two-fold increased risk of HF [HRadj 2.39 (1.36-4.20), P = 0.003] and 67% increased risk of the overall composite outcome [HRadj 1.67 (1.16-2.41), P = 0.006]. When compared with adult-onset HCM, childhood-onset was 36% more likely to develop life-threatening ventricular arrhythmias [HRadj 1.36 (1.03-1.80)] and twice as likely to require transplant or ventricular assist device [HRadj 1.99 (1.23-3.23)]. CONCLUSION: Patients with childhood-onset HCM are more likely to have sarcomeric disease, carry a higher risk of life-threatening ventricular arrythmias, and have greater need for advanced HF therapies. These findings provide insight into the natural history of disease and can help inform clinical risk stratification.

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.