BACKGROUND:Massive left ventricular hypertrophy (LVH) is a risk factor for sudden cardiac death in children with hypertrophic cardiomyopathy (HCM), but little is understood about its natural history. METHODS:Patients with pediatric-onset HCM identified from 2 registries (SHaRe [Sarcomeric Human Cardiomyopathy Registry] and IPHCC [International Paediatric Hypertrophic Cardiomyopathy Consortium]) with or without massive LVH were compared. Massive LVH was defined as absolute maximal left ventricular wall thickness (MLVWT) ≥30 mm or MLVWT z score ≥+20 at <18 years of age. Data from SHaRe and IPHCC include encounters from January 1960 through March 2024 and January 1970 through March 2024, respectively. Demographic, clinical, and serial MLVWT data were collected. Composite outcomes included major ventricular arrhythmia event (sudden cardiac death, aborted sudden cardiac death, or appropriate implantable cardioverter defibrillator therapy); heart failure (HF) event (left ventricular ejection fraction <50%, New York Heart Association class III or IV, transplant, or HF-related death); major adverse cardiac event (stroke or any major ventricular arrhythmia or HF outcome aside from left ventricular ejection fraction <50%); and HCM-related mortality (sudden cardiac death or HF-related death). Time-to-event analyses were performed using Cox proportional hazards models. RESULTS:We identified 587 patients (54 female [30%]). In 186 children with massive LVH, age at diagnosis was younger (median, 9.2 years [interquartile range, 2.1-13.1 years]) versus 13.6 years (9.7-15.5 years; P<0.001) and sarcomeric genetic variants more prevalent (72% versus 61%; P=0.034), as was HCM-related mortality (unadjusted hazard ratio, 3.3 [95% CI,1.2-9.7]; P=0.026), major adverse cardiac events (hazard ratio, 2.6 [1.7-3.9]; P<0.001), major ventricular arrhythmia (hazard ratio, 3.1 [1.8-5.2]; P<0.001), and HF (hazard ratio, 1.9 [1.1-3.1]; P=0.013). These associations remained significant when adjusted for sex and age at HCM diagnosis. In 115 patients with massive LVH with serial MLVWT data (62%), MLVWT increased significantly from first to last measurements (median, 26 mm [interquartile range, 18-32 mm] versus 31 mm [26-35 mm]; P<0.001), but there was no difference between z scores (median, +22 [interquartile range, +18 to +26] versus +23 [+20 to +28]; P=0.25). The last absolute MLVWT recorded was >5 mm less than the largest recorded MLVWT in 25 patients (22%). CONCLUSIONS:In pediatric HCM, massive LVH disproportionately affects those diagnosed in early childhood with sarcomeric disease, with increased risk for adverse events. Significant MLVWT regression is seen in nearly a quarter of patients.

Background and Aims: Dilated cardiomyopathy (DCM) is a genetically heterogeneous cause of heart failure and sudden cardiac death. Many patients remain without a molecular diagnosis. MAP3K7 encodes TAK1, a serine/threonine kinase important for cardiac homeostasis. MAP3K7 variants are an established cause of syndromic disease, including cardiospondylocarpofacial syndrome (CSCF), in which DCM has been occasionally reported. Here, we demonstrate that MAP3K7 variants can cause apparently isolated DCM, expanding the phenotypic spectrum of MAP3K7-related disorders. Methods: We compiled four orthogonal lines of human genetic evidence: de novo variation in paediatric cardiomyopathy; common variant association with adult DCM; familial segregation; and rare variant enrichment in DCM cases, together with functional categorisation of rare variants. Results: In 117 paediatric cardiomyopathy trios from the 100,000 Genomes Project, two probands harboured rare de novo MAP3K7 missense variants, significantly more than expected (Bonferroni-adjusted p=0.036). Independent GWAS implicated MAP3K7 as a susceptibility locus for adult DCM. Across global DCM cohorts, we identified families harbouring rare MAP3K7 variants, including one with segregation in nine affected relatives. Rare damaging non-truncating variants were enriched in DCM cases, while truncating variants were associated with DCM in the Genomics England cohort and increased left ventricular volumes in UK Biobank. DCM-associated variants reduced TAK1 kinase activity, supporting a loss-of-function mechanism consistent with CSCF-associated alleles. Conclusion: Multiple independent lines of evidence establish an association between MAP3K7 loss of function variants and DCM. Several affected individuals lacked overt syndromic features, demonstrating that MAP3K7-related disease may present as apparently isolated DCM across the lifespan and supporting inclusion of MAP3K7 in DCM diagnostic pipelines.

Background: Genetic testing is a Class I recommendation for patients with hypertrophic cardiomyopathy (HCM). Variant classification relies on evidence from publicly available case data, evolving classification rules, and gene-disease associations. Thus, as knowledge increases, genetic variant classifications change over time. We evaluated the occurrence and reasons for variant reclassification from a large multi-center international HCM registry (Sarcomeric Human Cardiomyopathy Registry; SHaRe), with the goal to minimize uncertainty for patients and clinicians. Methods: Participants receive clinical care at specialized HCM centres. Baseline classifications were derived from the clinical genetic test report (original or updated) or prior further adjudication by SHaRe geneticists. All variants were then computationally reannotated and reevaluated during 2024-2025. Variants underwent expedited curation if no new evidence was present. The remainder underwent full manual curation using accepted criteria and classified as pathogenic/likely pathogenic (P/LP), variant of uncertain significance (VUS) and benign/likely benign (B/LB). VUS were sub-classified to high, mid or low. Results: Of 12,187 HCM patients, 8,054 (66%) had genetic testing between 1990-2024, and 4,923 (61%) had a variant identified in one of 29 ClinGen-validated HCM genes (1606 unique variants). Expedited curation was performed for 704 (44%) variants and 902 (56%) underwent manual curation. There were 1279 (79%) variants that retained their classification: 148 B/LB, 663 VUS, and 468 P/LP. While 276 (17%) variants (n=557 patients) were reclassified, including 73 upgrades: 61 from VUS to P/LP (199 patients), and 12 from B/LB to VUS. There were 203 downgrades: 108 from P/LP to VUS (196 patients), and 95 from P/LP or VUS to B/LB. VUS were additionally subclassified: 90 VUS-High, 129 VUS-Mid, 115 VUS-Low. Sub-classification of VUS resulted in less uncertainty, with 369 (40.6%) variants reclassified as VUS-Low or B/LB, indicating a very strong probability of not being HCM associated. Conclusions: Clinically meaningful reclassification occurred in 10% of variants identified in HCM probands. Most VUS were unlikely to be causal, and sub-classification has potential to reduce their burden on clinicians and families. Contemporary approaches to classification can minimize uncertainty of genetic results and highlight the need for periodic reevaluation. ### Competing Interest Statement SHaRe is supported by unrestricted funding from Bristol Myers Squibb, Cytokinetics, Alexion, and Lexicon. The sponsors had no role in the study design, data collection, data analysis, data interpretation, manuscript preparation, or the decision to submit the manuscript for publication. Dr. Ho is a consultant for or receives research funding from Bristol Myers Squibb, Pfizer, Cytokinetics, Tenaya, Biomarin, viz.AI, and Lexicon. Dr. Lakdawala recieves personal fees from Bridge Bio, Alexion, Tenaya, Cytokinetics, Bayer, and Gemma and grants from Bristol Myers Squibb and Pfizer. Dr. Owens consults for Avidity, Alexion, Bristol Myers Squibb, Bayer, Cytokinetics, Bridgebio, Braveheart, Edgewise, Imbria, Kardigan, Lexeo, Stealth, and Tenaya. Dr. Helms receives grants from Tenaya Therapeutics and Preload Therapeutics and personal fees from Lexeo Therapeutics, Preload Therapeutics, and Cytokinetics. Dr. Saberi receives grants from Bristol Myers Squibb during the conduct of the study as well as personal fees from Bristol Myers Squibb and Cytokinetics and grants from Cytokinetics, Lexicon, Edgewise, and Novartis. Dr. Parikh receives scientific advisory fees from Lexeo Therapeutics, Solid Biosciences, Constantiam Biosciences, Borrealis, and BioMarin. Dr. Ashley reported other from Personalis (founder and publicly traded stock), DeepCell (founder), Svexa (founder), Saturnus Bio (founder), Swift Bio (founder), Candela (founder, advisor), Parameter Health (founder, advisor), Pacific Biosciences (advisor, publicly traded stocks, collaborative support in kind), AstraZeneca (nonexecutive director, publicly traded stock), Dexcom (nonexecutive director), Illumina (collaborative support in kind), Oxford Nanopore (collaborative support in kind). Dr. Gray has received advisory board and education honoraria from Bristol Myers Squibb. Dr. Olivotto is a consultant for Bristol Myers Squibb, Cytokinetics, Tenaya, Lexeo, Edgewise, and Rocket Pharma. Dr. Michels is a consultant or receives research funding from Bristol Myers Squibb, Cytokinetics, Bayer, Alnylam, Biomarin, and Sanofi. Dr. Ware has consulted for MyoKardia (now Bristol Myers Squibb), Foresite Labs, and Pfizer. Dr. Crotti has consulted for Bristol Myers Squibb. Dr. Bundgaard receives lecture fees from Amgen, MSD, Sanofi, Bristol Myers Squibb, and Pfizer. Dr. Rossano is a consultant for AskBio, Astellas, CRI Biotech, Bristol Myers Squibb, Bayer, and Merck. Dr. Abrams is a consultant for Dinaqor. Dr. Maurizi has received grants from Bristol Meier Squibb, Amicus, Foundation CVCL, AICARM APS Onlus, Bangarter-Rhyner Foundation and fees (honoraria or consulting) from Bristol Meier Squibb and Academic CM. Dr. Thompson receives compensation as editor for Merck Manuals. Dr. Day receives personal fees from Lexicon Pharmaceuticals and Cytokinetics and grants from Bristol Myers Squibb. Disclosures are unrelated to current manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Each participating site has received ethics approval in accordance with local policies as per the following: ethical approval requiring informed consent was obtained from Cincinnati Childrens Hospital USA; Childrens Hospital of Philadelphia USA; Michigan Medical USA; Yale Medical USA; Royal Brompton Hospital United Kingdom; Erasmus University Medical Center The Netherlands; Florence Centre for Cardiomyopathies Italy; Sydney Local Health District Royal Prince Alfred Hospital Australia; and InCor Heart Institute University of Sao Paulo Brazil ethics committees. Waiver of consent was granted by Stanford School of Medicine USA; Brigham and Womens Hospital USA; Boston Childrens Hospital USA; Pennsylvania University Medical Center USA and Sydney Local Health District Royal Prince Alfred Hospital Australia ethics committees. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors Australian Government, https://ror.org/0314h5y94 Bristol-Myers Squibb (United States), https://ror.org/00gtmwv55 Cytokinetics (United States), https://ror.org/03tx9ss94 Alexion Pharmaceuticals (United States), https://ror.org/031ywxc85 Lexicon Pharmaceuticals (United States), https://ror.org/00v64s089

Abstract Background Rare heterozygous loss-of-function (LoF) variants in SVIL , encoding the Z-disk and costameric protein supervillin, have recently been identified as a cause of hypertrophic cardiomyopathy (HCM). Although supervillin is implicated in actin-dependent mechanotransduction, the mechanisms linking SVIL deficiency to cardiomyopathy remain poorly understood. Homozygous LoF cause a novel skeletal Myofibrillar Myopathy-10 (MFM-10) while heterozygous LoF cause HCM without skeletal myopathy. In this study we use a human model system to disentangle the LoF pathomechanism of the scaffolding protein supervillin in cardiomyocytes and its clinical implications. Methods Using CRISPR/Cas-9 we engineered a representative pathogenic LoF variant Q255X into an isogenic induced pluripotent stem cell (iPSC) line creating the heterozygous SVIL Q255X/+ and homozygous SVIL Q255X/Q255X cell lines. These lines were differentiated into iPSC-derived cardiomyocytes (iPSC-CMs) and cellular phenotypes were assessed using bulk RNA-sequencing, LC-MS proteomics, electrophysiological and calcium handling analyses, contractility measurements, sarcomere organization analysis, Seahorse metabolic flux assay, and pharmacological intervention with mavacamten. Results The Q255X variant resulted in SVIL haploinsufficiency at both RNA and protein levels with no evidence of a truncated protein. Compared with isogenic controls, SVIL Q255X/+ iPSC-CMs demonstrated action potential shortening, calcium transient elongation, sarcomeric disorganization and hypertrophy, and impaired mitochondrial respiration. Multi-omic analyses of SVIL Q255X/+ iPSC-CMs showed a profile of cellular stress and inflammation, hypertrophic and pro-fibrotic signalling, and a pseudohypoxic state driven by decreased respiration and a HIF-induced glycolytic shift. These abnormalities were not present in SVIL Q255X/Q255X cardiomyocytes, consistent with a relatively limited cardiac phenotype reported in homozygous variant carriers. Mavacamten improved sarcomeric disorganization and hypertrophy in SVIL Q255X/+ cells but did not rescue energetic compromise. Conclusions Pathogenic heterozygous SVIL LoF produces a distinct cellular phenotype characterized by impaired mechanotransduction, mitochondrial dysfunction, and maladaptive metabolic remodelling that promotes hypertrophic and pro-fibrotic signalling. These findings define a mechanistic basis for SVIL -associated cardiomyopathy and identify metabolic dysfunction as a potential therapeutic target beyond sarcomere-directed therapy. Clinical Perspective What Is New? SVIL haploinsufficiency causes HCM through a mechanism distinct from canonical sarcomeric disease, characterized by impaired mechanotransduction, mitochondrial dysfunction, and pseudohypoxia-driven metabolic remodeling. Heterozygous SVIL loss of function produces a substantially more severe cardiomyocyte phenotype than homozygous loss of function, providing a mechanistic explanation for the predominance of cardiac disease in heterozygous variant carriers. Mavacamten improves sarcomeric organization but does not restore impaired mitochondrial respiration, demonstrating that energetic dysfunction persists despite sarcomere-directed therapy. What Are the Clinical Implications? Our findings give functional evidence to support SVIL as a clinically relevant HCM disease gene and its inclusion in clinical genetic testing panels. These findings establish SVIL -associated cardiomyopathy as a mechanistically distinct form of HCM and offer insight into the pathomechanism of Z-disk and costameric HCM The persistence of mitochondrial dysfunction despite myosin inhibition suggests that drugs targeting mitochondrial bioenergetics may be a therapeutic strategy in patients with SVIL -associated cardiomyopathy.

AIMS:Sudden arrhythmic death syndrome (SADS) refers to a sudden death, which remains unexplained despite comprehensive post-mortem examination and a toxicological screen. We aimed to investigate the impact of age and sex on the overall diagnostic yield and underlying aetiology in decedents with SADS using a combined approach of familial evaluation (FE) and molecular autopsy (MA). METHODS AND RESULTS:Consecutive referrals to a single centre for FE only, MA only or both, following a SADS death were included. First-degree family members underwent comprehensive FE and decedents with post-mortem DNA were sequenced with a 36 cardiac gene panel for MA. A Bayesian framework for analysis was performed to identify associations. Among 760 SADS decedents (66% male; mean age 31 ± 12 years) the overall diagnostic yield for an inherited cardiac condition was 37% (32-42%) and 9% (6-12%) for FE and MA cohorts. In a subset where both FE and MA were performed the diagnostic yield was 45% (38-61%). The relative risk of an FE diagnosis of long QT syndrome (LQTS) or Catecholaminergic polymorphic ventricular tachycardia (CPVT) vs. remaining unexplained declined by 5.6% [RR 0.94 (0.91-0.98)] and by 11% [RR 0.89 (0.81-0.97)], for each year increase in age. Females were more likely to have a diagnosis by both FE [40% (34-45%) vs. 36% (31-41%)] and MA [15% (10-21%) vs. 6% (3-8%)]. Females [8.1% (4.1-13.4%)], were more likely to be diagnosed with LQTS than males [1.2% (0.2-2.7%)] in the MA cohort. CONCLUSION:After a SADS death, the diagnostic yield of comprehensive FE, MA, or both in an expert setting can be up to 45% with a combined approach. Females had higher diagnostic yield than males, most notable with LQTS. CPVT and LQTS diagnoses declined with increasing age. These data highlight the relative utility of FE and MA depending on age and sex for determining underlying diagnoses following SADS deaths.

Background:Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality, and a major contributor to low birth weight. Beta blockers (BB) and calcium channel blockers (CCB) are the most commonly recommended agents to treat hypertension in pregnancy. Yet it remains unknown whether these agents alter the risk of preeclampsia (PE), and if so, whether effects arise through maternal physiology or through direct fetal mechanisms. Objectives:To use drug-target Mendelian randomization (MR) to estimate the effects of genetically-proxied inhibition of beta-adrenergic and L-type calcium-channel targets on PE risk, birth weight, partitioned into maternal and fetal genetic components, and gestational age (GA). Methods:We constructed instruments from genome-wide significant, LD-independent variants within prespecified windows around systolic blood pressure (SBP) modulating drug targets in addition to a genome-wide SBP instrument (European ancestry). Outcomes comprised of PE (16,349 cases / 595,135 controls), maternal and fetal genetic effects on birth weight (n≈210,267 and n≈298,142), and GA (n≈151,987). Two-sample MR estimated effects per 5mmHg decrease in SBP. Bayesian colocalization assessed shared causal variants. Multiple testing was controlled with Benjamini-Hochberg correction. Results:Genetically lower SBP was associated with reduced PE risk and modest increases in birth weight and GA. BB (ADRB1) target inhibition showed no convincing reduction in PE risk but was associated with lower birth weight, with associations predominantly through direct fetal genetic effects and strong colocalization at ADRB1 with fetal birth-weight signals. In contrast, CCB targets collectively associated with lower PE risk without consistent evidence of fetal growth impairment; colocalization support for individual CCB loci was limited. Sensitivity analyses (heterogeneity, pleiotropy) did not materially alter these patterns where instrument counts permitted. Conclusions:Drug-target MR suggests that BB pathways are unlikely to meaningfully reduce PE and are linked to reduced fetal growth - chiefly via direct fetal mechanisms. In contrast, CCB pathways are associated with lower PE risk and largely neutral fetal growth effects. These findings support prioritizing CCBs for evaluation in comparative trials of PE prevention.

Background Distinguishing pathogenic variants from those that are rare but benign remains a key challenge in clinical genetics, especially for variants not previously observed and characterised in humans. In vitro and in vivo functional characterisation are typically resource intensive, and model systems may not accurately predict influence on human disease. Many in silico tools have been developed to predict which variants are disease-causing, but typically lack precision. Here we demonstrate the applicability of a framework, called Paralogue Annotation, that draws on information from previously-characterised variants in homologous proteins to predict whether variants in a gene of interest are likely disease causing. Methods We assessed the performance of Paralogue Annotation through three orthogonal approaches: (1) comparison to established in silico variant prediction tools using 47,360 missense variants from ClinVar across 3,524 genes representing a broad range of diverse protein classes, by calculating precision and sensitivity; (2) evaluation against large-scale functional assays of variant effect in TP53 and PPARG ; and (3) comparing odd ratios calculated from case-control association tests for inherited cardiac arrhythmia syndromes, and neurodevelopmental disorders with epilepsy, stratifying variants by Paralogue Annotation. Results Paralogue Annotation correctly annotates 4,328 ClinVar pathogenic variants, with 245 false positives, yielding a precision of 0.95. This increases to 0.99 with more stringent annotation parameters (requiring greater conservation of amino acids between annotated orthologues) at the expense of sensitivity. Compared to established tools, Paralogue Annotation has higher precision for identification of pathogenic variants, albeit with lower sensitivity across diverse test sets. Extending the technique by transferring annotations between homologous protein domains, rather than full-length protein paralogues, increases sensitivity. Rare variants predicted pathogenic by Paralogue Annotation were more strongly disease-associated (increased odds ratio) than unstratified rare variants for six out of eight genes tested with case-control cohort approaches. Conclusions Paralogue Annotation has high precision for detection of pathogenic missense variants, outperforming in silico methods where data are available to make a prediction. As the number of characterised variants increases in reference datasets such as ClinVar, Paralogue Annotation will further increase in sensitivity and applicability.

BACKGROUND:Filamin-C (FLNC) gene variants are associated with cardiac and skeletal muscle diseases including a clear role of loss-of-function variants in dilated cardiomyopathy. OBJECTIVE:This study aimed to assess the contribution of rare FLNC variants to hypertrophic cardiomyopathy (HCM)/restrictive cardiomyopathy (RCM). METHODS:Family-based studies in 2 specialist services and statistical modeling of rare FLNC missense variants were conducted, using a cohort of 3289 sarcomere-negative HCM cases and 122,348 genome aggregation database controls. RESULTS:Clinical evaluation of patients with HCM/RCM and a rare FLNC variant identified a distinct electrocardiographic (ECG) repolarization phenotype in 37% (19 of 51 individuals, from 12 families), which was observed in only 1.0% of a control HCM cohort (2 of 197). FLNC variant carriers with the characteristic ECG had smaller left ventricular cavity size, lower contractility, and more severe diastolic dysfunction and were more likely to have a restrictive phenotype. Heart failure death, transplant, or cardiac arrest occurred in at least 1 individual in 7 of the 12 families (58%) in the "ECG-positive" group, and musculoskeletal abnormalities were present in 4 families (33%). 5 of 12 variants (41.7%) in the "ECG-positive" group cosegregated, and 2 were apparently de novo. 11 variants were missense, and 1 splice site. Rare FLNC missense variant burden indicated a low case excess among all HCM cases (etiologic fraction, 0.45; 95% confidence interval, 0.36-0.54), but in "ECG-positive" cases the etiologic fraction was substantially higher (0.98; 95% confidence interval, 0.97-0.99). CONCLUSION:Pathogenic FLNC variants in patients with HCM/RCM are nontruncating and cause a discrete phenotype comprising a characteristic ECG, hypertrophic and restrictive features without hypercontractility, and extracardiac abnormalities.

BACKGROUND:Patients with phenotypically mild hypertrophic cardiomyopathy (HCM) do not require symptom management, but may be at an earlier stage in the disease course, with potential to benefit from disease-modifying therapies. However, little is known about the natural history and predictors of major adverse cardiovascular events (MACE). OBJECTIVES:Using the Sarcomeric Human Cardiomyopathy Registry, we identified predictors of incident MACE and characterized disease progression in phenotypically mild HCM. METHODS:Phenotypically mild HCM was defined as: having shorter disease duration (<10 years since diagnosis or age ≤30 years), no previous MACE, being NYHA functional class I, and having a left ventricular (LV) maximal wall thickness (MWT) <25 mm. These individuals were followed prospectively for the development of symptoms or MACE: atrial fibrillation (AF), malignant ventricular arrhythmia (MVA) (sudden cardiac death, resuscitated arrest, or appropriate defibrillator therapy), heart failure (HF) (cardiac transplantation, LV assist device implantation, LV ejection fraction <35%, or NYHA functional class III or IV symptoms), stroke, or all-cause mortality. Cox regression identified MACE predictors. Linear and latent class mixed models characterized LV remodeling trajectories and risk clusters. RESULTS:Of 2,500 participants with phenotypically mild HCM (mean age 43 years, 31% women) followed for a mean duration of 7 ± 6 years, 534 (21%) developed MACE, including 289 with AF, 69 with MVA, and 193 with HF. Individuals who progressed from NYHA functional class I to ≥ II symptoms during follow-up (n = 585, 23%) were 2.79 times (95% CI: 2.30-3.39 times) more likely to experience MACE. Age at baseline (HR: 1.24; 95% CI: 1.17-1.32 per 10-year increase), body mass index (HR: 1.10; 95% CI: 1.01-1.21 per 5-kg/m2 increase), left atrial (LA) diameter (HR: 1.16; 95% CI: 1.09-1.25 per 5-mm increase), LV MWT (HR: 1.27; 95% CI: 1.10-1.46 per 5-mm increase), and LV outflow tract (LVOT) gradient (HR: 1.08; 95% CI: 1.05-1.12 per 15-mm Hg increase) associated with higher MACE rates. LV late gadolinium enhancement presence was associated with 36% (95% CI: 5%-76%) higher hazard of MACE. Remodeling trajectories during follow-up predicted risk with each 0.5 mm/year steeper increase in LA diameter associating with doubled AF (HR: 2.24; 95% CI: 1.69-2.97) and HF rates (HR: 2.22; 95% CI: 1.62-3.04) and each 0.5 mm/year steeper LV MWT increase associating with doubled MVA rates (HR: 1.92; 95% CI: 1.38-2.69). Higher sustained values and/or steeper increases in LA diameter, LV MWT, or LVOT gradient associated with the highest MACE rates. CONCLUSIONS:Approximately 21% of patients with phenotypically mild HCM developed MACE over medium-term follow-up. Older age, symptoms development, and increasing LA diameter, LV hypertrophy, or LVOT gradient associated with MACE, particularly in instances of steeper rate of change. These findings can guide management strategies and inform future studies of disease-modifying therapies.

BACKGROUND:Atrial fibrillation (AF) is heritable and its complex underlying genetic substrate is gradually being unraveled. OBJECTIVES:We sought to explore the impact of disease-causing cardiomyopathy variants on the risk of AF after adjustment for incident ventricular cardiomyopathy and clinical heart failure in 2 cohort studies (UK Biobank [UKB] and All of Us [AoU]) and evaluate the utility of polygenic risk scores (PRS) to further discern the risk of atrial and ventricular phenotypes in carriers. METHODS:Cox regression was used to evaluate for associations between disease-causing variants within genes for 3 cardiomyopathies (dilated cardiomyopathy [DCM], hypertrophic cardiomyopathy [HCM], and arrhythmogenic right ventricular cardiomyopathy) and AF. Disease-specific PRSs for AF, DCM, and HCM stratified study participants into quintiles. A HR random-effects meta-analysis was performed using the DerSimonian-Laird method. The Kaplan-Meier method was used to ascertain cumulative incidence from birth to 75 years of age. RESULTS:Among 655,796 individuals from UKB and AoU, presence of a disease-causing variant was associated with an increased AF hazard (HR: 1.73; 95% CI: 1.59-1.89; P < 0.001), including after adjustment for incident ventricular cardiomyopathy or clinical heart failure (adjusted to HR: 1.55; 95% CI: 1.46-1.64, P < 0.001). The cumulative AF risk for study participants with a putative disease-causing rare variant and a PRSAF within the top-risk quintile ranged from 32.5% (UKB) to 32.4% (AoU) relative to 9.8% (UKB) and 11.0% (AoU) for individuals without a putative disease-causing variant and a PRSAF within the lowest-risk quintile. The absolute cumulative cardiomyopathy risk among study participants with both a putative disease-causing variant and a disease-specific PRS within the top-risk quintile ranged from 5.9% (UKB) to 15.2% (AoU) for DCM and from 11.7% (UKB) to 19.1% (AoU) for HCM. CONCLUSIONS:Genetic variants that cause cardiomyopathy also increase the risk of AF, even in individuals without heart failure or overt ventricular disease. Combining disease-specific PRSs with these variants helps identify whether a person is more likely to develop atrial or ventricular disease. Although discovered as causes of cardiomyopathy, these genes often have an equal or greater impact on the risk of AF.

Aims:A significant proportion of type 2 diabetes cases remain undiagnosed despite screening advances, carrying substantial cardiometabolic risk. Artificial intelligence-enhanced electrocardiography (AI-ECG) detects subtle ECG changes in subclinical disease, potentially enabling opportunistic screening. Methods and results:We developed AI-ECG Risk Estimator for Diabetes Mellitus (AIRE-DM), a convolutional neural network with discrete-time survival loss, for diagnosis of prevalent and prediction of incident type 2 diabetes. It was trained on 1 163 401 ECGs from 189 537 individuals from Beth Israel Deaconess Medical Center (BIDMC) and externally validated in UK Biobank (UKB; n = 65 606) and ELSA-Brasil (n = 13 739). AI-ECG Risk Estimator for Diabetes Mellitus demonstrated moderate discrimination for prevalent type 2 diabetes (area under the receiver operating characteristic curve: BIDMC 0.724, UKB 0.733, ELSA-Brasil 0.706) and incident type 2 diabetes (C-index: BIDMC 0.667, UKB 0.688, ELSA-Brasil 0.625). The highest AIRE-DM risk quartile had elevated incident diabetes risk vs. the lowest (hazard ratio: BIDMC 4.75, UKB 7.52, ELSA-Brasil 3.96). AI-ECG Risk Estimator for Diabetes Mellitus was non-inferior to the American Diabetes Association Diabetes Risk Test in BIDMC, with improved predictive accuracy when combined. In normoglycaemic patients, AIRE-DM was superior to glycated haemoglobin (HbA1c) for predicting incident diabetes in BIDMC and non-inferior in ELSA-Brasil. The highest risk quartile reached 5% cumulative type 2 diabetes mellitus incidence 5.4 years (BIDMC) and 4.8 years (ELSA-Brasil) earlier than the lowest risk quartile, after adjusting for HbA1c, age, and sex. Phenome- and genome-wide association studies revealed biologically plausible associations with glucose regulation, cardiac morphology, diastolic dysfunction, arterial stiffness, and lipid metabolism. Conclusion:AI-ECG Risk Estimator for Diabetes Mellitus detects prevalent type 2 diabetes and predicts incident disease, uniquely identifying high-risk individuals within the normoglycaemic range. Combined with clinical scores or biomarkers, it enhances risk stratification, enabling earlier intervention.

BACKGROUND:Spontaneous coronary artery dissection (SCAD) is an uncommon cause of myocardial infarction that disproportionately affects women, particularly during pregnancy and the peripartum period. Limited understanding of its underlying pathophysiology hinders the development of effective preventive and therapeutic strategies. METHODS:This study investigated associations between genetically predicted circulating proteins and tissue-specific RNA levels with genetically predicted SCAD risk using Mendelian randomization and Bayesian colocalization. Genetic scores for >1500 circulating proteins were derived from the UK Biobank (N=34 557) and deCODE (N=35 559). Scores for 13 848 gene transcripts in arterial and fibroblast tissues were generated from Genotype-Tissue Expression data. Associations between these scores and SCAD were assessed in a genome-wide association study meta-analysis of 1917 individuals with SCAD and 9292 controls. Findings were validated in vitro using mass spectrometry-based proteomic analysis of extracellular vesicles from 50 patients with SCAD and 50 healthy controls. RESULTS:Genetic associations of 4 circulating proteins with SCAD (AFAP1 [actin filament-associated protein 1], ECM1 [extracellular matrix protein 1], SPON1 [spondin 1], and STAT6 [signal transducer and activator of transcription 6]) were identified. Two were supported by gene expression data (AFAP1 and ECM1), and one by tissue-specific Bayesian colocalization analyses (ECM1). Protein interaction mapping identified potential shared pathways through the JAK-STAT (Janus kinases and signal transducers and activators of transcription) signaling pathway and inflammatory regulation. Mass spectrometry-based proteomic analysis demonstrated that ECM1 was significantly upregulated in SCAD cases versus controls. CONCLUSIONS:Integrative analysis of proteomic, transcriptomic, and experimental data revealed 4 circulating proteins genetically associated with SCAD risk, with ECM1 emerging as a key protein with a likely causal role in SCAD pathogenesis. These findings highlight biological pathways for mechanistic studies and protein targets for potential therapeutic interventions.

BACKGROUND:Dilated cardiomyopathy (DCM) and arrhythmogenic cardiomyopathy (ACM) are progressive cardiac muscle disorders with phenotypic and genetic overlap. Although a male predominance is noted in DCM/ACM, it remains unclear whether this extends to specific genetic subtypes or reflects variation in disease stage and whether sex influences age-dependent disease onset across pediatric and adult groups. OBJECTIVES:The aim of this study was to define sex-based differences in genetic architecture and age at diagnosis of DCM/ACM across pediatric and adult populations. METHODS:Genetically tested adult and pediatric DCM/ACM patients and asymptomatic genotype-positive relatives enrolled in the multicenter SHaRe (Sarcomeric Human Cardiomyopathy Registry) were analyzed. Sex distribution across 27 DCM- and ACM-associated genes was evaluated using logistic regression. Age at diagnosis was compared across sex and genes using Kaplan-Meier cumulative incidence estimates. RESULTS:Among 3,410 patients, a 61% male predominance was present across subgroups of genotype positive, genotype negative, and variants of uncertain significance (P = 0.008), with significant gene-specific variation. TTN truncating variants (TTNtv) were less common in females (OR: 0.42 [95% CI: 0.33-0.54]; P < 0.01), while DSP (OR: 3.3 [95% CI: 2.35-4.78]; P < 0.01) and grouped non-TTN sarcomeric variants (ACTC1, TNNT2, MYH7, TNNC1, TNNI3, and TPM1) were more common (OR: 1.68 [95% CI: 1.15-2.47]; P < 0.001) in females compared with males with DCM/ACM. Age at diagnosis was comparable between sexes, except in TTNtv carriers, among whom males exhibited earlier disease onset compared with females (median age 45 years [Q1-Q3: 33-55 years] vs 51 years [Q1-Q3: 38-60 years]; P = 0.003). Pediatric-onset (diagnosis at <18 years) cases (n = 174) also demonstrated a male predominance (60% male) but had distinct genetic characteristics, with non-TTN sarcomeric and PKP2 variants being more prevalent compared with adult-onset disease (non-TTN sarcomeric OR: 5.5 [95% CI: 3.3-8.9; P < 0.01]; PKP2 OR: 2.8 [95% CI: 1.1-5.2; P < 0.05]) and a bimodal age at onset peaking in infancy and adolescence. CONCLUSIONS:Gene-specific sex differences influence disease prevalence and age at onset in DCM/ACM. TTNtv are more common with earlier onset in males, whereas DSP and non-TTN sarcomeric variants predominate in females. Pediatric-onset DCM/ACM is genetically distinct and caused predominantly by non-TTN sarcomeric variants, especially during infancy. These findings support age- and sex-informed surveillance strategies and prioritize future research into the mechanisms of observed sex-based differences.

To facilitate both disease research and personalised medicine, there is an urgent need for accessible, structured data models describing the molecular basis of genetically determined disease. Gene2Phenotype is a database of expert-curated monogenic gene-disease associations which was established in 2012 to enable efficient prioritisation of likely diagnostic genomic variants. Initially focused on developmental disorders, it has since been extended to support cardiac, eye, skeletal and skin disorders and germline cancer predisposition.We have redesigned and extended Gene2Phenotype which now openly shares standardised, structured models of rare monogenic diseases, detailing genotype, molecular mechanism and associated phenotypes, curated from scientific literature. The updated platform, which includes a new API, enabling programmatic access, improves the findability, accessibility, interoperability and reusability of detailed rare monogenic disease association data. These data have the potential to accelerate disease research, clinical diagnosis, treatment selection and the development of novel therapies. Gene2Phenotype is available at https://www.ebi.ac.uk/gene2phenotype/.

BACKGROUND:Sarcomere gene variants are a key cause of hypertrophic cardiomyopathy (HCM), and have been associated with worse prognosis. However, it is unclear how comorbidities influence clinical trajectories, the timing of events, and causes of death in sarcomeric and nonsarcomeric HCM. METHODS:We conducted a multicenter longitudinal cohort study of genotyped patients with HCM in the Sarcomeric Human Cardiomyopathy registry (SHaRe). Patients were classified as sarcomeric HCM (pathogenic/likely pathogenic sarcomere variant) or nonsarcomeric HCM (genetically elusive). The influence of genetic classification and comorbidities on the sequence of cardiovascular events were assessed in time-varying Cox proportional hazards models. RESULTS:Among 6120 patients (40% women; 87% probands; 50% sarcomeric HCM), followed for a median of 5.3 years, sarcomeric HCM (n=3082) was associated with a younger age at diagnosis (median 38.1 versus 54.3 years; P<0.001), a higher proportion of women and less obesity, hypertension, and left ventricular (LV) obstruction. After age standardization, sarcomeric HCM was associated with a higher burden of atrial fibrillation (age-standardized incidence [ASI] ratio, 1.28 [CI, 1.16-1.40]), LV systolic dysfunction (ASI ratio, 1.31 [CI, 1.15-1.48]), and ventricular arrhythmias (ASI ratio, 1.37 [CI, 1.17-1.52]) than nonsarcomeric HCM. All-cause mortality was similar (10.4% versus 9.4%; P=0.20); however, patients with sarcomeric HCM died younger (mean 7.8 years; P<0.001), with model-based survival-analysis estimating 3.5 life-years lost between ages 44 and 85. Sarcomeric HCM was also associated with higher HCM-related mortality (hazard ratio [HR], 1.61 [CI, 1.18-2.20]). Temporal analysis identified atrial fibrillation as the strongest disease-modifier, increasing the risk of LV systolic dysfunction (HR, 2.54 [CI 2.07-3.11]), ventricular arrhythmias (HR, 3.13 [CI, 2.36-4.20]), and mortality (HR, 1.94 [CI, 1.64-2.31]) in both groups. Genotype-interaction analyses demonstrated a larger impact of atrial fibrillation and LV systolic dysfunction on adverse outcomes in sarcomeric versus nonsarcomeric HCM, with effect ratios up to 1.98 for severe heart failure and 2.01 for mortality (both P<0.01). CONCLUSIONS:Genotype can refine risk stratification and inform clinical management in HCM. Sarcomeric HCM is associated with worse prognosis and may benefit from more vigilant surveillance for arrhythmias and systolic dysfunction, with a lower threshold for advanced therapies. Comorbidities, including hypertension and obesity, may be modifiable risk factors for patients with nonsarcomeric HCM.

Gene panels represent a widely used strategy for genetic testing in a vast range of Mendelian disorders. While this approach aids reliable bioinformatic detection of short coding variants, it often fails to detect many larger variants. Recent studies have recommended the adoption of pangenome references (as opposed to linear reference genomes like GRCh38) to augment detection of large variants from targeted sequencing, potentially providing diagnostic laboratories with the possibility to streamline diagnostic work-ups and reduce costs. Here, we analyze 1969 cardiomyopathy cases and 1805 controls sequenced with the Illumina Trusight Cardio panel using a pangenome-based workflow (GRAF) and five conventional orthogonal methodologies (GATK HaplotypeCaller, GATK-gCNV, ExomeDepth, Manta and Lumpy-SV) to detect variants ≥ 20 bp in size. Following lab-based variant validation by means of PCR and Sanger sequencing, we show that GRAF conjugates higher precision and recall (F1 score 0.86) compared with other methods (F1 0-0.57) in detecting potentially pathogenic variants ≥ 20 bp from short-read panel data. Results were complemented by a comparison of the tools’ performance in detecting ground truth variants on reference sample HG002 from Genome In A Bottle, which confirmed GRAF to outperform other tools also on exome sequencing (F1 0.97 vs. 0-0.94). Notably, in the HG002 benchmark dataset, GRAF also showed slightly improved performance compared to GATK HaplotypeCaller in the identification of small variants (1–19 bp; F1 0.975 vs. 0.968). Our results indicate that pangenome-based workflows aid improved detection of large variants from targeted sequencing data in the clinical context and suggest that they may contribute to more unified variant detection frameworks for all-size genetic variants in the future.