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Book chapterAbdi A, Jeviskov J, Hussain A, et al., 2027,
Regional Myocardial Strain Estimation with MyoTrackerChrono
, Pages: 131-142Cardiovascular diseases require precise, non-invasive diagnostic tools to assess regional myocardial function. While Speckle Tracking Echocardiography (STE) is widely used to measure myocardial strain, traditional block-matching and optical flow algorithms frequently fail due to acoustic noise and out-of-plane speckle decorrelation. This paper introduces MyoTrackerChrono, a hybrid deep learning architecture designed for robust, sparse point tracking in echocardiography. By integrating a Temporal Adapter between a spatial convolutional encoder and a tracking transformer, the model explicitly aggregates temporal context early in the feature extraction phase. This allows for stable tracking even during rapid cardiac phases or momentary signal loss. Validated on physics-based synthetic benchmarks, MyoTrackerChrono improves pixel-level tracking accuracy (Mean Absolute Error) by 33.0% over baseline models and reduces strain estimation error in mechanically complex mid-wall segments by over 64%. Furthermore, the architecture operates at an effective inference rate of 1382 FPS, confirming its feasibility for rapid post-acquisition clinical deployment.
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Book chapterUfumaka I, Alibakhshi A, Fernandes P, et al., 2027,
Multi-Expert Consensus as a Label-Free Quality Surrogate for Echocardiographic LV Segmentation
, Pages: 235-247Automated left ventricular (LV) segmentation is fundamental to echocardiographic assessment of cardiac function, yet most models report aggregate performance without accounting for variation in image quality. In clinical practice, poor acoustic windows produce ambiguous endocardial boundaries where both automated predictions and expert annotations become unreliable. We propose a label-free quality surrogate, q<inf>dice</inf>, derived from pairwise Dice disagreement across 11 independent clinical experts, requiring no explicit quality labels. Using this surrogate, we conduct a quality-stratified evaluation of three architecturally distinct models (T1, T2, and T3) on the UnityLV-MultiX dataset. T1 is a sparse keypoint model, T2 uses a dense binary mask representation, and T3 is a triple-head hybrid architecture in which predicted keypoint heatmaps guide segmentation feature attention through a differentiable spatial gate. All models are trained on a single-expert dataset and evaluated against a multi-expert consensus using Dice, HD95, MSD, and ejection fraction MAE. A leave-one-out analysis enables direct comparison of model and expert consistency against a common multi-expert reference. All three models exceed every individual expert in overall Dice. T3 achieves the highest Dice across all quality bands (0.937, 0.952, and 0.960 at Q<inf>low</inf>, Q<inf>mid</inf>, and Q<inf>high</inf> respectively; 0.949 overall). It shows the lowest EF MAE overall (5.24%), representing a 38% reduction relative to the expert mean (8.46%). T3’s keypoint and segmentation heads agree far more closely with each other than any cross-model pair (ρ=0.856), yet residual disagreement between the two heads concentrates on low-quality frames, providing a built-in, single-inference reliability flag without any external reference.
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Book chapterAlibakhshi A, Jevsikov J, Ufumaka I, et al., 2027,
Phase-Guided Quality Regression in Apical Echocardiography via CNN-LSTM: A Systematic Backbone Benchmarking Study
, Pages: 17-30Apical view acquisition errors in echocardiography can lead to inaccurate estimation of clinically important measurements, including ventricular volume, ejection fraction, and strain. In this work, we propose a phase-centred CNN-LSTM framework for automated regression of apical image quality in echocardiographic studies, investigating which backbone architecture can most effectively predict a continuous reduction in left ventricular long-axis length without relying on explicit mask-based measurements. A patient-specific reference standard was generated by first identifying end-diastole using a phase detection model and then measuring LV long-axis length. For each patient, the scan with the maximum observed LV length served as the patient-specific reference, and deviations across other scans were quantified using a heuristic formulation based on relative length reduction. Using this systematic labelling strategy, eight CNN-LSTM backbone architectures were trained and compared on 1,799 echocardiographic studies from 100 patients, comprising apical four-chamber and apical two-chamber views, with the goal of directly regressing the degree of length reduction from raw image sequences alone. Across backbone comparisons, convolution-based models showed the strongest overall performance, with EfficientNetV2 achieving the lowest regression error for apical four-chamber views and ConvNeXt-Tiny and ResNet50-level models showing competitive performance in apical two-chamber views. To assess clinical relevance, two expert-annotated evaluation datasets, each labelled by 10 experts, were used for ranking-based comparison against expert consensus. The proposed AI approach demonstrated agreement with expert consensus at a level comparable to several human experts and showed meaningful ability to identify scans associated with overestimation and underestimation of key echocardiographic measurements. These findings support the potential of backbone-driven regression of apical view qua
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Journal articleMazzarotto F, Kalay O, Arslan E, et al., 2026,
Pangenomes aid accurate detection of large insertions and deletions from targeted sequencing: the case of cardiomyopathies
, Genome Medicine, Vol: 18, ISSN: 1756-994XBackgroundGene 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.MethodsHere, 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.ResultsFollowing 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).ConclusionsOur 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.
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Journal articlePalermi S, Zeidaabadi B, Vecchiato M, et al., 2026,
Development and external validation of AI-ECG models in athlete pre-participation screening: Performance, limitations, and clinical implications.
, Int J Cardiol, Vol: 461BACKGROUND: Pre-participation screening (PPS) in competitive athletes aims to identify cardiovascular diseases associated with sudden cardiac death (SCD). Although the 12‑lead electrocardiogram (ECG) represents the cornerstone of PPS, structural abnormalities may demonstrate limited or incomplete electrical expression, particularly in asymptomatic athletes with physiological remodeling. Artificial intelligence (AI)-enabled ECG models have shown promising performance in hospital-based populations, but their transportability to low-prevalence athlete screening environments remains uncertain. OBJECTIVES: To develop and externally validate a deep learning (DL)-based AI-ECG ensemble model for detecting imaging-confirmed structural heart disease in competitive athletes undergoing PPS. METHODS: A convolutional neural network (CNN) ensemble was trained using hospital-derived ECG images from Beth Israel Deaconess Medical Center (BIDMC, Boston, USA) and externally validated in the Italian Team for Athlete CARDiac evaluation and AI-based Risk prediction (ITACARD-AI) registry. Separate CNNs were developed for valvular heart disease (VHD) and cardiomyopathies (CM) and combined using XGBoost meta-learning. Model performance was assessed using area under the receiver operating characteristic curve (AUROC), subgroup analyses, and threshold-based evaluation. RESULTS: The ITACARD-AI cohort included 1115 competitive athletes (mean age 26 ± 13 years; 70% male), including 48 athletes (4.3%) with VHD and 30 (2.7%) with CM. External validation demonstrated substantial performance degradation compared with hospital-based internal validation. AUROC values decreased to 0.70 (95% CI 0.64-0.75) for VHD and 0.69 (95% CI 0.60-0.78) for CM, indicating only modest discrimination in the screening population. Threshold analyses showed high negative predictive values (∼99%) but persistently low positive predictive values (≤8%), reflecting limited disease enrichment and st
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Journal articleMcGurk K, Curran L, Tayal U, 2026,
Rethinking myocarditis through genetics
, Journal of the American College of Cardiology, ISSN: 0735-1097 -
Journal articleAlibakhshi A, Fernandes P, Serej ND, et al., 2026,
From Relative Annotation to Pairwise Learning for Assessing Echocardiographic Rotational Alignment.
, Ultrasound Med BiolOBJECTIVE: To evaluate whether preserving relative expert-derived structure during model training improves the automated assessment of rotational misalignment in apical four-chamber echocardiographic images. METHODS: A multi-expert dataset of apical four-chamber images was annotated using multiple-image ranking to derive consensus rotational orderings along a clockwise-to-anti-clockwise continuum. Conventional pointwise regression models were compared with shared-weight pairwise models that received two images and predicted the signed difference between their consensus rotational scores. Performance was evaluated across three independent expert-ranked test sets using pairwise agreement and Spearman correlation. Robustness was further assessed using leave-one-expert-out and cycle-consistency analyses, with saliency-based visualization used to examine the image regions influencing predictions. RESULTS: Pairwise learning increased the mean pairwise agreement from 74.86% to 84.29% and the mean Spearman correlation from 67.74% to 85.43% compared with pointwise regression. The best pairwise model achieved a pairwise agreement of up to 87.81% and a Spearman correlation of up to 91.23%. The performance remained stable when individual annotators were excluded, and a cycle-consistency analysis demonstrated few cyclic preferences on independent test data. Visual explanation maps indicated model attention to clinically relevant cardiac anatomy. CONCLUSION: Training directly on relative expert-derived structure improved agreement with multi-expert consensus compared with conventional pointwise regression. Pairwise learning therefore provides a robust framework for assessing qualitative, continuous echocardiographic image-quality attributes such as rotational alignment.
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Journal articleRowin EJ, Maron BJ, Siontis KC, et al., 2026,
International Experience With Implantable Cardioverter Defibrillators for the Prevention of Sudden Death in High-Risk Patients With Hypertrophic Cardiomyopathy.
, Circulation, Vol: 154, Pages: 1290-1305BACKGROUND: Implanted cardioverter-defibrillators (ICDs) have been used in patients with hypertrophic cardiomyopathy (HCM) to prevent sudden death, and have proven lifesaving for many patients. However, experience with ICD therapy has largely been derived from relatively small HCM cohorts confined to specific countries or regions of the world. Therefore, we sought to determine the effectiveness of ICDs in preventing sudden death due to life-threatening ventricular arrhythmias in a large international multicenter HCM population. METHODS: Databases from 25 HCM centers (8 in the United States, 9 in Europe, 4 in Asia, and 1 each in Australia, Africa, Mexico, and South America) were retrospectively interrogated to identify consecutive patients with HCM with ICDs (1992 to 2024) followed for 7±6 years (up to 32 years) for clinical outcomes. RESULTS: A total of 3387 patients were identified (63% men). They had a mean left ventricular thickness of 22±7 mm. The participants had received ICDs at a mean age of 47±17 years. Over follow-up, 550 patients (16%) experienced ≥1 appropriate ICD therapy (2.6%/y), including 86 of the 247 implanted for secondary prevention (35% [6.4%/y]) and 464 of the 3140 implanted for primary prevention (15% [2.2%/y]). Appropriate therapy occurred in the 464 primary prevention patients at a mean age of 49±17 years, with a median time to first appropriate therapy of 4 years after ICD implantation; 16% of these received their first appropriate therapy ≥10 years after implantation, and 47% experienced multiple interventions. Independent predictors of appropriate ICD therapy included unexplained syncope, left ventricular apical aneurysms, left ventricular systolic dysfunction, and nonsustained ventricular tachycardia on ambulatory monitoring. Of the 3140 primary prevention patients, 2946 survived (94%) and 194 died (6%) (0.8%/y), including 68 due to HCM (0.3%/y), predominantly of end-stage heart failure (n=43) or stroke (
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Journal articleXu W, Sa F, Song Y, et al., 2026,
Cardiac MRI-Derived Right Ventricular Strain for Risk Stratification in Pediatric and Adolescent Arrhythmogenic Cardiomyopathy: A Multicenter Cohort Study.
, JACC Cardiovasc Imaging, Vol: 19, Pages: 1222-1235BACKGROUND: Pediatric and adolescent arrhythmogenic cardiomyopathy (ACM) is a clinically severe phenotype that remains underrepresented in cardiac magnetic resonance (CMR) research. The prognostic value of CMR-derived right ventricular deformation analysis in this population is unclear. OBJECTIVES: This study sought to describe the burden of severe cardiac outcomes in pediatric and adolescent ACM, and to assess the prognostic and incremental value of CMR-derived right ventricular global longitudinal strain (RVGLS) for risk stratification when incorporated into conventional clinical and CMR markers. METHODS: This multicenter study included consecutive pediatric and adolescent patients (≤21 years of age) with ACM who underwent baseline CMR evaluation. We assessed clinical, electrocardiographic, and CMR parameters according to the 2010 Task Force Criteria, along with biventricular strain parameters. Severe cardiac outcomes were defined as a composite of malignant ventricular arrhythmias (MVAs), heart transplantation, and heart failure-related death. RESULTS: The cohort included 102 patients (16.3 ± 3.4 years; 72% male) and 95 controls (mean age: 15.6 ± 3.3 years; 70% male). During a median of 58-month follow-up, 51 (50%) patients experienced severe cardiac outcomes and 28 (27.5%) MVA outcomes. Reduced RVGLS was independently associated with severe cardiac outcomes (HR: 1.14; P = 0.004) and MVA outcomes (subdistribution HR: 1.15; P < 0.001) after adjustment for clinical and conventional CMR parameters. Incorporation of RVGLS significantly improved prediction of severe cardiac outcomes beyond both right ventricular-based and left ventricular-based multivariable models, with significant improvement in discrimination and reclassification. Kaplan-Meier analysis further showed that RVGLS ≥-12.2% identified patients at higher risk of severe cardiac outcomes and MVA outcomes (both log-rank P < 0.001). CONCLUSIONS: Pediatric and adolescent ACM manifest
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Journal articleRisum N, Philbert BT, Svendsen JH, et al., 2026,
Direct His/LBB pacing as an alternative to biventricular pacing in patients with HFrEF and a typical LBBB: Design and rationale for the His-Alternative II trial.
, Am Heart J, Vol: 300BACKGROUND: Cardiac resynchronization therapy (CRT) using biventricular pacing (BiV-CRT) is an established treatment for patients with symptomatic heart failure, reduced left ventricular ejection fraction, and left bundle branch block (LBBB), leading to improvements in symptoms, ventricular function, exercise capacity and survival. Despite these benefits, up to one third of patients fail to respond optimally with no clinical improvement despite meeting current criteria for implantation. Conduction system pacing (CSP), delivered via His bundle pacing or left bundle branch area pacing, has emerged as an appealing alternative by directly engaging the native His-Purkinje system. However, randomized data directly comparing CSP-based CRT with conventional BiV-CRT remain limited. STUDY DESIGN: His-Alternative II is an investigator-initiated, multicenter, randomized non-inferiority trial designed to evaluate whether CRT delivered via CSP is non-inferior to conventional biventricular pacing with respect to left ventricular reverse remodeling. The study enrolls patients with symptomatic heart failure (New York Heart Association class II to III), left ventricular ejection fraction ≤35%, strict LBBB by electrocardiographic criteria, and optimal medical therapy. A total of 150 patients were randomized with a 1:2 randomization ratio to receive BiV-CRT or CSP-based CRT (His bundle pacing or left bundle branch pacing) and followed for 6 months. The primary endpoint is change in left ventricular end-systolic volume assessed by echocardiography; a surrogate endpoint consistently associated with long-term outcomes in CRT populations. Secondary endpoints include functional capacity, symptomatic status, quality of life, electrical resynchronization, and device-related complications. CONCLUSIONS: His-Alternative II is designed to determine whether CSP-based CRT can achieve left ventricular reverse remodeling comparable to that obtained with conventional BiV-CRT. The study will provide
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Journal articleEl-Medany A, Birdi AR, Abraham A, et al., 2026,
From wrist to heart: clinical validation and real-world translation of wearable and portable AI-enhanced electrocardiography.
, Eur Heart J Digit Health, Vol: 7Wearable and portable electrocardiogram (ECG) devices are shifting cardiovascular monitoring beyond clinician-directed testing, driven by consumer-led self-monitoring, remote care, and preventive cardiology. Artificial intelligence (AI) may enhance the value of these devices by supporting automated interpretation, but clinical translation remains uneven. This narrative review synthesises current evidence on AI-enhanced ECG (AI-ECG) analysis in wearable and portable systems, with emphasis on the gap between technical performance and real-world implementation. Although many advances have been developed using conventional 12-lead ECG datasets, deployment in wearable and portable devices introduces additional challenges related to device-specific signal acquisition, preprocessing, domain shift, and user-led recording. Evidence is most mature for atrial fibrillation detection, while applications across conduction disease, other arrhythmias, structural phenotypes, and prognostic assessment remain earlier in development and are supported by fewer prospective, device-specific evaluations. Across the field, retrospective and dataset-based studies predominate, with limited evidence that improved detection translates into better patient outcomes or health-system efficiency. Future research should evaluate performance using the intended device, population, and clinical pathway, and determine whether AI-ECG changes management without increasing unnecessary investigation or workload. Establishing clinical value, rather than improving classification accuracy alone, will determine the role of wearable and portable AI-ECG in routine cardiovascular care.
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Journal articleShiwani H, Augusto J, Topriceanu C-C, et al., 2026,
Prevalence and determinants of asymmetric septal hypertrophy (ASH) in diseases of left ventricular hypertrophy (LVH).
, Eur Heart J Cardiovasc Imaging, Vol: 27, Pages: 1860-1869AIMS: To determine the prevalence of asymmetric septal hypertrophy (ASH) across health and in diseases associated with left ventricular hypertrophy (LVH), including hypertrophic cardiomyopathy (HCM). METHODS AND RESULTS: We analysed two complementary datasets. First, a large UK Biobank healthy reference cohort (n = 4020) was used to model demographic determinants of septal-to-lateral wall thickness ratio (SLR) and to provide the reference group for age-, sex-, and body surface area-adjusted comparisons. Second, a multi-cohort clinical CMR dataset included 1655 subjects comprising local healthy volunteers, athletes, patients with hypertension, aortic stenosis, Fabry disease, amyloid light chain (AL) amyloidosis, amyloid transthyretin (ATTR) amyloidosis, and HCM. LVH was defined by maximum wall thickness (MWT) ≥15 mm and asymmetry defined as SLR≥1.3. Left ventricular morphology was classified as normal, asymmetric remodelling (SLR≥1.3; MWT<15 mm), symmetric hypertrophy (SLR<1.3; MWT≥15 mm) or ASH (SLR≥1.3; MWT≥15 mm). ASH was highly prevalent in HCM (61%) but was also observed in ATTR amyloidosis (37%), AS (26%), and AL amyloidosis (23%). In the healthy reference cohort, a higher septal-to-lateral ratio was independently associated with older age, female sex, and larger body surface area (P < 0.001). After adjustment for these demographic factors, only HCM retained a clinically meaningful excess in septal asymmetry (ΔSLR = +0.27; P < 0.001). In contrast, the apparent asymmetry in non-HCM cohorts was partly explained by demographic variation. After adjustment, only HCM showed a clinically meaningful excess in SLR, whereas other disease cohorts showed either no material difference or small negative differences relative to healthy controls. CONCLUSION: ASH is a common but non-specific finding in diseases associated with LVH. Septal asymmetry increases with age and body-size and is more pronounced in women. After adjusting for age, sex
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Journal articleRenwick C, Ogden M, Ramos M, et al., 2026,
Maximum heart rate prediction in children: are maximal heart rate prediction equations suitable for use in paediatric clinical practice?
, Cardiol Young, Pages: 1-6AIMS: Assessment of maximal heart rate is used in clinical practice to determine the degree of beta-blockade during exercise and periods of adrenergic stress. When direct measurement is not possible, indirect methods utilising heart rate prediction equations are commonly used, but their validity in children has been challenged. METHODS: Retrospective data on 109 healthy children (male 63, 58%; mean age 11.00 ± 3.09) undergoing routine exercise testing were analysed. Measured maximal heart rate was compared with estimates obtained from twenty-two prediction equations. RESULTS: All prediction equations overestimated maximal heart rate in males. In females, two equations underpredicted (Fairbarn and Heinzmann-Filho et al.), whilst the remaining equations overpredicted. The equations that predicted most accurately differed between males (Fairbarn) and females (Whyte (males). The prediction equation used commonly in clinical practice, Fox (220-age), overestimated significantly in males and females (p = < 0.001). A moderate positive correlation with age and maximal heart rate was seen in males only (r = 0.3195, p = 0.0107). CONCLUSIONS: This study shows that adult age regression equations do not accurately predict childhood maximal heart rate as determined by exercise testing. An inability to accurately predict maximal heart rate could have important implications for both childhood exercise prescription and the safe monitoring of pharmacological therapy that limits exertional heart rate response in children with inherited arrhythmic syndromes. In the absence of direct measurement of maximal heart rate, alternative paediatric-specific prediction methods should be developed to ensure appropriate estimation of childhood maximal heart rate.
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Journal articleGupta A, Collier D, Steckelmacher J, et al., 2026,
Safety, Acceptability and Efficacy of Noninvasive Transcutaneous-Autonomic Neuromodulation in Uncontrolled Hypertension.
, HypertensionBACKGROUND: Despite antihypertensive medications, ≈40% of patients with hypertension fail to achieve recommended blood pressure (BP) targets. Alternative device-based strategies are often expensive or invasive. We evaluated the safety, acceptability, and potential efficacy of a noninvasive transcutaneous autonomic neuromodulation (tAN) device. METHODS: SCRATCH-HTN (Sham Controlled Randomized Trial Evaluating the Safety, Acceptability and Efficacy of Autonomic Neuromodulation using Transcutaneous Vagal Sensory Stimulation in Uncontrolled Hypertensive Patients) was a double-blind, sham-controlled, phase 2a trial enrolling patients with uncontrolled hypertension (mean daytime systolic BP [SBP] ≥135 mm Hg and diastolic BP ≥85 mm Hg) on 1 or more medications. Participants self-administered active tAN or sham treatment for 30 minutes daily for 14 days, then 10 weekly sessions. Primary end points were safety and acceptability. The primary efficacy end point was change in daytime ambulatory SBP from baseline to 3 months. Secondary end points included BP, heart rate, and quality of life at 1 and 3 months. RESULTS: Sixty-three patients (mean age 47.2 years, 71.4% male, mean daytime BP 150/95 mm Hg) were randomized 2:1 to tAN or sham. tAN did not differ significantly from sham in daytime ambulatory SBP at 3 months (between-group difference, 2.35 mm Hg [95% CI, -4.37 to 9.07]; P=0.49) or 1 month (-1.01 mm Hg [-6.87 to 4.85]; P=0.73). Pre-specified adjusted analysis identified a significant interaction between treatment and baseline SBP (P interaction 0.003): participants with baseline SBP >160 mm Hg showed a greater response to tAN. No significant differences were observed for other secondary end points. tAN was safe and acceptable. CONCLUSIONS: tAN is safe and well-tolerated in patients with hypertension. No significant BP-lowering effect was demonstrated, although a potential benefit in subgroups or a modest effect in a
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Journal articleShun-Shin M, Whinnett Z, 2026,
Cardiac resynchronisation therapy: 30 years of progress.
, Lancet, Vol: 408, Pages: 1150-1151 -
Journal articleArgirò A, Meisner J, Adler E, et al., 2026,
Clinical Characteristics and Outcomes of Hypertrophic Cardiomyopathy Associated With Thin Filament Variants: Insights From the SHaRe Registry.
, Circ Genom Precis MedBACKGROUND: Conflicting evidence exists about whether sarcomeric hypertrophic cardiomyopathy (HCM) caused by genes encoding thin filament proteins (TNNT2, TNNI3, ACTC, TPM1, TNNC1; thin filament HCM) has a distinct clinical presentation and natural history from disease caused by the more commonly involved thick filament genes (MYH7, MYBPC3, MYL2, MYL3; thick filament HCM). METHODS: Retrospective analysis of the Sarcomeric Human Cardiomyopathy Registry. RESULTS: Four hundred eighty-eight patients with thin filament HCM were compared with 3494 patients with thick filament HCM. After controlling for age at diagnosis, sex, and proband status, thin filament HCM was associated with a higher risk of composite ventricular arrhythmias (hazard ratio, 1.48 [95% CI, 1.09-2.01]), cardiac arrest (hazard ratio, 2.02 [95% CI, 1.33-3.06]), and heart transplant or left ventricular assist device implantation (hazard ratio, 2.18 [95% CI, 1.3-3.65]). Younger age at diagnosis was associated with an increased risk for the ventricular arrhythmia composite outcome in thin and thick filament HCM (hazard ratio, 0.93 [95% CI, 0.91-0.94]; hazard ratio, 0.93 [95% CI, 0.93-0.94]; age reported as 5-year increment). Within specific thin filament genes, an increased risk of arrhythmic events or heart transplant/left ventricular assist device implantation was evident for variants in TNNT2 amino acids 92 to 94 (odds ratio versus other TNNT2 variants; odds ratio, 3.02 [95% CI, 1.17-7.49]) and TNNI3 amino acids 191 to 210 (odds ratio versus other TNNI3 variants; odds ratio, 3.5 [95% CI, 1.58-8.02]). CONCLUSIONS: Thin filament HCM seems to carry a higher risk for ventricular arrhythmias and advanced heart failure compared with thick filament HCM. Integrating gene-level and intragene-level information may improve risk stratification in patients with HCM.
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Journal articleRenberg A, Coppersmith S, Merritt O, et al., 2026,
Mapping and rewiring the MYBPC3 promoter for rescue of haploinsufficiency driven hypertrophic cardiomyopathy.
, bioRxivAutosomal dominant loss-of-function variants in the gene MYBPC3 are, collectively, the most common genetic cause of hypertrophic cardiomyopathy (HCM) and are a prototype of haploinsufficient human disease. Typical for haploinsufficiency-associated genes, hundreds of unique loss-of-function pathogenic variants have been reported for MYBPC3 - therapeutic gene editing to correct each of these variants poses major regulatory and logistical hurdles. Upregulating wild-type allele expression could offer a generalizable therapeutic strategy, but the capacity to modulate native MYBPC3 transcription is unknown. Here, we present a variant-agnostic approach to rescue haploinsufficiency by mapping and rationally redesigning the MYBPC3 promoter. Using massively parallel reporter assays (MPRAs) in human induced pluripotent stem cell-derived cardiomyocytes, we performed saturation mutagenesis of the MYBPC3 promoter at single base-pair resolution. This defined a new class of clinically relevant noncoding loss-of-function variants while revealing essential cis-regulatory grammar anchored by key transcription factor binding sites (TFBSs). Furthermore, by systematically screening thousands of variant combinations, modular promoter elements, and heterologous TFBS insertions, we identified synergistic sequence edits that drive robust increases in MYBPC3 expression. Together, our findings improve the clinical interpretation of noncoding variants and establish a scalable blueprint for promoter editing to treat MYBPC3-associated HCM and other haploinsufficient diseases.
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Journal articleIoannou A, Patel R, Mansell J, et al., 2026,
Exploration of Arrhythmia Burden in Cardiac Amyloidosis Using Implantable Loop Recorders: The EXCALIBUR Study.
, J Am Coll Cardiol, Vol: 88, Pages: 1387-1398BACKGROUND: Cardiac amyloidosis (CA) is a progressive infiltrative cardiomyopathy associated with conduction disease and arrhythmias, although their true burden and relationship with disease phenotype remain incompletely defined. OBJECTIVES: The purpose of this study was to prospectively characterize arrhythmic burden using implantable loop recorders and explore associations with amyloid subtype and disease characteristics. METHODS: In this prospective single-center observational study, 110 treatment-naïve patients with a new diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM) or light-chain cardiac amyloidosis (AL-CA) underwent comprehensive phenotyping, including cardiac magnetic resonance, followed by implantable loop recorder implantation. RESULTS: Among 110 patients (ATTRwt-CM: 43, ATTRv-CM: 20, AL-CA: 47) bradyarrhythmias with a Class I indication for pacemaker implantation occurred in 17.3% and were more frequent in ATTR-CM than AL-CA (15 [23.8%] vs 4 [8.5%]; P = 0.036). Baseline conduction abnormalities (QRS duration: sHR: 1.03; [95% CI: 1.01-1.04]; P < 0.001) and higher myocardial amyloid burden were associated with subsequent bradyarrhythmic events (ECV: sHR: 1.06 [95% CI: 1.02-1.10]; P = 0.002). New atrial fibrillation occurred in 28.2% of patients without prior atrial fibrillation and was more frequent in ATTR-CM than AL-CA (15 [50.0%] vs 5 [12.2%]; P < 0.001) with higher amyloid burden associated with increased risk (ECV: sHR: 1.04; 95% CI: 1.00-1.08; P = 0.038). During follow-up 21 (19.1%) patients died (ATTR-CM: 10 [15.9%]; AL-CA: 11[23.4%]). In patients with ATTR-CM, the terminal cardiac rhythm was uniformly pulseless electrical activity; in patients with AL-CA, PEA was the terminal rhythm in 9 (81.8%) patients and 2 (18.2%) had sustained ventricular arrhythmias. CONCLUSIONS: In CA, clinically significant arrhythmias are common and frequently asymptomatic. Arrhythmic burden and patterns differ between amyloid subtypes and are close
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Journal articleKhattak GR, El-Medany A, Aggour H, et al., 2026,
Predicting self-terminating ventricular tachycardia using cycle-length variability: external validation of a machine learning model
, Heart Rhythm O2, ISSN: 2666-5018BackgroundMachine learning (ML) models trained on intracardiac electrogram (EGM) data from implantable cardioverter-defibrillators (ICDs) show promise for predicting ventricular tachycardia (VT) behaviour. However, generalisability across heterogeneous real-world datasets remains unclear.ObjectiveWe sought to externally validate a previously developed ML model, designed to predict VT self-termination based on cycle length (CL) variability, using a large international multicentre dataset.MethodsThe original ML model was developed using 69 VT episodes from 27 patients in the Boston Scientific Latitude Clinician Database (BSLCD), incorporating CL variability and autoregressive features extracted from the first ten ventricular CLs. For external validation, we curated a diverse dataset using 18,379 EGM records from over 100 Medtronic-equipped centres across six continents, comprising 3,476 VT episodes from 567 patients. EGM data underwent rigorous signal cleaning and re-annotation using a uniform CL framework, enabling large-scale external evaluation of the previously published model.ResultsExternal validation of the previously published model on the Medtronic dataset demonstrated substantially reduced performance, with a mean area under the receiver operating characteristic curve (AUC) of 0.66 (95% confidence interval (CI) 0.65–0.66). In contrast, internal cross-validation on the BSLCD cohort reproduced previously reported performance (AUC 0.84, 95% CI 0.81–0.86).ConclusionCycle-length variability ML models may capture features associated with VT behaviour, but performance declined substantially when transported to a heterogeneous external ICD dataset. Our results highlight the importance of external validation across different device manufacturers and clinical settings when evaluating generalisability of ML models applied to intracardiac EGMs.
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Journal articleAdami E, Kim Y, Zheng SL, et al., 2026,
The molecular landscape of hypertrophic cardiomyopathy across disease stages and genotypes.
, Sci Transl Med, Vol: 18Hypertrophic cardiomyopathy (HCM) is marked by asymmetric cardiac wall thickening, hypercontractility, diastolic dysfunction, and fibrosis. Pathogenic sarcomere gene variants cause HCM, but comparable abnormalities occur in patients with unexplained disease, albeit with fewer adverse events. To investigate stage- and genotype-specific disease mechanisms, we performed single-nucleus RNA sequencing of cardiac tissues from 47 patients with HCM, spanning obstructive HCM with preserved systolic function and end-stage HCM, and compared them with nonfailing donor and dilated cardiomyopathy hearts. We identified transcriptional programs associated with cardiomyocyte hypertrophy, fibrosis, and vascular remodeling. Pathogenic variant-positive early-stage HCM samples showed reduced cardiomyocyte abundance and expansion of a proarrhythmogenic cardiomyocyte state. We identified proline-rich 16 (PRR16) as a cardiomyocyte growth-associated gene in HCM and validated its increased expression by RNA in situ hybridization and in a human induced pluripotent stem cell-derived cardiomyocyte HCM model. In HCM samples, fibroblast compositional shifts were associated with profibrotic activation and adverse extracellular matrix remodeling, accompanied by reduced collagen IV (COL4A1/COL4A2) expression and ultrastructural basement membrane abnormalities. HCM samples also exhibited extensive vascular alterations, including shifts in endothelial cell subpopulations, reduced pericyte abundance suggestive of microvascular dysfunction, and increased lymphangiogenic vascular endothelial growth factor C signaling. Unsupervised and supervised machine learning approaches distinguished HCM from dilated cardiomyopathy and accurately predicted genotype status in early-stage HCM from cell type-resolved transcriptional profiles, revealing widespread genotype-driven remodeling. Together, our findings uncover multicellular, genotype-associated remodeling programs in HCM, providing insight into mechanisms unde
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