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Cardiogenetics
Volume 15
Issue 3
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Cardiogenetics, Volume 15, Issue 3 (September 2025) – 4 articles

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24 pages, 649 KiB  
Review
Desmosomal Versus Non-Desmosomal Arrhythmogenic Cardiomyopathies: A State-of-the-Art Review
by Kristian Galanti, Lorena Iezzi, Maria Luana Rizzuto, Daniele Falco, Giada Negri, Hoang Nhat Pham, Davide Mansour, Roberta Giansante, Liborio Stuppia, Lorenzo Mazzocchetti, Sabina Gallina, Cesare Mantini, Mohammed Y. Khanji, C. Anwar A. Chahal and Fabrizio Ricci
Cardiogenetics 2025, 15(3), 22; https://doi.org/10.3390/cardiogenetics15030022 (registering DOI) - 1 Aug 2025
Abstract
Arrhythmogenic cardiomyopathies (ACMs) are a phenotypically and etiologically heterogeneous group of myocardial disorders characterized by fibrotic or fibro-fatty replacement of ventricular myocardium, electrical instability, and an elevated risk of sudden cardiac death. Initially identified as a right ventricular disease, ACMs are now recognized [...] Read more.
Arrhythmogenic cardiomyopathies (ACMs) are a phenotypically and etiologically heterogeneous group of myocardial disorders characterized by fibrotic or fibro-fatty replacement of ventricular myocardium, electrical instability, and an elevated risk of sudden cardiac death. Initially identified as a right ventricular disease, ACMs are now recognized to include biventricular and left-dominant forms. Genetic causes account for a substantial proportion of cases and include desmosomal variants, non-desmosomal variants, and familial gene-elusive forms with no identifiable pathogenic mutation. Nongenetic etiologies, including post-inflammatory, autoimmune, and infiltrative mechanisms, may mimic the phenotype. In many patients, the disease remains idiopathic despite comprehensive evaluation. Cardiac magnetic resonance imaging has emerged as a key tool for identifying non-ischemic scar patterns and for distinguishing arrhythmogenic phenotypes from other cardiomyopathies. Emerging classifications propose the unifying concept of scarring cardiomyopathies based on shared structural substrates, although global consensus is evolving. Risk stratification remains challenging, particularly in patients without overt systolic dysfunction or identifiable genetic markers. Advances in tissue phenotyping, multi-omics, and artificial intelligence hold promise for improved prognostic assessment and individualized therapy. Full article
(This article belongs to the Section Cardiovascular Genetics in Clinical Practice)
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11 pages, 857 KiB  
Article
How to Enhance Diagnosis in Fabry Disease: The Power of Information
by Maria Chiara Meucci, Rosa Lillo, Margherita Calcagnino, Giampaolo Tocci, Eustachio Agricola, Federico Biondi, Claudio Di Brango, Vincenzo Guido, Valentina Parisi, Francesca Giordana, Veronica Melita, Mariaelena Lombardi, Angela Beatrice Scardovi, Li Van Stella Truong, Francesca Musella, Francesco di Spigno, Benedetta Matrone, Ivana Pariggiano, Paolo Calabrò, Roberto Spoladore, Stefania Luceri, Stefano Carugo, Francesca Graziani and Francesco Burzottaadd Show full author list remove Hide full author list
Cardiogenetics 2025, 15(3), 21; https://doi.org/10.3390/cardiogenetics15030021 - 31 Jul 2025
Abstract
Background: Cardiac involvement is common in Fabry disease (FD) and typically manifests with left ventricular hypertrophy (LVH). Patients with FD are frequently misdiagnosed, and this is mainly related to the lack of disease awareness among clinicians. The aim of this study was to [...] Read more.
Background: Cardiac involvement is common in Fabry disease (FD) and typically manifests with left ventricular hypertrophy (LVH). Patients with FD are frequently misdiagnosed, and this is mainly related to the lack of disease awareness among clinicians. The aim of this study was to determine whether providing a targeted educational intervention on FD may enhance FD diagnosis. Methods. This research was designed as a single-arm before-and-after intervention study and evaluated the impact of providing a specific training on FD to cardiologists from different Italian centers, without experience in rare diseases. In the 12-month period after the educational intervention, the rate of FD screening and diagnosis was assessed and compared with those conducted in the two years preceding the study initiation. Results: Fifteen cardiologists participated to this study, receiving a theoretical and practical training on FD. In the two previous two years, they conducted 12 FD screening (6/year), and they did not detect any cases of FD. After the training, they performed 45 FD screenings, with an eight-fold rise in the annual screening rate. The screened population (age: 61 ± 11 years, men: 82%) was mainly composed of patients with unexplained LVH (n = 43). There were four new FD diagnoses and, among of them, three had a late-onset GLA variant. After the cascade genetic screening, 11 affected relatives and 8 heterozygous carriers were also detected. Conclusions: A targeted educational intervention for cardiologists allowed the identification of four new families with FD. Enhancing FD awareness is helpful to reduce the diagnostic and therapeutic delay. Full article
(This article belongs to the Section Education in Cardiogenetics)
15 pages, 1506 KiB  
Review
Dilated Cardiomyopathy and Sensorimotor Polyneuropathy Associated with a Homozygous ELAC2 Variant: A Case Report and Literature Review
by Francesco Ravera, Filippo Angelini, Pier Paolo Bocchino, Gianluca Marcelli, Giulia Gobello, Giuseppe Giannino, Guglielmo Merlino, Benedetta De Guidi, Andrea Destefanis, Giulia Margherita Brach Del Prever, Carla Giustetto, Guglielmo Gallone, Stefano Pidello, Antonella Barreca, Silvia Deaglio, Gaetano Maria De Ferrari, Claudia Raineri and Veronica Dusi
Cardiogenetics 2025, 15(3), 20; https://doi.org/10.3390/cardiogenetics15030020 - 31 Jul 2025
Abstract
Variants in ELAC2, a gene encoding the mitochondrial RNase Z enzyme essential for mitochondrial tRNA processing, have been associated with severe pediatric-onset mitochondrial dysfunction, primarily presenting with developmental delay, hypertrophic cardiomyopathy (HCM), and lactic-acidosis. We hereby report the case of a 25-year-old [...] Read more.
Variants in ELAC2, a gene encoding the mitochondrial RNase Z enzyme essential for mitochondrial tRNA processing, have been associated with severe pediatric-onset mitochondrial dysfunction, primarily presenting with developmental delay, hypertrophic cardiomyopathy (HCM), and lactic-acidosis. We hereby report the case of a 25-year-old young woman presenting with dilated cardiomyopathy (DCM) and peripheral sensorimotor polyneuropathy, harboring a homozygous variant in ELAC2. The same variant has been reported only once so far in a case of severe infantile-onset form of HCM and mitochondrial respiratory chain dysfunction, with in vitro data showing a moderate reduction in the RNase Z activity and supporting the current classification as C4 according to the American College of Medical Genetics (ACMG) criteria (PS3, PM2, PM3, PP4). Our extensive clinical, imaging, histological, and genetic investigations support a causal link between the identified variant and the patient’s phenotype, despite the fact that the latter might be considered atypical according to the current state of knowledge. A detailed review of the existing literature on ELAC2-related disease is also provided, highlighting the molecular mechanisms underlying tRNA maturation, mitochondrial dysfunction, and the variable phenotypic expression. Our case further expands the clinical spectrum of ELAC2-related cardiomyopathies to include a relatively late onset in young adulthood and underscores the importance of comprehensive genetic testing in unexplained cardiomyopathies with multisystem involvement. Full article
(This article belongs to the Section Rare Disease-Genetic Syndromes)
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33 pages, 4016 KiB  
Article
Integrated Deep Learning Framework for Cardiac Risk Stratification and Complication Analysis in Leigh’s Disease
by Md Aminul Islam, Jayasree Varadarajan, Md Abu Sufian, Bhupesh Kumar Mishra and Md Ruhul Amin Rasel
Cardiogenetics 2025, 15(3), 19; https://doi.org/10.3390/cardiogenetics15030019 - 15 Jul 2025
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Abstract
Background: Leigh’s Disease is a rare mitochondrial disorder primarily affecting the central nervous system, with frequent secondary cardiac manifestations such as hypertrophic and dilated cardiomyopathies. Early detection of cardiac complications is crucial for patient management, but manual interpretation of cardiac MRI is labour-intensive [...] Read more.
Background: Leigh’s Disease is a rare mitochondrial disorder primarily affecting the central nervous system, with frequent secondary cardiac manifestations such as hypertrophic and dilated cardiomyopathies. Early detection of cardiac complications is crucial for patient management, but manual interpretation of cardiac MRI is labour-intensive and subject to inter-observer variability. Methodology: We propose an integrated deep learning framework using cardiac MRI to automate the detection of cardiac abnormalities associated with Leigh’s Disease. Four CNN architectures—Inceptionv3, a custom 3-layer CNN, DenseNet169, and EfficientNetB2—were trained on preprocessed MRI data (224 × 224 pixels), including left ventricular segmentation, contrast enhancement, and gamma correction. Morphological features (area, aspect ratio, and extent) were also extracted to aid interpretability. Results: EfficientNetB2 achieved the highest test accuracy (99.2%) and generalization performance, followed by DenseNet169 (98.4%), 3-layer CNN (95.6%), and InceptionV3 (94.2%). Statistical morphological analysis revealed significant differences in cardiac structure between Leigh’s and non-Leigh’s cases, particularly in area (212,097 vs. 2247 pixels) and extent (0.995 vs. 0.183). The framework was validated using ROC (AUC = 1.00), Brier Score (0.000), and cross-validation (mean sensitivity = 1.000, std = 0.000). Feature embedding visualisation using PCA, t-SNE, and UMAP confirmed class separability. Grad-CAM heatmaps localised relevant myocardial regions, supporting model interpretability. Conclusions: Our deep learning-based framework demonstrated high diagnostic accuracy and interpretability in detecting Leigh’s disease-related cardiac complications. Integrating morphological analysis and explainable AI provides a robust and scalable tool for early-stage detection and clinical decision support in rare diseases. Full article
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