Patients with inherited cardiomyopathies, specifically those with high-risk genotypes including LMNA, truncating variants in FLNC, RBM20, PLN p.Arg14del, and desmosomal genes
Genotype-informed risk stratification and implantable cardioverter-defibrillator (ICD) decision-making
Ventricular arrhythmias and sudden cardiac death
This review highlights the paradigm shift towards genotype-informed risk stratification for sudden cardiac death prevention in inherited cardiomyopathies, aligning with the 2023 ESC Guidelines.
Inherited cardiomyopathies represent a major cause of ventricular arrhythmias (VA) and sudden cardiac death (SCD), frequently occurring in the absence of advanced systolic dysfunction. Traditional strategies for the primary prevention of SCD have relied predominantly on left ventricular ejection fraction (LVEF), an approach that fails to capture the substantial biological and clinical heterogeneity of non-ischemic cardiomyopathies. Over the past decade, advances in cardiac genetics and cardiac magnetic resonance imaging have identified specific genotypes associated with a disproportionate arrhythmic risk, which often precedes overt ventricular remodeling. The 2023 European Society of Cardiology (ESC) Guidelines on cardiomyopathies formalize this paradigm shift by integrating etiology, myocardial substrate, and electrical phenotype into contemporary risk stratification. In this narrative review, we focus on cardiomyopathy-associated genotypes consistently linked to high arrhythmic risk—LMNA, truncating variants in FLNC, RBM20, PLN p.Arg14del, and desmosomal genes—and examine their molecular mechanisms, phenotypic trajectories, and arrhythmogenic profiles. We discuss how genotype-specific patterns of myocardial fibrosis, conduction disease, and VA inform implantable cardioverter-defibrillator (ICD) decision-making beyond LVEF-based thresholds. By synthesizing genetic, imaging, and clinical evidence in light of ESC 2023 recommendations, this review highlights the evolving role of genotype-informed strategies in the personalized prevention of SCD and underscores remaining gaps in evidence and risk prediction.
Building similarity graph...
Analyzing shared references across papers
Loading...
Tetaj et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69d895486c1944d70ce063d6 — DOI: https://doi.org/10.3390/genes17040370
Nardi Tetaj
Andrea Segreti
Adele Ferro
Genes
Università Campus Bio-Medico
Building similarity graph...
Analyzing shared references across papers
Loading...