Risk Stratification and Optimal Use of Implantable Cardioverter-Defibrillator Therapy in Primary Prevention of Sudden Cardiac Death in Genetic Cardiomyopathies, with Assessment of the Role of Genetic Variants in Guiding Therapeutic Decisions

TL;DR

This paper explores how genetic variants can improve the use of implantable cardioverter-defibrillators in preventing sudden cardiac death in genetic cardiomyopathies.

Contribution

The paper introduces a framework for integrating genetic data with imaging biomarkers to refine arrhythmic risk stratification in cardiomyopathies.

Findings

Truncating genetic variants are linked to severe disease and high arrhythmic risk.

Missense variants show variable expressivity, affecting disease severity and onset.

Combining genetic and imaging data improves risk stratification beyond traditional methods.

Abstract

Genetic background is a critical determinant of disease expression, arrhythmic vulnerability, and therapeutic response in inherited cardiomyopathies. Implantable cardioverter-defibrillators (ICD) remain the cornerstone for primary prevention of sudden cardiac death, yet conventional selection based on left ventricular ejection fraction does not adequately reflect the heterogeneity of genetic substrates. Increasing evidence demonstrates that pathogenic variants differ not only in prevalence across cardiomyopathy subtypes but also in prognostic impact. Truncating variants, particularly in genes encoding structural proteins, are often associated with severe remodeling, progressive dysfunction, and high arrhythmic risk, whereas missense variants may confer variable expressivity, ranging from aggressive arrhythmogenic phenotypes to milder or late-onset disease. This variability underscores the importance of distinguishing variant classes in clinical decision-making. Integrating genetic information with advanced imaging markers, such as late gadolinium enhancement, allows refinement of arrhythmic risk stratification beyond static thresholds and supports more tailored ICD allocation. Nevertheless, translation into routine practice is limited by challenges in variant interpretation, phenotypic overlap between cardiomyopathy subtypes, and the lack of prospective validation of genotype-based models. In the precision medicine era, evolving strategies should move toward dynamic, multimodal approaches that combine genotype, phenotype, and imaging biomarkers, enabling more accurate prediction of arrhythmic risk and more cost-effective use of ICD therapy.