Integrating genetic variant data with advanced imaging markers supports more tailored implantable cardioverter-defibrillator allocation for sudden cardiac death prevention in genetic cardiomyopathies.
Does integrating genetic variant information and multimodal imaging improve arrhythmic risk stratification and ICD allocation in patients with genetic cardiomyopathies compared to conventional LVEF-based selection?
Integrating genetic variant data with imaging biomarkers may improve arrhythmic risk stratification and ICD allocation in genetic cardiomyopathies beyond traditional LVEF thresholds.
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.
Ruscio et al. (Mon,) conducted a review in Genetic cardiomyopathies. Genotype-guided risk stratification and implantable cardioverter-defibrillators (ICD) was evaluated. Integrating genetic variant data with advanced imaging markers supports more tailored implantable cardioverter-defibrillator allocation for sudden cardiac death prevention in genetic cardiomyopathies.