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Family Screening in Relatives at Risk for Plakophilin-2-Associated Arrhythmogenic Right Ventricular Cardiomyopathy
Steven A Muller1,2,3, Babken Asatryan1, Alessio Gasperetti1
1Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (S.A.M., B.A., A.G., R.T.C., C.T., B.M., S.L.Z., H.C., C.A.J.).
A new genotype-specific screening algorithm for arrhythmogenic right ventricular cardiomyopathy (ARVC) using plakophilin-2 (PKP2) variants offers personalized care. This approach improves risk stratification and clinical resource allocation for families with ARVC.
Area of Science:
- Cardiology
- Genetics
- Clinical Medicine
Background:
- Arrhythmogenic right ventricular cardiomyopathy (ARVC) risk and ventricular arrhythmias (VAs) are genotype-dependent.
- Current ARVC screening lacks personalization, necessitating genotype-informed protocols.
- Plakophilin-2 (PKP2) gene variants are a common cause of ARVC, making PKP2-specific screening crucial.
Purpose of the Study:
- To develop a safe and evidence-based screening algorithm specific to PKP2 variants in ARVC.
- To enable personalized recommendations for family screening based on genetic and clinical data.
- To improve the efficiency of clinical resource allocation in ARVC management.
Main Methods:
- Included 295 relatives with pathogenic/likely pathogenic PKP2 variants from 145 families.
- Phenotype assessment using ECG, Holter monitoring, and cardiac imaging based on 2010 Task Force Criteria.
- Cox regression and multistate modeling to determine ARVC development predictors and VA occurrence.
Main Results:
- 12% of relatives experienced VAs, exclusively in those with a definite ARVC diagnosis.
- Relatives with borderline ARVC progressed 5x faster to definite ARVC compared to genotype-positive/phenotype-negative relatives.
- Younger relatives (20-40 years) had a 2.23-fold increased risk of developing ARVC.
Conclusions:
- Developed a 3-tiered, evidence-based longitudinal screening algorithm for PKP2-related ARVC.
- Algorithm integrates age, symptoms, and baseline phenotype for tailored screening.
- Personalized screening can enhance patient care and optimize clinical resource use.
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