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Impact of genotype-phenotype associations on prognosis in dilated cardiomyopathy
Sophie L V M Stroeks1,2,3,4, Ping Wang3,4, Marco Merlo4,5
1Department of Cardiology, Maastricht University, Cardiovascular Research Institute Maastricht (CARIM), Maastricht, The Netherlands.
Insights
Genetic dilated cardiomyopathy (DCM) shows significant patient heterogeneity. Genotype-based risk prediction is more accurate than phenotype-based approaches for DCM patients, guiding personalized treatment and genetic screening.
Area of Science:
- Cardiology
- Genetics
- Genomics
Background:
- Dilated cardiomyopathy (DCM) has a monogenic cause in up to 40% of patients.
- Understanding genotype-phenotype associations is key for DCM risk stratification and personalized treatment.
Purpose of the Study:
- Characterize genotype-specific features in DCM.
- Evaluate if phenotype clustering reflects underlying genotype.
- Compare prognostic value of genotype vs. phenotype approaches in DCM.
Main Methods:
- A multicenter cohort of 534 DCM patients with pathogenic variants.
- Grouped patients by genotype (genotype-first) and clinical phenotype (phenotype-first).
- Compared clinical characteristics and evaluated outcomes (mortality, HF hospitalization, transplantation, arrhythmias).
Main Results:
- Significant genotype-phenotype associations found for 10 genes; FLNC, LMNA, DSP, PLN linked to arrhythmias; BAG3, TNNT2, DMD, TTN to cardiac dysfunction.
- Four phenotypic clusters identified, but showed no clear correlation with genotype.
- Genotype-first approach identified LMNA, FLNC, BAG3 variants with highest risk for adverse outcomes.
- Genotype was the strongest predictor of patient outcomes.
Conclusions:
- Genetic DCM presents significant clinical and genetic heterogeneity.
- Genotype-based risk stratification is more accurate than phenotype-first approaches for DCM.
- Broad genetic screening and gene-specific risk prediction are crucial for managing genetic DCM.
Aims:
Dilated cardiomyopathy (DCM) has a monogenic aetiology in up to 40% of patients. Understanding the spectrum of genotype-phenotype associations in DCM is crucial for risk stratification and personalized treatment. We aimed to (i) characterize genotype-specific features, (ii) evaluate whether phenotype-based clustering reflects underlying genotype, and (iii) compare the prognostic value of genotype- versus phenotype-based approaches.
Methods And Results:
A multicentre cohort of 534 DCM patients with a (likely) pathogenic variant were grouped by genotype (genotype-first approach) and clustered by clinical phenotype (phenotype-first approach). We compared clinical characteristics, identified genotype-phenotype associations, and evaluated outcomes, including all-cause mortality, heart failure hospitalization, heart transplantation, and malignant ventricular arrhythmias. Using the genotype-first approach, significant genotype-phenotype associations were found for 10 genes. FLNC, LMNA, DSP, and PLN variants were linked to arrhythmias. BAG3, TNNT2, DMD, and TTN were associated with increased cardiac volumes and decreased left ventricular ejection fraction (LVEF). Clustering identified four phenotypic clusters: (1) young, moderately reduced LVEF; (2) arrhythmias, moderate reduced LVEF; (3) low LVEF; (4) arrhythmias, low LVEF. There were no clear correlations between phenotypic clusters and genotype. The genotype-first approach showed that LMNA, FLNC, and BAG3 variants had the highest risk for heart failure and arrhythmogenic adverse outcomes. The phenotype-first approach indicated that clusters 3 and 4 were associated with the worst prognosis. Overall, genotype was the strongest predictor of outcome.
Conclusions:
Patients with a genetic form of DCM exhibit clinical and genetic heterogeneity. Genotype-based risk stratification is more accurate compared to a phenotype-first approach, highlighting the importance of broad genetic screening among patients with DCM. Additionally, gene-specific risk prediction should become more prominent in current guidelines on management of genetic DCM patients.
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