Impact of genotype-phenotype associations on prognosis in dilated cardiomyopathy.

aimsDilated 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

resultsA 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.

conclusionsPatients 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.