Prognostic relevance of gene-environment interactions in patients with dilated cardiomyopathy: applying the MOGE(S) classification

BACKGROUND: The multifactorial pathogenesis leading to dilated cardiomyopathy (DCM) makes stratification difficult. The recent MOGE(S) (morphofunctional, organ involvement, genetic or familial, etiology, stage) classification addresses this issue.

OBJECTIVES: The purpose of this study was to investigate the applicability and prognostic relevance of the MOGE(S) classification in patients with DCM.

METHODS: This study used patients from the Maastricht Cardiomyopathy Registry in the Netherlands and excluded patients with ischemic, valvular, hypertensive, and congenital heart disease. All other patients underwent a complete diagnostic work-up, including genetic evaluation and endomyocardial biopsy.

RESULTS: A total of 213 consecutive patients with DCM were included: organ involvement was demonstrated in 35 (16%) and genetic or familial DCM in 70 (33%) patients, including 16 (8%) patients with a pathogenic mutation. At least 1 cause was found in 155 (73%) patients, of whom 48 (23%) had more than 1 possible cause. Left ventricular reverse remodeling was more common in patients with nongenetic or nonfamilial DCM than in patients with genetic or familial DCM (40% vs. 25%; p = 0.04). After a median follow-up of 47 months, organ involvement and higher New York Heart Association functional class were associated with adverse outcome (p < 0.001 and p = 0.02, respectively). Genetic or familial DCM per se was of no prognostic significance, but when it was accompanied by additional etiologic-environmental factors such as significant viral load, immune-mediated factors, rhythm disturbances, or toxic triggers, a worse outcome was revealed (p = 0.03). A higher presence of MOGE(S) attributes (≥2 vs. ≤1 attributes) showed an adverse outcome (p = 0.007).

CONCLUSIONS: The MOGE(S) classification in DCM is applicable, and each attribute or the gene-environment interaction is associated with outcome. Importantly, the presence of multiple attributes was a strong predictor of adverse outcome. Finally, adaptation of the MOGE(S) involving multiple possible etiologies is recommended.