Plasma BIN1 correlates with heart failure and predicts arrhythmia in patients with arrhythmogenic right ventricular cardiomyopathy

摘要

Background: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a disorder involving diseased cardiac muscle. Bridging integrator 1 (BIN1) is a membrane-associated protein important to cardiomyocyte homeostasis and is downregulated in cardiomyopathy. We hypothesized that BIN1 could be released into the circulation and that blood-available BIN1 can provide useful data on the cardiac status of patients whose hearts are failing secondary to ARVC. Objective: To determine whether plasma BIN1 levels can be used to measure disease severity in patients with ARVC. Methods: We performed a retrospective cohort study of 24 patients with ARVC. Plasma BIN1 levels were assessed for their ability to correlate with cardiac functional status and predict ventricular arrhythmias. Results: Mean plasma BIN1 levels were decreased in patients with ARVC with heart failure (15 ± 7 vs 60 ± 17 in patients without heart failure, P <.05; the plasma BIN1 level was 60 ± 10 in non-ARVC normal controls). BIN1 levels correlated inversely with number of previous ventricular arrhythmia (R = -.47; P <.05), and low BIN1 levels correctly classified patients with advanced heart failure or ventricular arrhythmia (receiver operator curve area under the curve of 0.88 ± 0.07). Low BIN1 levels also predicted future ventricular arrhythmias (receiver operator curve area under the curve of 0.89 ± 0.09). In a stratified analysis, BIN1 levels could predict future arrhythmias in patients without severe heart failure (n = 20) with an accuracy of 82%. In the 7 patients with ARVC with serial blood samples, all of whom had evidence of disease progression during follow-up, plasma BIN1 levels decreased significantly (a decrease of 63%; P <.05). Conclusions: Plasma BIN1 level seems to correlate with cardiac functional status and the presence or absence of sustained ventricular arrhythmias in a small cohort of patients with ARVC and can predict future ventricular arrhythmias.