Date of Award

January 2012

Document Type

Open Access Thesis

Degree Name

Medical Doctor (MD)



First Advisor

Robin M. Shaw

Second Advisor

Frank Giordano

Subject Area(s)



Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a disorder characterized by fibrofatty replacement of the right ventricular myocardium and associated arrhythmias that originate from the right ventricle. BIN1 is a membrane-associated protein that is involved in cardiac T-tubule homeostasis and is down-regulated in cardiomyopathy. BIN1 has also been shown to be essential to the

differentiation of myoblasts and the induction of skeletal muscle T-tubule invagination.

We hypothesized that BIN1 is released into the circulation andthat circulatory BIN1 would provide useful cardiac monitoring data on patients suffering from heart failure in ARVC. The objective was to determine whether plasma BIN1 can measure disease severity in patients with ARVC.

The study presented is a retrospective cohort of 24 patients with ARVC. Plasma BIN1 levels were quantified and analyzed against clinical data to determine its ability to predict cardiac functional status and ventricular arrhythmias. Mean plasma BIN1 levels were decreased in ARVC patients compared to controls (37 ± 1 vs. 60 ± 10, p < 0.05). In a cross-sectional analysis, ARVC patients with heart failure had lower BIN1 (15 ± 7 vs. 60 ± 17 in patients without heart failure, p < 0.05). BIN1 levels correlated inversely with ventricular arrhythmia burden (R = -0.46, p < 0.05), and low BIN1 correctly classified patients with advanced heart failure or ventricular arrhythmia (ROC Area under the curve, AUC, 0.88 ± 0.07).

Low BIN1 also predicted future ventricular arrhythmias (ROC AUC 0.89 ± 0.09). In a stratified analysis, BIN1 predicted future arrhythmias in patients without severe heart failure to an accuracy of 82%. In ARVC patients with serial blood draws who had evidence of disease progression during follow up, plasma BIN1 decreased by 63% (p < 0.05).

In conclusion, plasma BIN1 correlates with disease severity in patients with ARVC and predicts future ventricular arrhythmias.


This is an Open Access Thesis.

Open Access

This Article is Open Access