Systems Analysis of B-blockers and B-adrenergic Responsiveness in Cardiac Myocytes

Heart failure, the inability of the heart to provide adequate blood flow to meet the body’s demand, is one of the leading causes of hospitalization and mortality in the United States. β-adrenergic receptor blockers (β-blockers) are commonly used to treat chronic heart failure but the biological mechanisms governing the efficacy of β-blockers is poorly understood. This impedes the design of improved and personalized heart failure therapies.
The β1-adrenergic receptor pathway has a dominant role in the regulation of heart contractility. Elevated catecholamine release, a hallmark of heart failure, has been shown to desensitize the β-adrenergic pathway causing an inability to increase contractility and cardiac output in response to acute stress. Two conflicting theories commonly postulated are that β-blockers are effective by either inhibiting the harmful consequences of sustained stimulation or maintaining the beneficial aspects of β1-adrenergic receptor pathway activation.
The focus of this dissertation is to quantitatively examine how cardiac β-adrenergic signaling is modulated by β-blockers, receptor polymorphisms and altered expression of pathway components. This was done via the following 3 aims: 1) test the hypothesis that the β-blocker propranolol both inhibits and maintains β1-adrenergic signaling in normal cardiac myocytes, 2) test the hypothesis that β1-adrenergic signaling is differentially modulated by clinically relevant β-blockers and receptor polymorphisms 3) test the hypothesis that integration of human heart failure patient transcriptional profiles with mechanistic computational models is sufficient to predict reduced β-adrenergic responsiveness.
The complexity of the β-adrenergic receptor pathway coupled with the influence of receptor polymorphisms makes it difficult to intuit the effect of β-blockers on observed cardiac physiology. We began by using a systems pharmacology approach to test the hypothesis that both proposed mechanisms for β-blocker efficacy can occur concurrently. To do this, a published computational model of the β1-adrenergic receptor pathway developed in our group was extended to include detailed receptor interactions. Model predictions, validated with Ca2+ and FRET imaging of isolated rat cardiac myocytes, surprisingly suggest that β-blockers can both inhibit and maintain signaling depending on the magnitude of receptor stimulation. In addition, these responses are modulated by receptor polymorphisms. To comprehensively investigate how alterations to the β-adrenergic signaling pathway contribute to the loss of adrenergic responsiveness in heart failure, we mapped differential gene expression in heart failure onto protein species in the computational model. Etiology-specific computational models were able to capture altered features of Ca2+ signaling in failing human myocytes. Together, this body of work provides insight into how β-adrenergic signaling is altered in heart failure and the impact of β-blockers. We discovered significant patient population-specific differences in response to β-blockers and alterations to the β1-adrenergic receptor pathway. Evaluating the mechanisms for these differences, with the help of computational models, is an important step towards designing personalized heart failure therapies.