Asthma is a disease of rapidly increasing incidence that affects more than 17 million people in the United States alone. It is of major importance to understand the causes of heterogeneous ventilation and airway obstruction, cardinal features responsible for lung dysfunction in asthma. Yet, despite detailed knowledge of the behavior of individual airways, and of cellular and molecular mechanism of asthma, not much is known about why the asthmatic airway tree constricts heterogeneously. Our working hypothesis is that heterogeneity of ventilation and airway obstruction observed in asthma, is an expression of emergent behavior of a complex network that magnifies the effects of spatial heterogeneity in structure or function of individual airways. In this project we propose to apply analytical tools from complex systems research to analyze the behavior of an integrative network model of the lung under both steady and unsteady conditions. The project involves the combined use of computational modeling and imaging studies using PET-CT focused on two major specific aims, each involving theoretical and experimental aspects: SA 1: Identify the conditions leading to a critical transition in the lungs from a uniform to a heterogeneous state, and calibrate theoretical predictions against existing and new experimental data. SA 2: Elucidate whether the dynamic behavior of the lung and its history can trap the system in abnormal heterogeneous states, and whether certain interventions can be used to reset the system back to a normal uniform state. This project challenges existing paradigms in asthma research and proposes a novel integrated physiological systems approach to the problem. This approach, we feel, is a vital step towards improved understanding of the disease that is needed for development of innovative methods to its diagnosis and therapy. A broader objective of these studies is to provide theoretical and experimental evidence in support of a novel theory on complex diseases recently formulated by J. H. T. Bates (17) whereby repeated exposure to insults could trap the system in abnormal states from which return to normality may not spontaneously occur once the insult source is removed. The research is highly leveraged, as it will lead to development of general complex systems tools for treating systems that, like the lung, are characterized by hierarchical networks with bistable elements.
Asthma is a disease of multiple origins that is becoming increasingly common and affects more than 300 million people worldwide with an estimated total economic burden of $6 billion annually. Predicting the timing and severity of an asthma attack is important to avoid life-threatening situations. This research is aimed at understanding the complex behavior of the lungs during an asthma attack, a key step needed for developing and testing therapeutic interventions to prevent or reverse asthma attacks.
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