Vagal control of the heart has seen renewed interest due to the now well-recognized potential of manipulating cardiac vagal activity for novel therapeutic opportunities in treating heart disease. Recent anatomical and physiological evidence shows that vagal cardiac control is multimodal at both pre- and post-ganglionic neuronal levels. Coordination between multiple modes of control (e.g., of heart rate, ventricular contractility, etc) is essential for heart health. Disruption of such coordination is a hallmark of heart failure and arrhythmias, for example. Studies thus far have largely focused on the physiological effects of the vagus on heart rate without delving into the underlying neural networks, where insights are likely to yield targets for fine-grained manipulation of vagal activity to treat heart disease. Our project is aimed at addressing this unmet need by focusing on the central neuronal as well as cardiac ganglionic circuits driving chrono-, dromo- and iono- tropism. We will pursue an integrated multiscale modeling strategy that combines fine-grained anatomical tracing of control circuits and high-throughput transcriptional analysis of single neurons identified based on circuit connectivity, with computational modeling of the multiscale closed loop vagal cardiac control. These involve hemodynamics, brainstem neuronal networks, and cardiac ganglionic circuits involved in the coordinated inotropic and chronotropic control of the heart. We will develop detailed electrophysiological models of neuronal excitability in nucleus ambiguus (NA) and dorsal motor nucleus (DMV), as well as the targeted cardiac ganglia, and incorporate the transcriptional changes identified from coronary artery ligation experiments in these models. We hypothesize that coordination and integration of the control of rate and contractility occurring at the level of the NA/DMV and the level of the cardiac ganglia are the basis for cardioprotective vagal cardiac outflows. We will test this hypothesis in three Aims: (1) Develop a multiscale network model framework integrating the key modules controlling SA node and left ventricle. (2) Determine the molecular mechanisms affecting the coordination involved in cardiac functional control in heart disease by linking gene regulatory networks and neural network behavior. (3) Test model predictions in selective manipulation of function experiments. Our multiscale computational modeling framework will enable us to combine and interpret the anatomical, transcriptional, and physiological results from experiments. Our investigative team has previously collaborated in modeling the baroreflexes and comprises complementary expertise in all aspects of the proposal. Our approach is expected to identify the relative contribution of brainstem circuits and cardiac ganglionic circuits to the coordination of multimodal vagal control. Our expected results, by uncovering the molecular and physiological mechanisms underlying the source and maintenance of coordinated vagal outflows, have significant implications for identifying targets for early diagnosis, prevention, and even novel palliative therapy in treating heart disease.
The profound protective effects of vagus nerve activity on heart health offer novel therapeutic avenues in the treatment of heart diseases. There is a lack of knowledge on how multiple aspects of vagal control of the heart are coordinated for cardioprotection. We will pursue an integrated experimental and computational modeling approach to identify the mechanisms controlling the multi-modal coordination of vagal control of the heart in both normal and disease pathologies.
| Mulugeta, Lealem; Drach, Andrew; Erdemir, Ahmet et al. (2018) Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience. Front Neuroinform 12:18 |
| Anderson, Warren D; DeCicco, Danielle; Schwaber, James S et al. (2017) A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation. PLoS Comput Biol 13:e1005627 |
