Modeling of pathogenic breathing pattern dysregulation in cardiopulmonary disease

Reference:
5R33HL087347

Abstract:
Ventilatory arrhythmia plays a pathogenic role in many common respiratory disorders ranging from sleep apnea, and acute lung injury to ventilatory support in the setting of chronic lung disease. Brainstem neural circuits that control cardiopulmonary functions generate oscillatory patterns that drive respiratory as well as sympathetic motor activities. These patterns exhibit highly structured variability and patients with various chronic diseases exhibit aberrations of these patterns and their variabilities. Analytic tools for quantifying ventilatory arrhythmia and for stratification of severity or prognosis are unavailable, representing a major barrier to defining its pathogenic contribution to disease, or to developing novel non-invasive or therapeutic markers. The long-term objectives of this exploratory project are these targets by determining the neurophysiologic mechanisms for ventilatory arrhythmia, specifically the physiological balance between central (pontomedullary) and afferent (pulmonary and baro) feedback mechanisms in the control of respiratory phase switching and pattern stabilization. The applicants hypothesize that alterations in this balance are evident in the pathology of the pulmonary conditions, but lie dormant due to lack of quantitative understanding of the dynamic properties of the respiratory control system. This hypothesis will be tested by analyzing breathing patterns in: 1) a mouse model of rett syndrome, in which ventilatory arrhythmia originates primarily from central deficits and 2) in humans with lung disease and a rat model of lung injury, in which ventilatory arrhythmia originates primarily from altered afferent feedback. The central aim is to develop analytical methods that incorporate new characteristics of breathing pattern variability, and a computational model that accurately predicts respiratory rhythm variability resulting from internal (e.g. network modulation of feedback gain, neuromodulator interactions etc.) and external factors (peripheral chemoreceptor function, lung mechanics). An interdisciplinary research team that includes four experienced groups at different Universities will collaborate closely to perform this project. The specific aims are: 1) to expand a computational model of the brainstem respiratory network to include not only the ponto-medullary circuits but pulmonary and baro-feedback and their interactions (Rybak); 2) to test novel tools permitting the identification of disturbed breathing patterns (Loparo/Wilson); 3) to elucidate the cellular mechanisms involved in reciprocal ponto-vagal interactions by synaptic inputs to pontine and medullary respiratory neurons elicited by vagal afferent activation, including an influence of brain derived neurotrophic factor on the balance of pontine-vagal control of phase duration (Dutschmann); 4) to determine how the network interactions are altered by activation of vagal or dorsolateral pontine neurons in normal and disease states (Dick/Jacono); and 5) to describe the relative role of heritable vagal mechanisms in generating breathing pattern variability in adult twins; and the impact of ventilatory coupling to cardiac activation (cardioventilatory coupling) on breathing variability in twins and patients with lung disease (Strohl/ Jacono). The quantitative tools and insights created from this unique collaboration will permit insight into new diagnostic, prognostic and therapeutic avenues to promote stable breathing and improve patient outcomes in acute and chronic lung injury

PROJECT DETAILS 

beginning: 2008.

end: 2010.

Country of research: United Kingdom and France

Counry of funding source: United States

Funding organization: National Institute of Health, US

Financing: NATIONAL FUNDINGS – 169 896 €

hyperlink

By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close