Recent evidence indicates that alterations in the neuronal control of blood pressure set point can cause hypertension, termed neurogenic hypertension. It is now plausible, and our hypothesis, that neurogenic hypertension is a major cause, a missing link, in development of hypertension. Thus, understanding the molecular framework for neurogenic hypertension will facilitate development of improved treatment or cure of the disease, and predictive diagnostics. Our previous results focus the present proposal on the A2 catecholaminergic neurons in the nucleus tractus solitarius (NTS). The A2 neurons regulate blood pressure set point independent of any effect on baroreceptor reflex function or gain. A2 cells were also implicated by our transcript profiling studies of the molecular adaptive response of the NTS to hypertension, and by our gene regulatory network computational models of the NTS response. The present proposal will characterize the responses of A2 cells to acute sustained hypertension and use predictive modeling to understand the complex alterations in A2 cellular properties and molecular processes mediating their adaptive responses. We will also study the network behavior of the specific subsets of functionally connected A2 neurons related to blood pressure control. We will build and analyze detailed gene regulatory network models of functionally connected subsets of A2 neurons using an iterative experimental/computational biology approach. These network models will predict the adaptive mechanisms of A2 neurons underlying blood pressure set point control in particular in response to acute sustained hypertension. The predictions will be tested by in vivo genetic manipulation and molecular and physiological assays to reveal molecular interactions critical to maintaining normal blood pressure.

Public Health Relevance

Essential hypertension is a major disease of unknown cause and continually increasing in prevalence. In this proposal, we seek to understand the response of neurons that affect blood pressure set point to acutely elevated blood pressure. By finding specific alterations in these neurons that underlie their adaptive processes, we aim to define mechanisms relevant to diagnostics and therapeutic approaches to hypertension.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL111621-04
Application #
8843930
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Maric-Bilkan, Christine
Project Start
2012-07-01
Project End
2017-04-30
Budget Start
2015-05-01
Budget End
2017-04-30
Support Year
4
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Thomas Jefferson University
Department
Pathology
Type
Schools of Medicine
DUNS #
053284659
City
Philadelphia
State
PA
Country
United States
Zip Code
19107
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
Anderson, Warren D; Makadia, Hirenkumar K; Vadigepalli, Rajanikanth (2016) Molecular variability elicits a tunable switch with discrete neuromodulatory response phenotypes. J Comput Neurosci 40:65-82
Gorky, Jonathan; Schwaber, James (2016) The role of the gut-brain axis in alcohol use disorders. Prog Neuropsychopharmacol Biol Psychiatry 65:234-41
Anderson, Warren D; Vadigepalli, Rajanikanth (2016) Modeling cytokine regulatory network dynamics driving neuroinflammation in central nervous system disorders. Drug Discov Today Dis Models 19:59-67
Anderson, Warren D; Makadia, Hirenkumar K; Greenhalgh, Andrew D et al. (2015) Computational modeling of cytokine signaling in microglia. Mol Biosyst 11:3332-46
Makadia, Hirenkumar K; Anderson, Warren D; Fey, Dirk et al. (2015) Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology. Biophys J 108:211-23
Makadia, Hirenkumar K; Schwaber, James S; Vadigepalli, Rajanikanth (2015) Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features. PLoS Comput Biol 11:e1004563
Park, James; Ogunnaike, Babatunde; Schwaber, James et al. (2015) Identifying functional gene regulatory network phenotypes underlying single cell transcriptional variability. Prog Biophys Mol Biol 117:87-98
DeCicco, Danielle; Zhu, Haisun; Brureau, Anthony et al. (2015) MicroRNA network changes in the brain stem underlie the development of hypertension. Physiol Genomics 47:388-99
Liu, Linbo; Shastry, Suresh; Byan-Parker, Suzanne et al. (2014) An autoregulatory mechanism governing mucociliary transport is sensitive to mucus load. Am J Respir Cell Mol Biol 51:485-93

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