(625g) A Pathway-Centric View of the Brain's Homeostasis Transcriptome During Acute Sustained Hypertension

The mechanisms of the development and origin of hypertension have been unclear. The recent evidence for “neurogenic hypertension” by resetting of brainstem blood pressure control mechanisms over long timescales is a modern scientific triumph. These physiological discoveries now provide the new opportunity to seek the underlying adaptive processes and altered mechanism in central neuronal control systems. We here describe a systems biology approach that bridges molecular mechanisms and neurophysiological behavior, with specific application to understanding the molecular basis for the setpoint control of blood pressure by the brain.

Our working hypothesis is that elevated blood pressure induces a temporal sequence of gene expression changes as an adaptive response and that this changed molecular phenotype underlies alterations in central blood pressure setpoint control. In order to identify the molecular response process we use high resolution quantitative PCR to profile large sets of functionally relevant genes across select brain nuclei in the autonomic-emotional neuraxis, in phenotypically homogeneous sets of neurons, and in single identified neurons - from in vivo samples. We sample four key brain regions in the autonomic-emotional neuraxis, specifically (1) the nucleus of the solitary tract - NTS, caudal and rostral ventro-lateral medulla - CVLM and RVLM, and (2) the Central Nucleus of the Amygdala (CeA). Within the NTS we are particularly focused on the noradrenergic A2 neurons. Increases in blood pressure induce broad transcriptional changes within 1h throughout the autonomic-emotional neuraxis, but with distinct expression programs in each region.

Our experimental results and dynamic response pattern analysis reveals a temporal sequence of gene regulatory changes that indicates a causative influence that starts in the NTS, subsequently followed by changes in CeA, and later evolving in the caudal and rostral VLM nuclei. We found a very early (within the first hour of the stimulus) and widespread gene regulatory response involving neuron-specific functions, the pattern of which was dynamic even in the short term (over the course of four hours). There is evidence of coordinate regulation in all the four brain regions studied, in elements of angiotensin II type 1 receptor (AT1R) mediated pathway, downstream transcriptional regulators including members of AP-1, CREB and ATF families, and ionotropic glutamate receptors. Since these functional systems are known to play prominent roles in normal homeostatic maintenance and hypertension pathobiology, we explore their adaptive regulation here in some detail.

We analyzed the data using a novel bioinformatics approach that identifies context-specific signaling network that is consistent with our gene expression data. The networks with highly significant consistency showed remarkable similarity within the treatment groups but are distinct for hypertensive vs normotensive samples. Our analysis indicated that the AT1R pathway interactions are likely to be different across the brain regions, and conditionally dependent on the hypertensive state. Results of A2 cell analysis show (1) significant systems-level gene expression response to increases in blood pressure within an hour, differential to controls, (2) that the response differs from cardiovascular NTS and other identified neurons, and (3) A2 cells are molecularly heterogeneous. The time series gene expression data also identify key receptors and transmitters affected by the blood pressure. The present broader measures provide not only simultaneous measures of many molecules-genes, but also provide context to understand the adaptive molecular process and networks. In addition, time series allows consideration of dynamics within and across distinct neuronal “nodes” forming a functional circuit. The A2 cell data radically expands our understanding of these neuron types and identification of molecular participants in the adaptive response predicts useful targets for genetic manipulation technologies.

These results reveal a dynamic transcriptional regulation that is likely to coordinately impact the homeostatic control circuits along the autonomic-emotional neuraxis.

Research Support: NIH - R01 GM083108, R33 HL088283 and R33 HL087361.