The Emergence of Cardioprotection from the Brain-Gut-Heart Network
Abstract
Cardiovascular disease is the largest cause of mortality with more than 2,200 individuals dying daily in the United States alone. Many of these patients suffer from heart failure, the treatments for which have not been able to improve the 50% five year mortality. The use of nonpharmacological interventions like vagal stimulation and ischemic preconditioning have demonstrated great potential, but poor consistency, in treating patients, highlighting the need to better understand the mechanisms by which these treatments work in order to improve consistency and efficacy. The dorsal motor nucleus of the vagus (DMV), which gives rise to vagal efferent projections, has been shown to be essential in mediating these effects. However there is currently limited understanding of the functional heterogeneity of neurons in the DMV, which limits the ability to design better vagal stimulation treatments or to capitalize on recapitulating other vagally mediated cardioprotective effects. In order to develop a better understanding of DMV heterogeneity and elucidate how this heterogeneity might shift to drive cardioprotection, we have taken molecular profiling approach on a single cell level. Such an approach takes advantage of gene regulatory networks and transcriptional patterns to discern biological function. We start with a first-of-its-kind manipulation of gene regulatory networks in the dorsal vagal complex using antisense locked nucleic acids targeted against two specific microRNAs that renormalizes blood pressure in the spontaneously hypertensive rat. These effects are specific to the hypertensive strain with little effect on the normotensive strains due in part to different underlying regulatory network structure. Such networks can be nudged by altering microRNA expression enough to drive physiological effects in the whole body system of hypertensive animals without appreciable perturbation of the already healthy networks of the normotensive animals. From here we develop a framework for understanding the transcriptional heterogeneity in DMV neurons specifically, generating phenotypic classifications. The results suggest that the traditional means of classifying neurons, by neurotransmitters or connectivity, does not have a strong underlying rationale based upon the transcriptional patterns we have observed. The rate limiting enzymes that generate neurotransmitters are often coexpressed with several others in the same neuron. This foundation permits even subtle shifts in neuronal populations to be observed, as is the case under remote ischemic preconditioning. We observe an increase in the number of neurons expressing excitatory H1 histamine receptors, which also have increased expression of tachykinin precursors and atrial naturetic peptide. This suggests a novel role for tuberomammillary projections to the DMV in the mediation of cardioprotection. Over several weeks in the development of heart failure after myocardial infarction, we observe a phenotypic shift in DMV neurons toward a neurosecretory phenotype, driven in part by transcription factors primarily active during embryonic development. This suggests not only that the DMV is responsive to heart failure, but also that the neurons are able to change phenotype to do so. Such phenotypic plasticity leads to consideration of the DMV, and the autonomic nervous system, as capable of adaptive responses rather than mere reflex mediation. Given the large number of DMV projections to the gut, there is further evidence of a brain-gut-heart network that mediates vagal cardioprotection and cardiovascular health as a whole. If we are to find more successful treatments of cardiovascular disease, it is important to consider this and not just treat the heart, but treat the whole network supporting it.^
Subject Area
Neurosciences|Health sciences|Bioinformatics
Recommended Citation
Gorky, Jonathan, "The Emergence of Cardioprotection from the Brain-Gut-Heart Network" (2018). ProQuest ETD Collection - Thomas Jefferson University. AAI10937301.
https://jdc.jefferson.edu/dissertations/AAI10937301
