Dynamic microRNA networks in the brainstem underlie the development of hypertension

Danielle DeCicco, Thomas Jefferson University

Abstract

Essential hypertension is a major disease impacting millions across the globe. Hypertension is often resistant to current therapies, which can result in deadly consequences such as stroke and heart attack. One third of the United States population is hypertensive, and despite 75% using anti-hypertensive medication, only 53% have blood pressure controlled. Hypertensive patients typically exhibit autonomic dysfunction, and it is now compelling that neural contribution to hypertension is a major cause of its development and maintenance. Of the molecular pathways that have been examined in the context of neural contribution to essential hypertension, two have shown to have significant impact in affecting the hypertensive state: Angiotensin II (Ang II) signaling and Leukotriene B4 (LTB4) signaling. However, despite protein signaling pathways being necessary for the development of disease, non-coding RNA, mainly through microRNA, regulation of such pathways has proven to be a key regulatory element in disease. Within this thesis, the first and the only work, on microRNA changes in the brainstem autonomic control circuits that lead to development of hypertension will be presented. Using a systems biology approach integrating high-throughput data, network analysis, and in vivo and in vitro experimental testing, we have identified microRNAs in the brainstem of the Spontaneously Hypertensive Rat (SHR) relative to Wistar-Kyoto (WKY) controls with significantly different expression levels in two key neuroanatomical regions, the nucleus of the solitary tract (NTS) and the rostral ventrolateral medulla (RVLM). Alterations in microRNA expression levels are time and location-dependent, differing at a key period of hypertension onset in NTS, but differing at the prehypertensive stage in RVLM. Using correlational relationships and network identification analysis, between microRNAs and mRNAs measured, we observed a double-negative regulatory motif consisting of a microRNA down-regulating a negative regulator of a pro-hypertensive signaling pathway like Angiotensin II signaling or leukotriene-based inflammation. We demonstrated for the first time that the broad concordance of microRNA dynamics and target gene expression compose a regulatory network in the brainstem underlying hypertension. We then localized the regulatory network to different cell types in these regions in the brain. From the cohort of microRNAs we identified, microRNA-135a and microRNA-376a were previously shown to be enriched in astrocytes, a reactive immune cell in the brain, and neurons, respectively. We examined whether we could localize the tissue-scale network to each cell-type using a novel, optimized technique for measuring microRNA expression and target gene expression in the same 10-cell pool obtained from fresh-frozen slices of NTS from SHR and WKY. Some portions of the network were robust, and did localize to the cell-type level; whereas other portions were only seen at the tissue-level. Having identified two microRNAs, with cell-type specific properties, in SHR at a particular key time point in the development of hypertension, we performed in vivo manipulation studies directing microRNA antagonists directly into the IVth intracerebral ventrical (ICV) in the central nervous system (CNS) to normalize the expression of the disease-associated microRNAs in SHR through stereotaxic surgery. For the first time, our results demonstrate microRNA perturbations in the brain can elicit physiological effects, reducing blood pressure. In this context, disease-associated microRNAs represent a new class of targets for development of microRNA-based therapies, which may yield patient benefits unobtainable by conventional therapeutic approaches.

Subject Area

Molecular biology

Recommended Citation

DeCicco, Danielle, "Dynamic microRNA networks in the brainstem underlie the development of hypertension" (2016). ETD Collection for Thomas Jefferson University. AAI10156226.
https://jdc.jefferson.edu/dissertations/AAI10156226

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