Hypertension poses a significant challenge to vasculature homeostasis and stands as the most common cardiovascular disease in the world. Its effects are especially profound on endothelial cells that form the inner lining of the vasculature and are directly exposed to the effects of excess pressure. Here, we characterize the in vivo transcriptomic response of cardiac endothelial cells to hypertension by rapidly isolating these cells from the spontaneous hypertension mouse model BPH/2J and its normotensive BPN/3J control strain and performing and RNA sequencing on both. Comparison of transcriptional differences between these groups reveals statistically significant changes in cellular pathways consistent with cardiac fibrosis found in hypertensive animals. Importantly, many of the fibrosis-linked genes identified also differ significantly between juvenile prehypertensive and adult hypertensive BPH/2J mice, suggesting that these transcriptional differences are hypertension related. We examined the dynamic nature of these transcriptional changes by testing whether blood pressure normalization using either a calcium channel blocker (amlodipine) or a angiotensin II receptor blocker (losartan) is able to reverse these expression patterns associated with hypertension. We find that blood pressure reduction is capable of reversing some gene-expression patterns, while other transcripts are recalcitrant to therapeutic intervention. This illuminates the possibility that unmanaged hypertension may irreversibly alter some endothelial transcriptional patterns despite later intervention. This study quantifies how endothelial cells are remodeled at the molecular level in cardiovascular pathology and advances our understanding of the transcriptional events associated with endothelial response to hypertensive challenge.
CITATION STYLE
Nelson, J. W., Ferdaus, M. Z., McCormick, J. A., Minnier, J., Kaul, S., Ellison, D. H., & Barnes, A. P. (2018). Endothelial transcriptomics reveals activation of fibrosis-related pathways in hypertension. Physiological Genomics, 50(2), 104–116. https://doi.org/10.1152/physiolgenomics.00111.2017
Mendeley helps you to discover research relevant for your work.