bioRxivCell Biology
MicroRNA 1253 regulation of WAVE2 and its relevance to health disparities in hypertension
M. A. Arkorful, N. Noren Hooten, Y. Zhang, A. N. Hewitt, L. Barrientos Sanchez, M. K. Evans, D. F. Dluzen
Abstract
The prevalence of hypertension among African Americans (AAs) in the US is among the highest of any demographic and affects over two-thirds of AA women. Previous data from our laboratory suggests substantial differential gene expression (DGE) of mRNAs and microRNAs (miRNAs) exists within peripheral blood mononuclear cells (PBMCs) isolated from AA and white women with or without hypertension. We hypothesized that DGE by race may contribute to racial differences in hypertension. We found that the Wiskott-Aldrich syndrome protein Verprolin homologous-2 (WAVE2) is differentially-expressed in AA women with hypertension, along with several other members of the actin cytoskeleton signaling pathway that plays a role in cell shape and branching of actin filaments. We performed an in silico miRNA target prediction analysis that suggested miRNA miR-1253 regulates WAVE2. Transfection of miR-1253 mimics into human umbilical vein endothelial cells (HUVECs) and human aortic endothelial cells (HAECs) significantly repressed WAVE2 mRNA and protein levels (P<0.05), and a luciferase reporter assay confirmed that miR-1253 regulates the WAVE2 3 UTR (P<0.01). miR-1253 over-expression in HUVECs significantly increased HUVEC lamellipodia formation (P<0.01), suggesting the miR-1253/WAVE2 interaction may play a role in endothelial cell shape and actin cytoskeleton function. Together, we have identified novel roles for miR-1253 and WAVE2 in a hypertension-related disparities context. This may ultimately lead to the discovery of additional actin-related genes which are important in the vascular-related complications of hypertension and influence the disproportionate susceptibility to hypertension among AAs in general and AA women in particular.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
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