Translating the microRNA signature of microvesicles derived from human coronary artery smooth muscle cells in patients with familial hypercholesterolemia and coronary artery disease.

Aims: To analyze the impact of atherogenic lipoproteins on the miRNA signature of microvesicles derived from human coronary artery smooth muscle cells (CASMC) and to translate these results to familial hypercholesterolemia (FH) and coronary artery disease (CAD) patients.
Methods: Conditioned media was collected after exposure of CASMC to atherogenic lipoproteins. Plasma samples were collected from two independent populations of diagnosed FH patients and matched normocholesterolemic controls (Study population 1, N=50; Study population 2, N=24) and a population of patients with suspected CAD (Study population 3, N=50). Extracellular vesicles were isolated and characterized using standard techniques. A panel of 30 miRNAs related to vascular smooth muscle cell (VSMC) (patho-)physiology was analyzed using RT-qPCR.
Results: Atherogenic lipoproteins significantly reduced levels of miR-15b-5p, -24-3p, -29b-3p, -130a-3p, -143-3p, -146a-3p, -222-3p, -663a levels (P<0.050) in microvesicles (0.1μm-1μm in diameter) released by CASMC. Two of these miRNAs, miR-24-3p and miR-130a-3p, were reduced in circulating microvesicles from FH patients compared with normocholesterolemic controls in a pilot study (Study population 1) and in different validation studies (Study populations 1 and 2) (P<0.050). Supporting these results, plasma levels of miR-24-3p and miR-130a-3p were also downregulated in FH patients compared to controls (P<0.050). In addition, plasma levels of miR-130a-3p were inversely associated with coronary atherosclerosis in a cohort of suspected CAD patients (Study population 3) (P<0.050).
Conclusions: Exposure to atherogenic lipoproteins modifies the miRNA profile of CASMC-derived microvesicles and these alterations are reflected in patients with FH. Circulating miR-130a-3p emerges as a potential biomarker for coronary atherosclerosis.
(Copyright © 2017 Elsevier Ltd. All rights reserved.)