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Mir-1, miR-122, miR-132, and miR-133 Are Related to Subclinical Aortic Atherosclerosis Associated with Metabolic Syndrome

Bibliographic Data

ID15466132
AuthorsAgnė Šatrauskienė (0009-0004-8809-9355, Vilnius University), Rokas Navickas (0000-0002-8258-8009, Vilnius University, corresponding author), Aleksandras Laucevičius (0000-0002-8642-1441, Vilnius University), Tomas Krilavičius (0000-0001-8509-420X, Vytautas Magnus University), Rūta Užupytė (0000-0001-6175-0583, Vilnius University), Monika Zdanytė (0000-0002-0754-8015, University of Tübingen), Ligita Ryliškytė (0000-0002-8992-6795, Vilnius University), Agnė Jucevičienė (0000-0002-4486-1879, Vilnius University), Paul Holvoet (0000-0001-9201-0772, KU Leuven)
Year2021
Volume18
Issue4
Pages1483-1483
Publication date2021-02-04
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph18041483
PMID33557426
OpenAlexW3126532634
LanguageEN
References cited4

Previously, miR-1, miR-122, miR-126, miR-132, miR-133, and miR-370 were found to be related to coronary artery disease (CAD) progression. However, their relationship with subclinical atherosclerosis, especially in subjects with metabolic syndrome, is unknown. Therefore, our aim was to determine their relationship with arterial markers of subclinical atherosclerosis. Metabolic syndrome subjects (n = 182) with high cardiovascular risk but without overt cardiovascular disease (CVD) were recruited from the Lithuanian High Cardiovascular Risk (LitHiR) primary prevention program. The ardio-ankle vascular index (CAVI), augmentation index normalized to a heart rate of 75 bpm (AIxHR75), aortic pulse wave velocity (AoPWV), and carotid artery stiffness were assessed. MicroRNAs (miRs) were analyzed in serum. Pearson correlation and a univariate linear regression t -test showed that miR-1, miR-133b, and miR-133a were negatively associated with CAVI mean, whereas miR-122 was positively associated. MiR-1, miR-133b and miR-133a, and miR-145 were negatively associated with AIxHR75. MiR-122 correlated negatively with AoPWV. In multivariate linear regression models, miR-133b and miR-122 predicted CAVImean, miR-133 predicted AIxHR75, and miR-122 predicted AoPWV. MiR-132 predicted right carotid artery stiffness, and miR-1 predicted left carotid artery stiffness. The addition of smoking to miR-133b and miR-122 enhanced the prediction of CAVI. Age and triglycerides enhanced the prediction of AoPWV by miR-122. A cluster of four miRs are related to subclinical atherosclerosis in subjects with metabolic syndrome. Combined, they may have a more substantial diagnostic or prognostic value than any single miR. Future follow-up studies are needed to establish their clinical relevance

Arterial stiffness · Blood pressure · Cardiology · Coronary artery disease · Metabolic syndrome · Obesity · Pulse wave velocity · Subclinical infection · Cancer-related molecular mechanisms research · Circular RNAs in diseases · Medicine · MicroRNA in disease regulation · Internal Medicine

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