Association between Hypertension with and without Left Ventricular Hypertrophy and the Expression of a Panel of microRNAs in an Iranian Population
Abstract
Introduction: Given the established role of microRNAs (miRNAs) in hypertension (HTN), this study aimed to analyze the expression of a defined miRNA panel in hypertensive individuals, both with and without left ventricular hypertrophy (LVH), compared with normotensive controls within an Iranian population.
Methods: We conducted a cross-sectional study with case-control sampling, comprising three study groups: controls, HTN, and HTN+LVH. Through an extensive literature review, we selected a panel of eight miRNAs (miR-1, miR-21, miR-29a, miR-29b, miR-133, miR-155, miR-221, and miR-222) for analysis using real-time PCR. Gene expression data were analyzed through a general linear model implemented in R programming.
Results: The study analyzed 100 total samples. We used miR-29a and miR-133 as endogenous controls for calculations. Analysis revealed no significant association between miR-29b or miR-221 expression and the study groups (P>0.2 for both). Additionally, miR-1 demonstrated downregulation in both hypertensive groups (P<0.05), although this effect lost significance after adjusting for potential confounders (P=0.05–0.2). The HTN+LVH group showed significant downregulation of miR-21 (P<0.05). The duration of HTN diagnosis correlated with the upregulated expression of both miR-155 and miR-222. The strongest association emerged for miR-222, with the study groups explaining 25.7% of its variation (the highest R² value among all models).
Conclusions: HTN without LVH might be associated with the downregulation of miR-1 and miR-155 and the upregulation of miR-222. HTN, along with LVH, might be associated with the downregulation of miR-1 and miR-21 and the upregulation of miR-222. Increasing years of experiencing HTN were correlated with the upregulation of miR-155 and miR-222. The largest effect size was for miR-222.
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| Files | ||
| Issue | Vol 20 No 1 (2025) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/jthc.v20i1.19218 | |
| Keywords | ||
| Molecular Epidemiology Genetic Epidemiology Personalized Medicine | ||
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