Dataset Information

Circulatory MicroRNAs in Plasma and Atrial Fibrillation in the General Population: The Rotterdam Study.

ABSTRACT:

Background

MicroRNAs (miRNAs), small non-coding RNAs regulating gene expression, have been shown to play an important role in cardiovascular disease. However, limited population-based data regarding the relationship between circulatory miRNAs in plasma and atrial fibrillation (AF) exist. Moreover, it remains unclear if the relationship differs by sex. We therefore aimed to determine the (sex-specific) association between plasma circulatory miRNAs and AF at the population level.

Methods

Plasma levels of miRNAs were measured using a targeted next-generation sequencing method in 1999 participants from the population-based Rotterdam Study. Logistic regression and Cox proportional hazards models were used to assess the associations of 591 well-expressed miRNAs with the prevalence and incidence of AF. Models were adjusted for cardiovascular risk factors. We further examined the link between predicted target genes of the identified miRNAs.

Results

The mean age was 71.7 years (57.1% women), 98 participants (58 men and 40 women) had prevalent AF at baseline. Moreover, 196 participants (96 men and 100 women) developed AF during a median follow-up of 9.0 years. After adjusting for multiple testing, miR-4798-3p was significantly associated with the odds of prevalent AF among men (odds ratio, 95% confidence interval, 0.39, 0.24-0.66, p-value = 0.000248). No miRNAs were significantly associated with incident AF. MiR-4798-3p could potentially regulate the expression of a number of AF-related genes, including genes involved in calcium and potassium handling in myocytes, protection of cells against oxidative stress, and cardiac fibrosis.

Conclusions

Plasma levels of miR-4798-3p were significantly associated with the odds of prevalent AF among men. Several target genes in relation to AF pathophysiology could potentially be regulated by miR-4798-3p that warrant further investigations in future experimental studies.

SUBMITTER: Geurts S

PROVIDER: S-EPMC8775308 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundDifferent biological pathways have been related to atrial fibrillation (AF). Novel biomarkers capturing inflammation, oxidative stress, and neurohumoral activation have not been investigated comprehensively in AF.Methods and resultsIn the population-based Gutenberg Health Study (n = 5000), mean age 56 ± 11 years, 51% males, we measured ten biomarkers representing inflammation (C-reactive protein, fibrinogen), cardiac and vascular function (midregional pro adrenomedullin [MR-proADM], midregional pro atrial natriuretic peptide [MR-proANP], N-terminal pro-B-type natriuretic peptide [Nt-proBNP], sensitive troponin I ultra [TnI ultra], copeptin, and C-terminal pro endothelin-1), and oxidative stress (glutathioneperoxidase-1, myeloperoxidase) in relation to manifest AF (n = 161 cases). Individuals with AF were older, mean age 64.9 ± 8.3, and more often males, 71.4%. In Bonferroni-adjusted multivariable regression analyses strongest associations per standard deviation increase in biomarker concentrations were observed for the natriuretic peptides Nt-proBNP (odds ratio [OR] 2.89, 99.5% confidence interval [CI] 2.14-3.90; P<0.0001), MR-proANP (OR 2.45, 99.5% CI 1.91-3.14; P<0.0001), the vascular function marker MR-proADM (OR 1.54, 99.5% CI 1.20-1.99; P<0.0001), TnI ultra (OR 1.50, 99.5% CI 1.19-1.90; P<0.0001) and. fibrinogen (OR 1.44, 99.5% CI 1.19-1.75; P<0.0001). Based on a model comprising known clinical risk factors for AF, all biomarkers combined resulted in a net reclassification improvement of 0.665 (99.3% CI 0.441-0.888) and an integrated discrimination improvement of >13%.ConclusionsIn conclusion, in our large, population-based study, we identified novel biomarkers reflecting vascular function, MR-proADM, inflammation, and myocardial damage, TnI ultra, as related to AF; the strong association of natriuretic peptides was confirmed. Prospective studies need to examine whether risk prediction of AF can be enhanced beyond clinical risk factors using these biomarkers.