MicroRNAs (miRNAs) are a class of small non-coding RNA molecules involved in the regulation of gene expression. They are involved in the fine-tuning of fundamental biological processes such as proliferation, differentiation, survival and apoptosis in many cell types. Emerging evidence suggests that miRNAs regulate critical pathways involved in stem cell function. Several miRNAs have been suggested to target transcripts that directly or indirectly coordinate the cell cycle progression of stem cells. Moreover, previous studies have shown that altered expression levels of miRNAs can contribute to pathological conditions, such as cancer, due to the loss of cell cycle regulation. However, the precise mechanism underlying miRNA-mediated regulation of cell cycle in stem cells is still incompletely understood. In this review, we discuss current knowledge of miRNAs regulatory role in cell cycle progression of stem cells. We describe how specific miRNAs may control cell cycle associated molecules and checkpoints in embryonic, somatic and cancer stem cells. We further outline how these miRNAs could be regulated to influence cell cycle progression in stem cells as a potential clinical application.

Background and Purpose: MicroRNAs (miRNAs) are post-transcriptionally regulators of gene expression that can be released extracellularly upon pathophysiological processes. By complementary binding of target transcripts, miRNAs can modulate the expression of an abundance of genes. Increasing evidence recognize miRNAs as promising biomarkers for complex traits, including cardiovascular disease and stroke. We conducted a longitudinal study to determine the association between circulatory miRNAs and incident stroke in a population-based setting. Methods: Next-generation sequencing was used to measure expression levels of 2083 miRNAs in plasma samples, collected between 2002 and 2005, from 1914 stroke-free participants of the Rotterdam Study. Participants were assessed for incident stroke through continuous monitoring of medical records until January 1, 2016. Cox proportional hazards regression models adjusted for age, sex, and vascular risk factors were used to investigate the association between the levels of 591 miRNAs well-expressed in plasma and incident stroke. Furthermore, stroke subtype analysis was performed to assess the link between identified miRNAs and ischemic, hemorrhagic, and unspecified stroke. Subsequently, post hoc analyses were conducted to gain insight into the association between putative target genes of miRNAs and stroke. Results: Of 1914 participants (mean age 71.5 years ±7.6; 57.7% women), 138 were diagnosed with incident stroke during a mean follow-up of 9.7±3.2 years. After adjusting for potential confounders, we found plasma levels of 3 miRNAs to be associated with incident stroke (false discovery rate-adjusted P <0.05). These include miR-6124 (hazard ratio, 1.66 [95% CI, 1.31–2.09]), miR-5196-5p (hazard ratio, 1.90 [95% CI, 1.39–2.61]), and miR-4292 (hazard ratio, 2.65 [95% CI, 1.62–4.34]). In silico analysis of the putative target genes of these miRNAs showed associations of variants in several target genes with stroke. Conclusions: This study indicates that plasma levels of 3 miRNAs are associated with the risk of stroke, proposing them as potential biomarkers for early detection of the disease.

Background Tobacco smoking is a well-known modifiable risk factor for many chronic diseases, including cardiovascular disease (CVD). One of the proposed underlying mechanism linking smoking to disease is via epigenetic modifications, which could affect the expression of disease-associated genes. Here, we conducted a three-way association study to identify the relationship between smoking-related changes in DNA methylation and gene expression and their associations with cardio-metabolic traits. Results We selected 2549 CpG sites and 443 gene expression probes associated with current versus never smokers, from the largest epigenome-wide association study and transcriptome-wide association study to date. We examined three-way associations, including CpG versus gene expression, cardio-metabolic trait versus CpG, and cardio-metabolic trait versus gene expression, in the Rotterdam study. Subsequently, we replicated our findings in The Cooperative Health Research in the Region of Augsburg (KORA) study. After correction for multiple testing, we identified both cis- and trans-expression quantitative trait methylation (eQTM) associations in blood. Specifically, we found 1224 smoking-related CpGs associated with at least one of the 443 gene expression probes, and 200 smoking-related gene expression probes to be associated with at least one of the 2549 CpGs. Out of these, 109 CpGs and 27 genes were associated with at least one cardio-metabolic trait in the Rotterdam Study. We were able to replicate the associations with cardio-metabolic traits of 26 CpGs and 19 genes in the KORA study. Furthermore, we identified a three-way association of triglycerides with two CpGs and two genes (GZMA; CLDND1), and BMI with six CpGs and two genes (PID1; LRRN3). Finally, our results revealed the mediation effect of cg03636183 (F2RL3), cg06096336 (PSMD1), cg13708645 (KDM2B), and cg17287155 (AHRR) within the association between smoking and LRRN3 expression. Conclusions Our study indicates that smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic risk factors. These findings may provide additional insights into the molecular mechanisms linking smoking to the development of CVD.

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.

MicroRNAs (miRNAs) are non-coding RNA molecules that regulate gene expression. Extensive research has explored the role of miRNAs in the risk for type 2 diabetes (T2D) and coronary heart disease (CHD) using single-omics data, but much less by leveraging population-based omics data. Here we aimed to conduct a multi-omics analysis to identify miRNAs associated with cardiometabolic risk factors and diseases. First, we used publicly available summary statistics from large-scale genome-wide association studies to find genetic variants in miRNA-related sequences associated with various cardiometabolic traits, including lipid and obesity-related traits, glycemic indices, blood pressure, and disease prevalence of T2D and CHD. Then, we used DNA methylation and miRNA expression data from participants of the Rotterdam Study to further investigate the link between associated miRNAs and cardiometabolic traits. After correcting for multiple testing, 180 genetic variants annotated to 67 independent miRNAs were associated with the studied traits. Alterations in DNA methylation levels of CpG sites annotated to 38 of these miRNAs were associated with the same trait(s). Moreover, we found that plasma expression levels of 8 of the 67 identified miRNAs were also associated with the same trait. Integrating the results of different omics data showed miR-10b-5p, miR-148a-3p, miR-125b-5p, and miR-100-5p to be strongly linked to lipid traits. Collectively, our multi-omics analysis revealed multiple miRNAs that could be considered as potential biomarkers for early diagnosis and progression of cardiometabolic diseases.