MiR-486 and miR-92a Identified in Circulating HDL Discriminate between Stable and Vulnerable Coronary Artery Disease Patients

<div><p>Small non-coding microRNAs (miRNAs) are implicated in gene regulation, including those involved in coronary artery disease (CAD). Our aim was to identify whether specific serum miRNAs present in the circulating lipoproteins (Lp) are associated with stable or vulnerable CAD patients. A cardiovascular disease-focused screening array was used to assess miRNAs distribution in sera collected from 95 CAD patients: 30 with stable angina (SA), 39 with unstable angina (UA), 26 at one month after myocardial infarction (MI) and 16 healthy control subjects. We found that miR-486, miR-92a and miR-122 presented the highest expression in CAD sera. These miRNA together with miR-125a, miR-146a and miR-33a were further individually analyzed by TaqMan assays. The results were consistent with PCR-array screening data that all of these miRNAs were significantly increased in CAD patients compared to controls. Using a binary logistic regression model, we established that miR-486 and miR-92a in association with some high-density lipoprotein (HDL) components can designate vulnerable CAD patients. Further, all classes of Lp were isolated from sera by density gradient ultracentrifugation. Analysis of the selected miRNAs in each Lp class showed that they were associated mainly with HDL, miR-486 and miR-92a having the highest levels. In UA and MI patients, miR-486 prevailed in HDL₂, while miR-92a prevailed in HDL₃, and their levels discriminate between stable and vulnerable CAD patients. We identified two circulating miRNAs that in association with some lipid metabolism biomarkers can be used as an additional tool to designate vulnerable CAD patients.</p></div

Clinical characteristics of the CAD patients and control subjects.

<p>SA = patients with stable angina, UA = patients with unstable angina, MI = patients at 1 month after myocardial infarction, NA = not available, ND = not detectable. Data are expressed as means ± standard error of the mean (SEM) and analyzed with Oneway ANOVA test with LSD Posthoc analysis. Chi-squared (χ²) analysis was performed to evaluate the differences between logistic data (gender, age distribution, obesity, diabetes, hypertension, medication).</p><p>^<b>*</b> p<0.05</p><p>^** p<0.01</p><p>^*** p<0.001 vs. Control</p><p>^<b>§</b> p<0.05 vs. UA</p><p>Clinical characteristics of the CAD patients and control subjects.</p

Hyperglycemia Determines Increased Specific MicroRNAs Levels in Sera and HDL of Acute Coronary Syndrome Patients and Stimulates MicroRNAs Production in Human Macrophages - Fig 3

<p><b>Expression of Drosha, DGCR8 and Dicer mRNA (A) and of selected miRNAs (B) in human macrophages incubated with sera from CAD patients with stable angina (SA) or acute coronary syndrome (ACS), with/without hyperglycemia</b>. The expression level of each gene of interest was determined relative to β-actin, while the expression level of each miRNA was determined relative to snRNU6. Data are expressed as mean 2^-ΔΔCq values ± standard error of the mean. LPDS = human lipoprotein-deficient serum (* p<0.05, ** p<0.01, *** p<0.001 hyperglycemic (HG) vs. normoglycemic (NG), Student T-test).</p

Levels of apolipoprotein A-I (apoA-I) (A) and paraoxonase-1 (PON1) activity (B) in HDL₂ and HDL₃ fractions isolated by isopycnic density gradient ultracentrifugation from pooled sera of control subjects and the coronary artery disease (CAD) patients with stable angina (SA), unstable angina (UA) and patients at one month after myocardial infarction (MI); the procedure was performed on 3 independent pools of sera from each group.

<p>Data are expressed as means ± standard deviation and analyzed with Oneway ANOVA analysis with LSD Posthoc test; * p<0.05 vs. SA group.</p

Boxplot distribution of the investigated miRNAs in sera.

<p>Levels of miR-223 (<b>A</b>), miR-92a (<b>B</b>), miR-486 (<b>C</b>), miR-122 (<b>D</b>), miR-125a (<b>E</b>), miR-146a (<b>F</b>) in sera from <b>Control</b> subjects and coronary artery disease (CAD) patients with stable angina (<b>SA</b>) or acute coronary syndrome (<b>ACS</b>), with/without hyperglycemia. Data are expressed as log-transformed 2^-ΔCq values, multiplied by 10⁶ ± standard error of the mean (** p<0.01, *** p<0.001 hyperglycemic (HG) vs. normoglycemic (NG), ^### p<0.001 SA or ACS vs. Control, Student T-test).</p

Lipids, apolipoproteins and PON1 activity in sera of normoglycemic and hyperglycemic CAD patients and control subjects.

<p>Lipids, apolipoproteins and PON1 activity in sera of normoglycemic and hyperglycemic CAD patients and control subjects.</p

Clinical characteristics of the normoglycemic and hyperglycemic CAD patients and control subjects.

<p>Clinical characteristics of the normoglycemic and hyperglycemic CAD patients and control subjects.</p

Boxplot distribution of the highest ranked miRNAs after miRNAs screening analysis.

<p>Levels of miR-486 (<b>A</b>), miR-92a (<b>B</b>), miR-122 (<b>C</b>), miR-125a (<b>D</b>), miR-146a (<b>E</b>) and miR-33a (<b>F</b>) measured in the sera from control subjects and coronary artery disease (CAD) patients with stable angina (SA), unstable angina (UA) and patients at one month after myocardial infarction (MI). Data are expressed as log-transformed individual 2^-ΔCq values. Note that significantly increased serum miRNAs levels were measured in all CAD patients vs control sera, but they do not differ statistically between the CAD groups (<b>*</b>p<0.05, <b>**</b>p<0.01, <b>***</b>p<0.001 vs. control group, Oneway ANOVA analysis with LSD Posthoc test).</p