Circulating miR-216a as a biomarker of metabolic alterations and obesity in women

Abstract

Obesity leads to an amplified risk of disease and contributes to the occurrence of type 2 diabetes, fatty liver disease, coronary heart disease, stroke, chronic kidney disease and various types of cancer. MicroRNAs (miRNAs), small non-coding RNA molecules of 20-25 nucleotides, can remain stable in plasma and have been studied as potential (predictive) biomarkers for obesity and related metabolic disorders. The aim of this study was to identify circulating miRNAs as biomarkers for obesity status and metabolic alterations in women. Circulating miR-216a and miR-155-5p were selected by miRNA expression profiling and validated by real time quantitative PCR in a validation cohort of 60 obese women and 60 normal weight-age-matched control women. This was supplemented by correlation analysis of the candidate miRNA and anthropometric variables, blood biochemistry and lipid profile markers. Circulating miR-216a was validated as a biomarker of obesity status with significantly reduced levels in obese women. Interestingly, this was associated with a negative correlation between the plasma miR-216a content and body mass index (BMI), waist circumference, mean arterial pressure (MAP), triglycerides, ratio of total cholesterol/high density lipoprotein (HDL)-cholesterol and high sensitivity-C reactive protein (hs-CRP).Taken together, we provide evidence for an abnormally expressed circulating miRNA, miR-216a, with additive value as a predictive marker for obesity that correlates with metabolic alterations presented by lipid profile and inflammatory markers.

Keywords: Biomarker; Metabolic syndrome; Obesity; microRNA.

Figure 1

Experimental setup for biomarker identification.(a) Overview of the screening cohort and miRNA expression profiling strategy. Every pool is organized in a group; the relative characteristics and inclusion criteria are described in the main text, while the images represent the main characteristics of each pool. Plasma RNA from 10 patients is subdivided in two pools by pooling RNA from 5 patients together within a group. Pool 1 consists of plasma RNA from 5 female patients with BMI≥ 25kg/m², forming a pool with obesity and overweight. Pool 2 consists of RNA from 5 healthy control women with normal weight BMI 18.5- 24.9 kg/m². (b) The lower panels show an overview of the validation cohort consisting of 60 obese (BMI≥ 30kg/m²) and 60 normal weight (BMI 18.5- 24.9 kg/m²) female subjects matched by age. miRNA candidates were validated by qPCR in plasma RNA of each individual sample (n=120). BMI, Body Mass Index; qPCR, quantitative Polymerase Chain Reaction.

Figure 2

Workflow Candidate selection. (a) Overview of the workflow of miRNA candidate selection following miRNA expression profiling. The general workflow includes the comparison of significantly deregulated miRNAs between the two pools using both global and endogenous normalization methods (miR-191-5p as endogenous normalizer). miRNAs corresponding between both methods following additional filtering (Raw Cq values > 30, fold change <|1.5|, false positives with undetermined values) were identified as biomarker candidates for validation. Pool 1 vs Pool 2; showed 23 significantly deregulated miRNAs by global normalization, 64 by endogenous normalization, and 15 corresponding between both methods, with 5 candidates after final filtering. (b) Hierarchical clustering and heatmap showing the ultimate list of miRNA candidates. Blue indicates fold changes < 0, reduced expression, and yellow indicates fold changes > 0, increased expression. (c) After considering miRNAs that remain stable after hemolysis, two candidates were chosen for validation: miR-216a-5p and miR- 155-5p.

Figure 3

Plasma miRNA expression levels in the validation cohort. The dot plots show the individual fold changes with the means and SEM for (a) miR- 216a and (b) miR-155-5p, by real time qPCR in plasma samples of the validation cohort (n=60 obese and n=60 normal weight controls paired by age). Every dot in the dot plot represents the expression corresponding to an individual subject, presented together with the mean and standard error of means per group. Not all miRNAs of a sample pair could be detected in every sample; for miR-216a, n=53 paired samples, thus 106 individual samples were rendered detectable, miR-155, n= 39 paired samples, thus 78 individual samples were rendered detectable. The relative miRNA expression levels were normalized to miR-191-5p. Statistical analysis included nonparametric Wilcoxon signed rank test for paired samples **P<0.01; SEM, standard error of means.

Figure 4

Spearman correlations between miR-216a, and miR-155-5p with anthropometric and biochemical markers. The scatterplots illustrate the correlations between miR-216a-5p fold change, or miR-155-5p fold change, and the following variables: (a) BMI (kg/m²), (b) DBP (mmHg), (c) MAP (mmHg), (d) Triglycerides (mmol/L), (e) ratio Total Cholesterol and HDL-cholesterol, (f) hs-CRP (mg/L) and (g) waist circumference (cm). r = Spearman rank correlation coefficient, p= p-value, BMI, body mass index; DBP, diastolic blood pressure; MAP, mean arterial pressure; HDL, high density lipoprotein; hs-CRP, high sensitivity C-reactive protein.