Objective: Circulating microRNAs (miRNAs) have been proposed as emerging biomarkers for obesity and metabolic comorbidities. Our aim was to characterize miRNA signatures and assess their utility to discriminate between insulin resistance (IR) phenotypes in paediatric obesity and evaluate their role in diverse metabolic pathways.
Methods: Observational, case-control study, including prepubertal children between 6 and 10 years, divided in three study groups: a) healthy control (n=3), b) metabolically healthy obese children (n=3) and c) IR obese children (n=3). Obese patients were defined by a body mass index > 2 SD for age and sex. IR patients fulfilled at least one of the ADA’s insulin resistance criteria (Basal Insulin>15 U/mL; Insulin along the OGTT>150 U/mL; Insulin>75U/mL at 120’ on the OGTT; and/or, iHOMA>3,5). We first screened 179 miRNAs to identify differentially expressed miRNAs between groups. Total RNA was extracted from plasma using the miRNeasy Serum/Plasma Advanced Kit (Qiagen). Correlations between miRNA levels and clinical parameters were investigated.
Results: The established criteria for miRNA candidate’s selection were high expression levels (Max. Cq<39 and detected in at least 95% of all samples) and statistical significance (p<0.05). We found 19 miRNAs highly expressed and differentially detected between a) metabolically healthy obese vs. IR obese children and b) healthy subjects vs. obese children, including miRNAs with previously reported roles in iron and glucose metabolism, oxidative stress, inflammation and erythrocyte integrity.
Conclusion: The miRNA profile identified new candidates related to pediatric obesity, and enables to differentiate between IR phenotype and metabolically healthy obese children.
Do you have obtained the secuences of each individual miRNA for all the cases?
If so, did you ever considered to carry out a computational study of the secondary structure of the mi-RNAs sequences to calculate Free energy and stimate stability and/or search 2D structural patterns/mottiffs toward biomarkerscharacterization and discovery?
In so doing, you can use Vienna RNAfold structure package or similar!
http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi