ESPE Abstracts (2016) 86 P-P2-504

aPediatrics Unit, Department of Biomedical Sciences and Human Oncology, University of Bari “A. Moro”, Bari, Italy; bInstitute of Biomedical Technologies, National Research Council, Bari, Italy; cMolecular Endocrinology Unit, Bambino Gesù Children’s Hospital, Roma, Italy; dInstitute of Biomembranes and Bioenergetics, National Research Council, Bari, Italy; eDepartment of Biosciences, Biotechnology, and Pharmacological Sciences, University of Bari “A. Moro”, Bari, Italy; fDepartment of Biosciences, University of Milan, Milano, Italy

Background: Children born small for gestational age (SGA) are at increased risk of coronary heart disease and type 2 diabetes in adulthood, due to reprogramming of endocrine and metabolic functions. Dysregulation of specific miRNAs in response to genetic and environmental factors contribute to aberrant gene expression patterns underlying metabolic dysfunction.

Objective and hypotheses: We aimed to identify miRNAs associated with increased risk of obesity in SGA children. We hypothesized that circulating miRNA expression profiles vary according to differences in BMI and circulating miRNAs may reflect metabolic dysfunction.

Method: We recruited 4 SGA obese children (BMI-SDS 2.41±0.72, 11.96±1.76 years) and 4 appropriate for gestational age (AGA) obese children (BMI SDS 2.38±0.57, 13.61±0.5 years), with their respective controls matched for sex and age. Small RNAs have been extracted by serum and sequenced by miSeq Illumina sequencer. miRNA-Seq data has been analyzed throughout a customized bioinformatics pipeline in order to detect and quantify miRNA profile in the groups analyzed. The results have been validated by RT-qPCR.

Results: We identified four down regulated and ten up-regulated miRNAs in the group of obese SGA, among which four shared with AGA obese children, compared to AGA controls. Specific miRNAs, such as miR-486-3p, miR-122-5p, miR-16-5p, miR-532-5p, miR-425-5p and miR-16-2-3p appeared specifically correlated with the obesity in SGA children. We used mirTarBase (miRNA-target interactions database) to search experimentally validated mRNA targets. A functional analysis of these genes in DAVID database showed a significant statistical enrichment in ‘regulation of cell proliferation’ and ‘regulation of metabolic process’.

Conclusion: We identified new serum molecular biomarkers which may be useful for cardiometamolic risk prediction in SGA children.

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