Metabolomics allows the discrimination of the pathophysiological relevance of hyperinsulinism in obese prepubertal children

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BACKGROUND/OBJECTIVES:Insulin resistance (IR) is the cornerstone of the obesity-associated metabolic derangements observed in obese children. Targeted metabolomics was employed to explore the pathophysiological relevance of hyperinsulinemia in childhood obesity in order to identify biomarkers of IR with potential clinical application.SUBJECTS/METHODS:One hundred prepubertal obese children (50 girls/50 boys, 50% IR and 50% non-IR in each group), underwent an oral glucose tolerance test for usual carbohydrate and lipid metabolism determinations. Fasting serum leptin, total and high molecular weight-adiponectin and high-sensitivity C-reactive protein (CRP) levels were measured and the metabolites showing significant differences between IR and non-IR groups in a previous metabolomics study were quantified. Enrichment of metabolic pathways (quantitative enrichment analysis) and the correlations between lipid and carbohydrate metabolism parameters, adipokines and serum metabolites were investigated, with their discriminatory capacity being evaluated by receiver operating characteristic (ROC) analysis.RESULTS:Twenty-three metabolite sets were enriched in the serum metabolome of IR obese children (P < 0.05, false discovery rate (FDR) < 5%). The urea cycle, alanine metabolism and glucose-alanine cycle were the most significantly enriched pathways (PFDR < 0.00005). The high correlation between metabolites related to fatty acid oxidation and amino acids (mainly branched chain and aromatic amino acids) pointed to the possible contribution of mitochondrial dysfunction in IR. The degree of body mass index-standard deviation score (BMI-SDS) excess did not correlate with any of the metabolomic components studied. In the ROC analysis, the combination of leptin and alanine showed a high IR discrimination value in the whole cohort (area under curve, AUCALL = 0.87), as well as in boys (AUCM = 0.84) and girls (AUCF = 0.91) when considered separately. However, the specific metabolite/adipokine combinations with highest sensitivity were different between the sexes.CONCLUSIONS:Combined sets of metabolic, adipokine and metabolomic parameters can identify pathophysiological relevant IR in a single fasting sample, suggesting a potential application of metabolomic analysis in clinical practice to better identify children at risk without using invasive protocols.

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