Plasma amino acid profiles in pediatric obesity: potential biomarkers for the early assessment of metabolic risk

儿童肥胖症患者血浆氨基酸谱:代谢风险早期评估的潜在生物标志物

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Abstract

INTRODUCTION: Childhood obesity is among the most serious and rapidly growing public health issues globally. Although body mass index (BMI) is commonly used to evaluate obesity, it does not always reflect early metabolic disturbances. Recent studies have emphasized the importance of metabolomics, particularly plasma amino acid profiling, in detecting subclinical metabolic risk. In this context, branched-chain amino acids (BCAAs) have emerged as potential early biomarkers of insulin resistance and cardiometabolic risk. METHODS: This cross-sectional study included 97 participants aged 5-18 years, including 56 children with obesity (BMI ≥ 95th percentile) and 41 healthy controls. Anthropometric measurements, as well as fasting glucose, insulin, lipid profile, and HbA1c levels, were recorded. Plasma concentrations of 44 amino acids were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with a commercial kit (JASEM®, Agilent Ultivo Triple Quadrupole LC-MS). BCAA levels and relevant ratios, such as glycine/BCAA and glutamic acid/glutamine, were calculated. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic performance of key variables. RESULTS: Children with obesity had significantly higher levels of BCAAs and other amino acids, including phenylalanine, tyrosine, alanine, and glutamic acid (all p < 0.05). Conversely, glycine, serine, and asparagine levels were significantly lower in children with obesity. Fasting insulin emerged as a strong predictor of obesity [area under the ROC curve (AUC) = 0.87], while total BCAAs also displayed strong predictive performance (AUC = 0.78). A reduced glycine/BCAA ratio and an increased glutamic acid/glutamine ratio were associated with early metabolic dysregulation. CONCLUSION: Our findings highlight the potential of plasma amino acid profiling as a supportive tool for the early assessment of metabolic risk in children with obesity. The integration of amino acid-based indices could improve risk classification and support personalized preventive strategies in pediatric populations.

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