Abstract
Amino acid (AA) pattern shifts are increasingly recognized as early biochemical fingerprints of pediatric obesity and its metabolic sequelae. In children and adolescents, elevations in branched-chain AAs (BCAAs: leucine, isoleucine, valine), aromatic AAs (AAAs: phenylalanine, tyrosine), and glutamate—often coupled with reductions in glycine and serine—have been repeatedly linked to insulin resistance (IR), dysglycemia, and metabolic dysfunction-associated fatty liver disease (MASLD/NAFLD). These signatures may reflect impaired BCAA catabolism, altered mitochondrial substrate handling, hepatic nitrogen flux, and adipose-liver crosstalk, and they may provide complementary risk stratification beyond standard clinical markers. (1) To summarize AA pattern changes characteristic of pediatric/adolescent obesity, prediabetes, diabetes, and fatty liver disorders and their relationship to insulin resistance. (2) To synthesize evidence linking AA signatures to IGF-1 biology and developmental covariates (age, sex, puberty), and to discuss management implications. A structured review (last 20 years) of PubMed/Scopus-indexed literature was performed, prioritizing pediatric/adolescent studies. We included targeted and untargeted metabolomics studies reporting fasting or standardized AA measures in: (i) obesity/obesity phenotypes, (ii) prediabetes/abnormal glucose tolerance, (iii) Type 1 or Type 2 diabetes, and (iv) NAFLD/MASLD, with outcomes involving IR (HOMA-IR, clamp-derived indices), hepatic steatosis (MRI/MRS, ultrasound, biopsy), or cardiometabolic risk clustering. We narratively synthesized AA directionality and consistency across conditions and platforms. Risk of bias was assessed using RoB 2 for randomized trials and ROBINS-I for non-randomized studies. Across multiple pediatric cohorts, obesity was most consistently associated with higher BCAAs, AAAs, glutamate, and several BCAA-derived intermediates, with lower glycine/serine in metabolically higher-risk phenotypes. Several studies linked AA signatures to future IR or hypertriglyceridemia and identified associations with metabolically unhealthy obesity. In youth with dysglycemia or Type 2 diabetes risk, AA profiles were heterogeneous across studies but increasingly support combined panels (BCAA/AAA elevation with glycine reduction and glutamine-glutamate imbalance) to capture β-cell stress and IR-related trajectories. In pediatric NAFLD, AA signatures (notably BCAA dysregulation and glutamate-related indices) were associated with steatosis burden and, in some studies, predicted liver fat independent of BMI and conventional risk factors. Developmental effects were substantial: age, sex, and pubertal stage modified AA distributions, and IGF-1-linked metabolomic relationships suggest GH/IGF axis-metabolism coupling. AA patterns provide biologically plausible, developmentally modulated candidate biomarkers which align with IR, dysglycemia, and pediatric fatty liver risk. Future pediatric studies should standardize sampling, puberty adjustment, and analytic pipelines, and should test whether AA-informed risk stratification improves prevention and treatment response monitoring.