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Metabolic risk profiling in childhood obesity through hormonal dysfunction and genetic variants: findings from a retrospective study

Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Childhood obesity is frequently accompanied by endocrine dysfunction and genetic susceptibility, but their combined contribution to metabolic risk remains insufficiently defined. This retrospective study evaluated hormonal, metabolic, and genetic determinants of metabolic syndrome (MetS) in children and adolescents with obesity. METHODS: Electronic medical records from January 2021 to May 2025 were reviewed. A total of 429 children and adolescents with obesity were included. Clinical, biochemical, endocrine, and targeted SNP genotyping data for FTO rs9939609, MC4R rs17782313, and LEPR rs1137101 were analyzed. MetS was defined according to pediatric criteria. Multivariable logistic regression and receiver operating characteristic analysis were performed. RESULTS: MetS was present in 187 participants (43.6%). Fasting glucose averaged 5.3 ± 0.5 mmol/L, HbA1c averaged 5.24 ± 0.22%, and median HOMA-IR was 4.4 (2.7-5.7). Insulin resistance was observed in 68.0% of Tanner stage I participants and 73.3% of Tanner stage II-V participants. Elevated HOMA-IR was strongly associated with MetS (OR = 2.89, 95% CI: 1.71-4.99, P < 0.001). Leptin was positively associated with MetS risk (OR = 1.32, 95% CI: 1.02-1.70, P = 0.033), whereas adiponectin was inversely associated (OR = 0.63, 95% CI: 0.49-0.80, P < 0.001). FTO and MC4R risk allele carriage independently predicted MetS, with ORs of 1.88 and 1.71, respectively. The combined endocrine-genetic model showed acceptable discrimination (AUC = 0.751). CONCLUSION: Insulin resistance, adipokine imbalance, and FTO/MC4R variants were independently associated with MetS in pediatric obesity. Integrated endocrine-genetic profiling may improve early metabolic risk stratification. CLINICAL TRIAL NUMBER: Not applicable.
Institution: Yangzhou University
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,190
OpenAlex ID: W7165138254
FWCI:
Cites: 42
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