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Updated: Apr 15, 2026

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Exploring Metabolic Changes in Children with Congenital Hypothyroidism: A Serum Metabolomic Study Combined by Machine

Yucheng Guo1, Xilun Li1, Kexin Fang1

  • 1Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, Fujian, China.

Journal of Proteome Research
|April 13, 2026
PubMed

Insights

Congenital hypothyroidism (CH) in children can be diagnosed using NMR-based metabolomics. Seven common metabolites were identified, and an artificial neural network model achieved 89.4% accuracy for early CH detection.

Area of Science:

  • Endocrinology
  • Metabolomics
  • Genetics

Background:

  • Congenital hypothyroidism (CH) is a genetic endocrine disorder.
  • Untreated CH can lead to developmental delays.
  • Early diagnosis is crucial for effective intervention.

Purpose of the Study:

  • To identify metabolic disturbances in children with CH using NMR-based metabolomics.
  • To discover potential diagnostic biomarkers for CH.
  • To develop an accurate diagnostic model for CH.

Main Methods:

  • Serum samples from CH children and healthy controls were analyzed using NMR-based metabolomics.
  • Multivariate statistical analysis identified differential metabolites.
  • Recursive feature elimination (RFE) and artificial neural network (ANN) models were used for diagnosis.

Main Results:

  • Seven common differential metabolites were identified across age groups, including lysine, 1-methylhistidine, glycerophosphocholine, phosphocholine, β-glucose, lipids, and creatine.
  • CH children exhibited metabolic disturbances in glycerophospholipid and glycine, serine, and threonine metabolism.
  • An optimized ANN model using the top five metabolites achieved 89.4% prediction accuracy.

Conclusions:

  • Identified metabolites serve as potential diagnostic biomarkers for CH in children.
  • This approach can enhance early diagnosis accuracy and serve as a rapid screening tool for newborns.
  • Findings support an auxiliary diagnostic method for suspected CH cases, facilitating timely clinical intervention.

Keywords:
congenital hypothyroidismdifferential metabolitesmachine learningmetabolomicsnuclear magnetic resonance

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