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Enhancing Genotype-Phenotype Correlation in Pediatric PKU: A Comparative Analysis of Hotspot Mutations and Prediction

Li Zhang1,2, Jie Ren3, Jilong Su3

  • 1Newborn Disease Screening Center, Children's Hospital, Affiliated to Shanxi Medical University, Shanxi Children's Hospital Shanxi Maternal and Child Health Hospital, Taiyuan, China.

Genetic Testing and Molecular Biomarkers
|July 14, 2026
PubMed

Insights

This study analyzed genotype-phenotype correlations in Chinese pediatric phenylketonuria (PKU) patients. The allele phenotype value/genotype-phenotype value system showed higher accuracy in predicting PKU phenotypes.

Area of Science:

  • Genetics
  • Metabolic Disorders
  • Human Disease

Background:

  • Phenylketonuria (PKU) is a significant genetic metabolic disorder in China, affecting approximately 1 in 11,000 births.
  • High genetic heterogeneity in PKU necessitates understanding genotype-phenotype correlations for effective clinical management.

Purpose of the Study:

  • To investigate genotype-phenotype correlations in Chinese pediatric PKU patients.
  • To compare the predictive accuracy of two models: the allele phenotype value/genotype-phenotype value (APV/GPV) system and the assigning value (AV) score system.

Main Methods:

  • Analysis of genotype-phenotype data from pediatric PKU patients across various regions in China.
  • Comparison of APV/GPV system accuracy against the AV score system for predicting PKU phenotypes.
  • Focus on hotspot mutations within the phenylalanine hydroxylase (PAH) gene.

Main Results:

  • Compound heterozygotes were the predominant genotype in PKU patients.
  • Classical PKU (cPKU) represented 44% of cases; mild hyperphenylalaninemia was observed in 22%.
  • The APV/GPV system achieved higher accuracy (72.02%) than the AV score system (56.82%, p < 0.05) overall, though not significantly different for cPKU alone (p > 0.05).

Conclusions:

  • Genotype-phenotype correlations in Chinese PKU patients vary regionally.
  • Enhancing hotspot mutation data is crucial for improving PKU prediction models.
  • More accurate prediction models are needed to improve patient care and reduce familial burden.
Abstract

Keywords:
PAHPKUgenotype–phenotype correlationhotspot mutationprediction models

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