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Genotype-Phenotype Correlations in PMM2-CDG.

Laurien Vaes1, Daisy Rymen2, David Cassiman3

  • 1Faculty of Medicine, KU Leuven, B3000 Leuven, Belgium.

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|November 27, 2021
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Summary
This summary is machine-generated.

This study reveals genotype-phenotype correlations in Phosphomannomutase 2-Congenital Disorders of Glycosylation (PMM2-CDG). Specific PMM2 gene variants influence disease severity, offering better prognostic insights.

Keywords:
NPCRSPMM2-CDGcongenital disorders of glycosylationgenotypemutation

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Area of Science:

  • Biochemistry
  • Genetics
  • Rare Diseases

Background:

  • PMM2-CDG is a rare genetic disorder characterized by hypoglycosylation of proteins.
  • No clear genotype-phenotype correlations have been established for PMM2-CDG.
  • Understanding these correlations is crucial for predicting disease progression and patient outcomes.

Purpose of the Study:

  • To investigate genotype-phenotype correlations in PMM2-CDG patients.
  • To determine the impact of specific PMM2 variants on disease severity.
  • To establish a molecular basis for phenotypic prognosis in PMM2-CDG.

Main Methods:

  • Retrospective cohort study of 26 PMM2-CDG patients.
  • Analysis of patient genotypes and phenotypes.
  • Disease severity assessed using the Nijmegen Pediatric CDG Rating Score (NPCRS).
  • Statistical analysis using non-parametric and Chi-Square tests.

Main Results:

  • Seventeen different pathogenic variants were analyzed.
  • Variants in the stabilization/folding domain, like p.Cys241Ser, correlated with significantly lower NPCRS scores and milder phenotypes.
  • Variants in the dimerization domain, such as p.Pro113Leu and p.Phe119Leu, were associated with significantly higher NPCRS scores and more severe clinical courses.
  • Variants with zero enzyme activity did not significantly impact the NPCRS.

Conclusions:

  • Specific PMM2 variants significantly influence PMM2-CDG phenotype and severity.
  • Genotype-based analysis provides valuable insights into disease prognosis.
  • This study establishes a foundation for predicting PMM2-CDG clinical outcomes based on molecular findings.