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Pediatric neurology

September 23, 2026 · via Europe PMC

Multisystemic Clues and Diagnostic Gaps: A Comparative Analysis of Pediatric Congenital Disorders of Glycosylation Patients.

Gokalp S, Akar HT, Aktasoglu EO, Basan H, Sezer A.

Journal ArticleAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

In a small pediatric series, congenital disorders of glycosylation were multisystemic and a normal transferrin test did not rule them out.

What was studied

A retrospective review of nine children with CDG at one tertiary center, with clinical, biochemical, neuroimaging and genetic data.

Key findings

  • Common features were hypotonia, global developmental delay, epilepsy and abnormal brain MRI such as cerebral atrophy.
  • Transferrin isoelectric focusing was abnormal in five patients and normal in four with pathogenic variants.
  • Rare subtypes included GALNT2-CDG, B4GALT1-CDG and ST3GAL5-CDG.

Clinical relevance

Pediatricians and metabolic or neurology specialists evaluating unexplained neurodevelopmental disease may need molecular testing even when biochemical screening is normal.

Who should care

Pediatric Neurology

Limitations

With only nine patients from a single center, the findings are descriptive and cannot establish frequencies.

Genetic testing may be considered when CDG is suspected despite normal transferrin results.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Background

Congenital disorders of glycosylation (CDG) comprise a diverse group of rare inherited metabolic diseases caused by defects in glycan biosynthesis and processing. Since glycoconjugates play a critical role in development and cellular integrity, disruptions in glycosylation can result in a wide range of multisystemic symptoms, often with prominent neurological involvement. Despite their clinical relevance, many CDG cases remain underdiagnosed due to the limited sensitivity of conventional biochemical tests. This study aims to further characterize the clinical, radiologic, and genetic findings.

Methods

This study retrospectively analyzed nine pediatric patients diagnosed with CDG at a tertiary center. Clinical features, biochemical investigations, neuroimaging findings, and molecular genetic results were reviewed. Genetic confirmation was obtained using targeted next-generation sequencing or whole-exome sequencing.

Results

The cohort revealed wide phenotypic variability, with predominant features including hypotonia, global developmental delay, epilepsy, and abnormal brain magnetic resonance imaging findings such as cerebral atrophy and white matter abnormalities. While transferrin isoelectric focusing revealed abnormal patterns in five patients, four patients had normal transferrin isoelectric focusing results despite harboring pathogenic variants. Several rare CDG subtypes were identified, including GALNT2-CDG, B4GALT1-CDG, and ST3GAL5-CDG.

Conclusions

Our study underscores the importance of considering CDG in the differential diagnosis of multisystemic neurodevelopmental disorders. It also highlights the limitations of regular biochemical screening in excluding CDG, emphasizing the essential role of early implementation of molecular testing. Our findings not only contribute to the expanding spectrum of CDG presentations in pediatric populations but also provide valuable insights into novel genotype-phenotype correlations.

DOI

10.1016/j.pediatrneurol.2026.09.015

PMID

42854636

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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