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Updated: Jan 15, 2026

Determination of Glucan Chain Length Distribution of Glycogen Using the Fluorophore-Assisted Carbohydrate Electrophoresis FACE Method
Published on: March 31, 2022
Growth impairment in glycogen storage disease type I versus types III/VI/IX: a cross-sectional study
Xiaohui Wu1, Yueyu Sun2, Min Yang3
1Department of Pediatrics, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China.
Background:
Growth retardation is common in glycogen storage disease (GSD), though the relative contributions of hormonal and metabolic factors remain unclear. We compared clinical and biochemical features between GSD I and non-GSD I patients and identified independent predictors of height standard deviation score (SDS).
Methods:
Thirty-eight children with GSD (24 with GSD I; 14 with GSD III/VI/IX; mean age: 7.5 years) underwent evaluation of height SDS, BMI SDS, IGF1 SDS, and metabolic parameters. After excluding three patients with inflammatory bowel disease (final n = 35), multiple regression was used to identify factors associated with height SDS. In GSD I (n = 24), Lasso regression selected variables, and 1,000 bootstrap resamples assessed coefficient stability.
Results:
GSD I patients had lower height SDS (-2.30 vs. - 1.17; p = 0.021) and higher lactate (3.94 vs. 1.48 mmol/L; p < 0.001), uric acid (431.04 vs. 283.79µmol/L; p < 0.001) and triglyceride levels (2.38 vs. 1.29 mmol/L, p = 0.002) compared to non-GSD I. In combined-cohort regression, lactate was the only independent negative predictor of height SDS (p = 0.011); glucose levels and IGF1 SDS did not reach statistical significance. In GSD I, Lasso retained lactate (β = - 0.682), glucose (β = - 0.625), and IGF1 SDS (β = 0.524), and bootstrap validation showed only IGF1 SDS remained consistently significant.
Conclusions:
Hyperlactatemia is significant predictor of growth impairment in GSD, while IGF1 is a stable predictor in GSD I. These findings highlight metabolic and hormonal targets for future hypothesis-driven research in this population.
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