Classical galactosemia (CG) is one of the more frequent inborn errors of metabolism affecting approximately 1:40.000 people. Despite a life-saving galactose-restricted diet, patients develop highly variable long-term complications including intellectual disability and movement disorders. The pathophysiology of these complications is still poorly understood and development of new therapies is hampered by a lack of valid prognostic biomarkers. Multi-omics approaches may discover new biomarkers and improve prediction of patient outcome. In the current study, (semi-)targeted mass-spectrometry based metabolomics and lipidomics were performed in erythrocytes of 40 patients with both classical and variant phenotypes and 39 controls. Lipidomics did not show any significant changes or deficiencies. The metabolomics analysis revealed that CG does not only compromise the Leloir pathway, but also involves other metabolic pathways including glycolysis, the pentose phosphate pathway, and nucleotide metabolism in the erythrocyte. Moreover, the energy status of the cell appears to be compromised, with significantly decreased levels of ATP and ADP. This possibly is the consequence of two different mechanisms: impaired formation of ATP from ADP possibly due to reduced flux though the glycolytic pathway and trapping of phosphate in galactose-1-phosphate (Gal-1P) which accumulates in CG. Our findings are in line with the current notion that the accumulation of Gal-1P plays a key role in the pathophysiology of CG not only by depletion of intracellular phosphate levels but also by decreasing metabolite abundance downstream in the glycolytic pathway and affecting other pathways. New therapeutic options for CG could be directed towards the restoration of intracellular phosphate homeostasis.
Original languageEnglish
Pages (from-to)1094-1105
Number of pages12
JournalJournal of Inherited Metabolic Disease
Issue number6
Early online date2022
Publication statusPublished - Nov 2022


  • GALT-deficiency
  • galactose-1-phosphate
  • galactosemia
  • lipidomics
  • metabolomics
  • multi-omics

Cite this