Protease-dependent defects in N-cadherin processing drive PMM2-CDG pathogenesis

Tracer metabolomics reveals the role of aldose reductase in glycosylation

Abnormal polyol metabolism is predominantly associated with diabetes, where excess glucose is converted to sorbitol by aldose reductase (AR). Recently, abnormal polyol metabolism has been implicated in phosphomannomutase 2 congenital disorder of glycosylation (PMM2-CDG) and an AR inhibitor, epalrestat, proposed as a potential therapy. Considering that the PMM2 enzyme is not directly involved in polyol metabolism, the increased polyol production and epalrestat's therapeutic mechanism in PMM2-CDG remained elusive. PMM2-CDG, caused by PMM2 deficiency, presents with depleted GDP-mannose and abnormal glycosylation. Here, we show that, apart from glycosylation abnormalities, PMM2 deficiency affects intracellular glucose flux, resulting in polyol increase. Targeting AR with epalrestat decreases polyols and increases GDP-mannose both in patient-derived fibroblasts and in pmm2 mutant zebrafish. Using tracer studies, we demonstrate that AR inhibition diverts glucose flux away from polyol production toward the synthesis of sugar nucleotides, and ultimately glycosylation. Finally, PMM2-CDG individuals treated with epalrestat show a clinical and biochemical improvement.

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG)

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders’ views on AI for therapy discovery in CDG.