Genetic Diseases of Fucosylation: Insights from Model Organisms
Bibliographic record
Abstract
Fucosylation plays a fundamental role in maintaining cellular functions and biological processes across all animals. As a form of glycosylation, it involves the biochemical addition of fucose, a six-carbon monosaccharide, to biological molecules like lipids, proteins, and glycan chains. This modification is essential for optimizing cellular interactions required for receptor-ligand binding, cell adhesion, immune responses, and development. Disruptions in cellular fucose synthesis or in the mechanisms enabling its transfer to other molecules have been linked to human disease. Inherited defects in the fucosylation pathway are rare, with about thirty patients described. Through genome-wide association studies (GWAS), variants in fucosylation pathway genes have been associated with complex diseases such as glaucoma and stroke, and somatic mutations are often found in cancers. Recent studies have applied targeted genetic animal models to elucidate the mechanisms through which disruptions in fucosylation contribute to disease pathogenesis and progression. Key focus areas include GDP-fucose synthesis through de novo or salvage pathways, GDP-fucose transport into the Golgi and endoplasmic reticulum (ER), and its transfer by fucosyltransferases (FUTs) or protein O-fucosyltransferases (POFUTs) onto acceptor molecules. Loss or gain of function fucosylation gene mutations in animal models such as mice, zebrafish, and invertebrates have provided insights into some fucosylation disease pathogenesis. This review aims to bring together these findings, summarizing key insights from existing animal studies to possibly infer fucosylation disease mechanisms in humans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".