Genetic ablation of acid ceramidase in Krabbe disease confirms the psychosine hypothesis and identifies a new therapeutic target
Bibliographic record
Abstract
Infantile globoid cell leukodystrophy (GLD, Krabbe disease) is a fatal demyelinating disorder caused by a deficiency in the lysosomal enzyme galactosylceramidase (GALC). GALC deficiency leads to the accumulation of the cytotoxic glycolipid, galactosylsphingosine (psychosine). Complementary evidence suggested that psychosine is synthesized via an anabolic pathway. Here, we show instead that psychosine is generated catabolically through the deacylation of galactosylceramide by acid ceramidase (ACDase). This reaction uncouples GALC deficiency from psychosine accumulation, allowing us to test the long-standing "psychosine hypothesis." We demonstrate that genetic loss of ACDase activity (Farber disease) in the GALC-deficient mouse model of human GLD (twitcher) eliminates psychosine accumulation and cures GLD. These data suggest that ACDase could be a target for substrate reduction therapy (SRT) in Krabbe patients. We show that pharmacological inhibition of ACDase activity with carmofur significantly decreases psychosine accumulation in cells from a Krabbe patient and prolongs the life span of the twitcher (Twi) mouse. Previous SRT experiments in the Twi mouse utilized l-cycloserine, which inhibits an enzyme several steps upstream of psychosine synthesis, thus altering the balance of other important lipids. Drugs that directly inhibit ACDase may have a more acceptable safety profile due to their mechanistic proximity to psychosine biogenesis. In total, these data clarify our understanding of psychosine synthesis, confirm the long-held psychosine hypothesis, and provide the impetus to discover safe and effective inhibitors of ACDase to treat Krabbe disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".