Using chanarin-dorfman syndrome patient fibroblasts to explore disease mechanisms and new treatment avenues
Bibliographic record
Abstract
BACKGROUND: Chanarin-Dorfman syndrome (CDS) is a multisystemic autosomal recessive rare disorder. CDS is caused by variants in the abhydrolase domain containing 5 (ABHD5) encoding gene (CGI-58), which ultimately leads to excessive lipid storage, and therefore a high abundance of cellular lipid droplets (LDs). Although the molecular etiology of the disease was described many years ago, no treatment for CDS is currently available. RESULTS: To further characterize the molecular basis of the disease and to uncover new treatment avenues, we used skin fibroblasts originating from a young patient diagnosed with CDS due to a homozygous nonsense mutation. We show that dysfunctional ABHD5 does not only affect LDs, but also influences other metabolic-related organelles; the mitochondria and peroxisomes. Additionally, we found that expressing functional ABHD5 in CDS patient cells reduced LD number. Finally, we developed and applied a high content-based drug repurposing screen based on a collection of ∼2500 FDA approved compounds, yielding several compounds that affected LD total area and size. CONCLUSIONS: Our findings enhance the understanding of the dysfunction underlying CDS and propose new avenues for the treatment of CDS patients.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".