Effect of the DGAT1 inhibitor pradigastat on triglyceride and apoB48 levels in patients with familial chylomicronemia syndrome
Bibliographic record
Abstract
BACKGROUND: Familial chylomicronemia syndrome (FCS) is a rare lipid disease caused by complete lipoprotein lipase (LPL) deficiency resulting in fasting chylomicronemia and severe hypertriglyceridemia. Inhibition of diacylglycerol acyltransferase 1 (DGAT1), which mediates chylomicron triglyceride (TG) synthesis, is an attractive strategy to reduce TG levels in FCS. In this study we assessed the safety, tolerability and TG-lowering efficacy of the DGAT1 inhibitor pradigastat in patients with FCS. METHODS: Six FCS patients were enrolled in an open-label clinical study. Following a 1-week very low fat diet run-in period patients underwent baseline lipid assessments, including a low fat meal tolerance test. Patients then underwent three consecutive 21 day treatment periods (pradigastat at 20, 40 & 10 mg, respectively). Treatment periods were separated by washout periods of ≥4 weeks. Fasting TG levels were assessed weekly through the treatment periods. Postprandial TGs, ApoB48 and lipoprotein lipid content were also monitored. RESULTS: Following once daily oral dosing, steady-state exposure was reached by Day 14. There was an approximately dose proportional increase in pradigastat exposure at studied doses. Pradigastat was associated with a 41% (20 mg) and 70% (40 mg) reduction in fasting triglyceride over 21 days of treatment. The reduction in fasting TG was almost entirely accounted for by a reduction in chylomicron TG. Pradigastat treatment also led to substantial reductions in postprandial TG as well as apo48 (both fasting and postprandial). Pradigastat was safe and well tolerated, with only mild, transient gastrointestinal adverse events. CONCLUSION: The novel DGAT1 inhibitor pradigastat substantially reduces plasma TG levels in FCS patients, and may be a promising new treatment for this orphan disease. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01146522 .
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".