Effect of Alipogene Tiparvovec (AAV1-LPL<sup>S447X</sup>) on Postprandial Chylomicron Metabolism in Lipoprotein Lipase-Deficient Patients
Bibliographic record
Abstract
BACKGROUND: Lipoprotein lipase-deficient (LPLD) individuals display marked chylomicronemia and hypertriglyceridemia associated with increased pancreatitis risk. The aim of this study was to determine the effect of i.m. administration of an adeno-associated viral vector (AAV1) for expression of LPL(S447X) in muscle (alipogene tiparvovec, AAV1-LPL(S447X)) on postprandial chylomicron metabolism and on nonesterified fatty acid (NEFA) and glycerol metabolism in LPLD individuals. METHODOLOGY: In an open-label clinical trial (CT-AMT-011-02), LPLD subjects were administered alipogene tiparvovec at a dose of 1 × 10(12) genome copies per kilogram. Two weeks before and 14 wk after administration, chylomicron metabolism and plasma palmitate and glycerol appearance rates were determined after ingestion of a low-fat meal containing (3)H-palmitate, combined with (continuous) iv infusion of [U-(13)C]palmitate and [1,1,2,3,3-(2)H]glycerol. PRINCIPAL FINDINGS: After administration of alipogene tiparvovec, the triglyceride (TG) content of the chylomicron fraction and the chylomicron-TG/total plasma TG ratio were reduced throughout the postprandial period. The postprandial peak chylomicron (3)H level and chylomicron (3)H area under the curve were greatly reduced (by 79 and 93%, 6 and 24 h after the test meal, respectively). There were no significant changes in plasma NEFA and glycerol appearance rates. Plasma glucose, insulin, and C-peptide also did not change. CONCLUSIONS/SIGNIFICANCE: Intramuscular administration of alipogene tiparvovec resulted in a significant improvement of postprandial chylomicron metabolism in LPLD patients, without inducing large postprandial NEFA spillover.
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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) | 0.001 | 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 | 0.001 | 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".