Long-Term Correction of Murine Lipoprotein Lipase Deficiency with AAV1-Mediated Gene Transfer of the Naturally Occurring LPL <sup>S447X</sup> Beneficial Mutation
Bibliographic record
Abstract
Human lipoprotein lipase (LPL) deficiency causes profound hypertriglyceridemia and life-threatening pancreatitis. We recently developed an adult murine model for LPL deficiency: LPL -/- mice display grossly elevated plasma triglyceride (TG) levels (>200-fold) and very low high-density lipoprotein cholesterol (HDL-C < 10% of normal). We used this animal model to test the efficacy of adeno-associated virus-mediated expression of hLPL(S447X) (AAV1-LPL(S447X)) in muscle for the treatment of LPL deficiency. Intramuscular administration of AAV1-LPL(S447X) resulted in dose-dependent expression of hLPL protein and LPL activity (up to 33% of normal murine levels) in postheparin plasma. Remarkably, visible hyperlipidemia was resolved within 1 week; plasma TG was reduced to near-normal levels (from 99.0 to 1.8 mmol/L), and plasma HDL-C was increased 6-fold (from 0.2 to 1.1 mmol/L). At 8 months after administration of AAV1-LPL(S447X), an intravenous lipid challenge showed efficient, near-normal clearance of plasma TG. Histologic analyses of injected muscle further indicated that abnormal muscle morphology observed in LPL -/- mice was reversed after treatment. Expression of therapeutic levels of LPL(S447X), and the subsequent beneficial effect on plasma lipid levels, has lasted for more than 1 year. We therefore conclude that AAV1-mediated transfer of LPL(S447X) into murine skeletal muscle results in long-term near-correction of dyslipidemia associated with LPL deficiency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".