Correction of Feline Lipoprotein Lipase Deficiency with Adeno-Associated Virus Serotype 1-Mediated Gene Transfer of the Lipoprotein Lipase S447X Beneficial Mutation
Bibliographic record
Abstract
Human lipoprotein lipase (hLPL) deficiency, for which there currently exists no adequate treatment, leads to excessive plasma triglycerides (TGs), recurrent abdominal pain, and life-threatening pancreatitis. We have shown that a single intramuscular administration of adeno-associated virus (AAV) serotype 1 vector, encoding the human LPL(S447X) variant, results in complete, long-term normalization of dyslipidemia in LPL(/) mice. As a prelude to gene therapy for human LPL deficiency, we tested the efficacy of AAV1-LPL(S447X) in LPL(/) cats, which demonstrate hypertriglyceridemia (plasma TGs, >10,000 mg/dl) and clinical symptoms similar to LPL deficiency in humans, including pancreatitis. Male LPL(/) cats were injected intramuscularly with saline or AAV1-LPL(S447X) (1 x 10(11)-1.7 x 10(12) genome copies [GC]/kg), combined with oral doses of cyclophosphamide (0-200 mg/m(2) per week) to inhibit an immune response against hLPL. Within 3-7 days after administration of >or=5 x 10(11) GC of AAV1-LPL(S447X) per kilogram, the visible plasma lipemia was completely resolved and plasma TG levels were reduced by >99% to normal levels (10-20 mg/dl); intermediate efficacy (95% reduction) was achieved with 1 x 10(11) GC/kg. Injection in two sites, greatly limiting the amount of transduced muscle, was sufficient to completely correct the dyslipidemia. By varying the dose per site, linear LPL expression was demonstrated over a wide range of local doses (4 x 10(10)-1 x 10(12) GC/site). However, efficacy was transient, because of an anti-hLPL immune response blunting LPL expression. The level and duration of efficacy were significantly improved with cyclophosphamide immunosuppression. We conclude that AAV1-mediated delivery of LPL(S447X) in muscle is an effective means to correct the hypertriglyceridemia associated with feline LPL deficiency.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".