Decreased APOE-containing HDL subfractions and cholesterol efflux capacity of serum in mice lacking Pcsk9
Bibliographic record
Abstract
BACKGROUND: Studies in animals showed that PCSK9 is involved in HDL metabolism. We investigated the molecular mechanism by which PCSK9 regulates HDL cholesterol concentration and also whether Pcsk9 inactivation might affect cholesterol efflux capacity of serum and atherosclerotic fatty streak volume. METHODS: Mass spectrometry and western blot were used to analyze the level of apolipoprotein E (APOE) and A1 (APOA1). A mouse model overexpressing human LDLR was used to test the effect of high levels of liver LDLR on the concentration of HDL cholesterol and APOE-containing HDL subfractions. Pcsk9 knockout males lacking LDLR and APOE were used to test whether LDLR and APOE are necessary for PCSK9-mediated HDL cholesterol regulation. We also investigated the effects of Pcsk9 inactivation on cholesterol efflux capacity of serum using THP-1 and J774.A1 macrophage foam cells and atherosclerotic fatty streak volume in the aortic sinus of Pcsk9 knockout males fed an atherogenic diet. RESULTS: APOE and APOA1 were reduced in the same HDL subfractions of Pcsk9 knockout and human LDLR transgenic male mice. In Pcsk9/Ldlr double-knockout mice, HDL cholesterol concentration was lower than in Ldlr knockout mice and higher than in wild-type controls. In Pcsk9/Apoe double-knockout mice, HDL cholesterol concentration was similar to that of Apoe knockout males. In Pcsk9 knockout males, THP-1 macrophage cholesterol efflux capacity of serum was reduced and the fatty streak lesion volume was similar to wild-type controls. CONCLUSIONS: In mice, LDLR and APOE are important factors for PCSK9-mediated HDL regulation. Our data suggest that, although LDLR plays a major role in PCSK9-mediated regulation of HDL cholesterol concentration, it is not the only mechanism and that, regardless of mechanism, APOE is essential. Pcsk9 inactivation decreases the HDL cholesterol concentration and cholesterol efflux capacity in serum, but does not increase atherosclerotic fatty streak volume.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".