Dual Mechanisms for the Fibrate-mediated Repression of Proprotein Convertase Subtilisin/Kexin Type 9
Bibliographic record
Abstract
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is associated with familial autosomal dominant hypercholesterolemia and is a natural inhibitor of the LDL receptor (LDLr). PCSK9 is degraded by other proprotein convertases: PC5/6A and furin. Both PCSK9 and the LDLr are up-regulated by the hypocholesterolemic statins. Thus, inhibitors or repressors of PCSK9 should amplify their beneficial effects. In the present study, we showed that PPARalpha activation counteracts PCSK9 induction by statins by repressing PCSK9 promoter activity and by increasing PC5/6A and furin expression. Quantification of mRNA and protein levels showed that various fibrates decreased PCSK9 and increased PC5/6A and furin expression. Fenofibric acid (FA) reduced PCSK9 protein content in immortalized human hepatocytes (IHH) as well as its cellular secretion. FA suppressed PCSK9 induction by statins or by the liver X receptor agonist TO901317. PCSK9 repression is occurring at the promoter level. We showed that PC5/6A and furin fibrate-mediated up-regulation is PPARalpha-dependent. As a functional test, we observed that FA increased by 30% the effect of pravastatin on the LDLr activity in vitro. In conclusion, fibrates simultaneously decreased PCSK9 expression while increasing PC5/6A and furin expression, indicating a broad action of PPARalpha activation in proprotein convertase-mediated lipid homeostasis. Moreover, this study validates the functional relevance of a combined therapy associating PCSK9 repressors and statins.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".