Proprotein Convertase Subtilisin/Kexin Type 9 Interacts With Apolipoprotein B and Prevents Its Intracellular Degradation, Irrespective of the Low-Density Lipoprotein Receptor
Bibliographic record
Abstract
OBJECTIVE: proprotein convertase subtilisin/kexin type 9 (PCSK9) negatively regulates the low-density lipoprotein (LDL) receptor (LDLR) in hepatocytes and therefore plays an important role in controlling circulating levels of LDL-cholesterol. To date, the relationship between PCSK9 and metabolism of apolipoprotein B (apoB), the structural protein of LDL, has been controversial and remains to be clarified. METHODS AND RESULTS: We assessed the impact of PCSK9 overexpression (≈400-fold above baseline) on apoB synthesis and secretion in 3 mouse models: wild-type C57BL/6 mice and LDLR-null mice (Ldlr(-/-) and Ldlr(-/-)Apobec1(-/-)). Irrespective of LDLR expression, mice transduced with the PCSK9 gene invariably exhibited increased levels of plasma cholesterol, triacylglycerol, and apoB. Consistent with these findings, the levels of very-low-density lipoprotein and LDL were also increased whereas high-density lipoprotein levels were unchanged. Importantly, we demonstrated that endogenous PCSK9 interacted with apoB in hepatocytes. The PCSK9/apoB interaction resulted in increased production of apoB, possibly through the inhibition of intracellular apoB degradation via the autophagosome/lysosome pathway. CONCLUSIONS: We propose a new role for PCSK9 that involves shuttling between apoB and LDLR. The present study thus provides new insights into the action of PCSK9 in regulating apoB metabolism. Furthermore, our results indicate that targeting PCSK9 expression represents a new paradigm in therapeutic intervention against hyperlipidemia.
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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) | 0.000 | 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 | 0.000 | 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".