The Proprotein Convertase PCSK9 Induces the Degradation of Low Density Lipoprotein Receptor (LDLR) and Its Closest Family Members VLDLR and ApoER2
Bibliographic record
Abstract
The proprotein convertase PCSK9 gene is the third locus implicated in familial hypercholesterolemia, emphasizing its role in cardiovascular diseases. Loss of function mutations and gene disruption of PCSK9 resulted in a higher clearance of plasma low density lipoprotein cholesterol, likely due to a reduced degradation of the liver low density lipoprotein receptor (LDLR). In this study, we show that two of the closest family members to LDLR are also PCSK9 targets. These include the very low density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2) implicated in neuronal development and lipid metabolism. Our results show that wild type PCSK9 and more so its natural gain of function mutant D374Y can efficiently degrade the LDLR, VLDLR, and ApoER2 either following cellular co-expression or re-internalization of secreted human PCSK9. Such PCSK9-induced degradation does not require its catalytic activity. Membrane-bound PCSK9 chimeras enhanced the intracellular targeting of PCSK9 to late endosomes/lysosomes and resulted in a much more efficient degradation of the three receptors. We also demonstrate that the activity of PCSK9 and its binding affinity on VLDLR and ApoER2 does not depend on the presence of LDLR. Finally, in situ hybridization show close localization of PCSK9 mRNA expression to that of VLDLR in mouse postnatal day 1 cerebellum. Thus, this study demonstrates a more general effect of PCSK9 on the degradation of the LDLR family that emphasizes its major role in cholesterol and lipid homeostasis as well as brain development.
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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) | 0.001 | 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".