PCSK9 Induces CD36 Degradation and Affects Long-Chain Fatty Acid Uptake and Triglyceride Metabolism in Adipocytes and in Mouse Liver
Bibliographic record
Abstract
OBJECTIVE: Proprotein convertase subtilisin/kexin type 9 (PCSK9) promotes the degradation of the low-density lipoprotein receptor thereby elevating plasma low-density lipoprotein cholesterol levels and the risk of coronary heart disease. Thus, the use of PCSK9 inhibitors holds great promise to prevent heart disease. Previous work found that PCSK9 is involved in triglyceride metabolism, independently of its action on low-density lipoprotein receptor, and that other yet unidentified receptors could mediate this effect. Therefore, we assessed whether PCSK9 enhances the degradation of CD36, a major receptor involved in transport of long-chain fatty acids and triglyceride storage. APPROACH AND RESULTS: Overexpressed or recombinant PCSK9 induced CD36 degradation in cell lines and primary adipocytes and reduced the uptake of the palmitate analog Bodipy FL C16 and oxidized low-density lipoprotein in 3T3-L1 adipocytes and hepatic HepG2 cells, respectively. Surface plasmon resonance, coimmunoprecipitation, confocal immunofluorescence microscopy, and protein degradation pathway inhibitors revealed that PCSK9 directly interacts with CD36 and targets the receptor to lysosomes through a mechanism involving the proteasome. Importantly, the level of CD36 protein was increased by >3-fold upon small interfering RNA knockdown of endogenous PCSK9 in hepatic cells and similarly increased in the liver and visceral adipose tissue of Pcsk9(-/-) mice. In Pcsk9(-/-) mice, increased hepatic CD36 was correlated with an amplified uptake of fatty acid and accumulation of triglycerides and lipid droplets. CONCLUSIONS: Our results demonstrate an important role of PCSK9 in modulating the function of CD36 and triglyceride metabolism. PCSK9-mediated CD36 degradation may serve to limit fatty acid uptake and triglyceride accumulation in tissues, such as the liver.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".