Circulating Proprotein Convertase Subtilisin/Kexin 9 (PCSK9) Regulates VLDLR Protein and Triglyceride Accumulation in Visceral Adipose Tissue
Bibliographic record
Abstract
OBJECTIVE: Proprotein convertase subtilisin/kexin 9 (PCSK9) promotes the degradation of the low-density lipoprotein receptor (LDLR), and its gene is the third locus implicated in familial hypercholesterolemia. Herein, we investigated the role of PCSK9 in adipose tissue metabolism. METHODS AND RESULTS: At 6 months of age, Pcsk9(-/-) mice accumulated ≈80% more visceral adipose tissue than wild-type mice. This was associated with adipocyte hypertrophy and increased in vivo fatty acid uptake and ex vivo triglyceride synthesis. Moreover, adipocyte hypertrophy was also observed in Pcsk9(-/-) Ldlr(-/-) mice, indicating that the LDLR is not implicated. Rather, we show here by immunohistochemistry that Pcsk9(-/-) males and females exhibit 4- and ≈ 40-fold higher cell surface levels of very-low-density lipoprotein receptor (VLDLR) in perigonadal depots, respectively. Expression of PCSK9 in the liver of Pcsk9(-/-) females reestablished both circulating PCSK9 and normal VLDLR levels. In contrast, specific inactivation of PCSK9 in the liver of wild-type females led to ≈ 50-fold higher levels of perigonadal VLDLR. CONCLUSIONS: In vivo, endogenous PCSK9 regulates VLDLR protein levels in adipose tissue. This regulation is achieved by circulating PCSK9 that originates entirely in the liver. PCSK9 is thus pivotal in fat metabolism: it maintains high circulating cholesterol levels via hepatic LDLR degradation, but it also limits visceral adipogenesis likely via adipose VLDLR regulation.
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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".