Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9): Lessons Learned from Patients with Hypercholesterolemia
Bibliographic record
Abstract
BACKGROUND: Identification of the proprotein convertase subtilisin/kexin type 9 (PCSK9) as the third gene causing familial hypercholesterolemia (FH) and understanding its complex biology has led to the discovery of a novel class of therapeutic agents. CONTENT: PCSK9 undergoes autocatalytic cleavage in the endoplasmic reticulum and enters the secretory pathway. The PCSK9 gene is under the regulatory control of sterol receptor binding proteins 1 and 2. Statins increase PCSK9 and this may modulate the response to this class of medications. In plasma, PCSK9 binds to the epidermal growth factor-like domain of the LDL receptor (LDL-R) on the cell and, once incorporated in the late endosomal pathway, directs the LDL-R toward lysosomal degradation rather than recycling to the plasma membrane. Thus, gain-of-function PCSK9 mutations lead to an FH phenotype, whereas loss-of-function mutations are associated with increased LDL-R-mediated endocytosis of LDL particles and lower LDL cholesterol in plasma. Inhibition of PCSK9 is thus an attractive therapeutic target. Presently, this is achieved by using monoclonal antibodies for allosteric inhibition of the PCSK9-LDL-R interaction. Phase 2 and 3 clinical trials in patients with moderate and severe hypercholesterolemia (including FH) show that this approach is safe and highly efficacious to lower LDL-C and lipoprotein(a). SUMMARY: PCSK9 has other biological roles observed in vitro and in animal studies, including viral entry into the cell, insulin resistance, and hepatic tissue repair. Given the potential number of humans exposed to this novel class of medications, careful evaluation of clinical trial results is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".