Functional analysis of natural <scp>PCSK</scp>9 mutants in modern and archaic humans
Bibliographic record
Abstract
PCSK9 is the last member of the proprotein convertases (PCs) family and its gene is mutated in ~ 2% to 3% of individuals with familial hypercholesterolemia (FH). This protein enhances the degradation of the low-density lipoprotein receptor (LDLR) and hence increases the levels of circulating LDL-cholesterol (LDLc). Studies of the underlying mechanism(s) regulating the activity of different mutations in the PCSK9 gene are ongoing as they enhance our understanding of the biology and clinical relevance of PCSK9 and its partners. In an attempt to unravel the regulation of PCSK9 transcription and possibly identify mutation 'hot spot' regions with alterations in CpG methylation, we present for the first time the complete methylome profile of the PCSK9 gene in modern and archaic humanoids. Our data showed that the genomes of modern humans and archaic PCSK9 exhibit a similar methylation pattern. Next, we defined the mechanistic consequences of three PCSK9 natural mutations (PCSK9-R96L, -R105W, and -P174S) and one archaic Denisovan mutation (PCSK9-H449L) using various complementary cellular and in vitro binding assays. Our results showed that the PCSK9-H449L is a loss-of-function (LOF) mutation, likely due to its lower binding affinity to the LDLR. Similarly, PCSK9-R96L and -R105W are LOF mutations, even though they have been identified in FH patients. The PCSK9-R105W mutation leads to a significantly lower autocatalytic processing of proPCSK9. PCSK9-P174S resulted in a LOF in both extracellular and intracellular pathways. In conclusion, our extensive analyses revealed that all studied mutations result in PCSK9 LOF, via various mechanisms, leading to lower levels of LDLc.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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; a candidate call from one teacher head, 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".