Pathogenic gain-of-function mutations in the prodomain and C-terminal domain of PCSK9 inhibit LDL binding
Bibliographic record
Abstract
Proprotein convertase subtilisin/kexin type-9 (PCSK9) is a secreted protein that binds and mediates endo-lysosomal degradation of low-density lipoprotein receptor (LDLR), limiting plasma clearance of cholesterol-rich LDL particles in liver. Gain-of-function (GOF) point mutations in PCSK9 are associated with familial hypercholesterolemia (FH). Approximately 30%–40% of PCSK9 in normolipidemic human plasma is bound to LDL particles. We previously reported that an R496W GOF mutation in a region of PCSK9 known as cysteine-histidine–rich domain module 1 (CM1) prevents LDL binding in vitro [Sarkar et al., J. Biol. Chem. 295 (8), 2285–2298 (2020)]. Herein, we identify additional GOF mutations that inhibit LDL association, localized either within CM1 or a surface-exposed region in the PCSK9 prodomain. Notably, LDL binding was nearly abolished by a prodomain S127R GOF mutation, one of the first PCSK9 mutations identified in FH patients. PCSK9 containing alanine or proline substitutions at amino acid position 127 were also defective for LDL binding. LDL inhibited cell surface LDLR binding and degradation induced by exogenous PCSK9-D374Y but had no effect on an S127R-D374Y double mutant form of PCSK9. These studies reveal that multiple FH-associated GOF mutations in two distinct regions of PCSK9 inhibit LDL binding, and that the Ser-127 residue in PCSK9 plays a critical role.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".