Novel Loss-of-Function PCSK9 Variant Is Associated with Low Plasma LDL Cholesterol in a French-Canadian Family and with Impaired Processing and Secretion in Cell Culture
Bibliographic record
Abstract
BACKGROUND: PCSK9 (proprotein convertase subtilisin/kexin type 9) is a polymorphic gene whose protein product regulates plasma LDL cholesterol (LDLC) concentrations by shuttling liver LDL receptors (LDLRs) for degradation. PCSK9 variants that cause a gain or loss of PCSK9 function are associated with hyper- or hypocholesterolemia, which increases or reduces the risk of cardiovascular disease, respectively. We studied the clinical and molecular characteristics of a novel PCSK9 loss-of-function sequence variant in a white French-Canadian family. METHODS: In vivo plasma and ex vivo secreted PCSK9 concentrations were measured with a commercial ELISA. We sequenced the PCSK9 exons for 15 members of a family, the proband of which exhibited very low plasma PCSK9 and LDLC concentrations. We then conducted a structure/function analysis of the novel PCSK9 variant in cell culture to identify its phenotypic basis. RESULTS: We identified a PCSK9 sequence variant in the French-Canadian family that produced the PCSK9 Q152H substitution. Family members carrying this variant had mean decreases in circulating PCSK9 and LDLC concentrations of 79% and 48%, respectively, compared with unrelated noncarriers (n=210). In cell culture, the proPCSK9-Q152H variant did not undergo efficient autocatalytic cleavage and was not secreted. Cells transiently transfected with PCSK9-Q152H cDNA had LDLR concentrations that were significantly higher than those of cells overproducing wild-type PCSK9 (PCSK9-WT). Cotransfection of PCSK9-Q152H and PCSK9-WT cDNAs produced a 78% decrease in the secreted PCSK9-WT protein compared with control cells. CONCLUSIONS: Collectively, our results demonstrate that the PCSK9-Q152H variant markedly lowers plasma PCSK9 and LDLC concentrations in heterozygous carriers via decreased autocatalytic processing and secretion, and hence, inactivity on the LDLR.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".