PCSK9 SNP rs11591147 is associated with low cholesterol levels but not with cognitive performance or noncardiovascular clinical events in an elderly population
Bibliographic record
Abstract
Proprotein convertase subtilisin-like/kexin type 9 (PCSK9) is a protein involved in LDL-cholesterol metabolism. The single-nucleotide polymorphism (SNP) rs11591147 has been associated with lower LDL-cholesterol and a lower risk of coronary heart disease. Because PCSK9 has high affinity to the LDL receptor, inhibiting PCSK9 is a testable therapeutic target for lipid-lowering therapy. Currently, several approaches to inhibit PCSK9 are under development, but it is unknown what the effects of those inhibitors will be on cognition or noncardiovascular clinical events. In this study, we assessed the association between rs11591147 and cognitive performance, activities of daily living (ADL), and noncardiovascular clinical events within 5,777 participants of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). Rs11591147 was associated with 10% to 16% lower LDL cholesterol levels (P = 3.62 × 10(-12)), but was not associated with cognitive performance, ADL, or noncardiovascular clinical events in the PROSPER study. Our findings suggest that lower cholesterol levels due to genetic variation in the PCSK9 gene are not associated with cognitive performance, functional status, or noncardiovascular clinical events.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".