PCSK9 Variants, Low-Density Lipoprotein Cholesterol, and Neurocognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Despite concerns about adverse neurocognitive events raised by prior trials, pharmacological PCSK9 (proprotein convertase subtilisin/kexin type-9) inhibition was not associated with neurocognitive effects in a recent phase 3 randomized trial. PCSK9 loss-of-function (LOF) variants that result in lifelong exposure to lower levels of low-density lipoprotein cholesterol can provide information on the potential long-term effects of lower low-density lipoprotein cholesterol on neurocognitive impairment and decline. METHODS: We investigated the association between PCSK9 LOF variants and neurocognitive impairment and decline among black REGARDS study (Reasons for Geographic and Racial Differences in Stroke) participants with (n=241) and without (n=10 454) C697X or Y142X LOF variants. Neurocognitive tests included the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery (Word List Learning, World List Delayed Recall, Semantic Animal Fluency) and Six-Item Screener (SIS) assessments, administered longitudinally during follow-up. Neurocognitive impairment was defined as a score ≥1.5 SD below age, sex, and education-based stratum-specific means on 2 or 3 CERAD assessments or, separately, a score <5 on any SIS assessment at baseline or during follow-up. Neurocognitive decline was assessed using standardized continuous scores on individual neurocognitive tests. RESULTS: >0.10). Odds ratios for neurocognitive impairment per 20 mg/dL low-density lipoprotein cholesterol decrements were 1.02 (95% CI, 0.96-1.08) and 0.99 (95% CI, 0.95-1.02) for the CERAD and SIS definitions of impairment, respectively. CONCLUSIONS: These results suggest that lifelong exposure to low PCSK9 levels and cumulative exposure to lower levels of low-density lipoprotein cholesterol are not associated with neurocognitive effects in blacks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".