One-Year Effects of High-Intensity Statin on Bioactive Lipids: Findings From the JUPITER Trial
Bibliographic record
Abstract
BACKGROUND: Statin effects extend beyond low-density lipoprotein cholesterol reduction, potentially modulating the metabolism of bioactive lipids (BALs), crucial for biological signaling and inflammation. These bioactive metabolites may serve as metabolic footprints, helping uncover underlying processes linked to pleiotropic effects of statins and yielding a better understanding of their cardioprotective properties. This study aimed to investigate the impact of high-intensity statin therapy versus placebo on plasma BALs in the JUPITER trial (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin; NCT00239681), a randomized primary prevention trial involving individuals with low-density lipoprotein cholesterol <130 mg/dL and high-sensitivity C-reactive protein ≥2 mg/L. METHODS: (n=409). The effect of randomized allocation of rosuvastatin 20 mg versus placebo on BALs was examined by fitting a linear regression with delta values (∆=year 1-baseline) adjusted for age and baseline levels of each feature. Significant associations in discovery were analyzed in the validation cohort. Multiple comparisons were adjusted using 2-stage overall false discovery rate. RESULTS: We identified 610 lipid features associated with statin randomization with significant replication (overall false discovery rate, <0.05), including 26 with annotations. Statin therapy significantly increased levels of 276 features, including BALs with anti-inflammatory activity and arterial vasodilation properties. Concurrently, 334 features were significantly lowered by statin therapy, including arachidonic acid and proinflammatory and proplatelet aggregation BALs. By contrast, statin therapy reduced an eicosapentaenoic acid-derived hydroxyeicosapentaenoic acid metabolite, which may be related to impaired glucose metabolism. Additionally, we observed sex-related differences in 6 lipid metabolites and 6 unknown features. CONCLUSIONS: Statin allocation was significantly associated with upregulation of BALs with anti-inflammatory, antiplatelet aggregation and antioxidant properties and downregulation of BALs with proinflammatory and proplatelet aggregation activity, supporting the pleiotropic effects of statins beyond low-density lipoprotein cholesterol reduction.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".