Dissecting the multifaceted impact of statin use on fatty liver disease: a multidimensional study
Bibliographic record
Abstract
BACKGROUND: Statin use could benefit patients with non-alcoholic fatty liver disease (NAFLD), but the evidence is segmented and inconclusive. This multidimensional study comprehensively investigated the potential benefits and mechanism-of-action of statins in NAFLD. METHODS: A cross-sectional investigation was performed within the Rotterdam Study (general population; n = 4.576) and the PERSONS cohort (biopsy-proven NAFLD patients; n = 569). Exclusion criteria were secondary causes for steatosis and insufficient data on alcohol, dyslipidemia or statin use. Associations of statin use with NAFLD (among entire general population), fibrosis and NASH (among NAFLD individuals and patients) were quantified. These results were pooled with available literature in meta-analysis. Last, we assessed statins' anti-lipid and anti-inflammatory effects in 3D cultured human liver organoids and THP-1 macrophages, respectively. FINDINGS: Statin use was inversely associated with NAFLD in the Rotterdam study compared to participants with untreated dyslipidemia. In the PERSONS cohort, statin use was inversely associated with NASH, but not with fibrosis. The meta-analysis included 7 studies and indicated a not significant inverse association for statin use with NAFLD (pooled-Odds Ratio: 0.69, 95% Confidence Interval: 0.46-1.01) and significant inverse associations with NASH (pooled-OR: 0.59, 95% CI: 0.44-0.79) and fibrosis (pooled-OR: 0.48, 95% CI: 0.33-0.70). In vitro, statins significantly reduced lipid droplet accumulation in human liver organoids and downregulated expression of pro-inflammatory cytokines in macrophages. INTERPRETATION: Pooled results demonstrated that statin use was associated with a lower prevalence of NASH and fibrosis and might prevent NAFLD. This may be partially attributed to the anti-lipid and anti-inflammatory characteristics of statins. Given their under-prescription, adequate prescription of statins may limit the disease burden of NAFLD. FUNDING: ZonMw, KWF, NWO, SLO, DGXII, RIDE, National and regional government, Erasmus MC and Erasmus University.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.016 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".