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Record W4310847620 · doi:10.1016/j.ebiom.2022.104392

Dissecting the multifaceted impact of statin use on fatty liver disease: a multidimensional study

2022· review· en· W4310847620 on OpenAlexaff
Ibrahim Ayada, Laurens A. van Kleef, Huai Zhang, Kuan Liu, Pengfei Li, Yasir J. Abozaid, Marla Lavrijsen, Harry L.A. Janssen, Luc J. W. van der Laan, Mohsen Ghanbari, Maikel P. Peppelenbosch, Ming‐Hua Zheng, Robert J. de Knegt, Qiuwei Pan

Bibliographic record

VenueEBioMedicine · 2022
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersStichting voor Lever- en Maag-Darm OnderzoekKWF KankerbestrijdingNederlandse Organisatie voor Wetenschappelijk OnderzoekMinisterie van Onderwijs, Cultuur en WetenschapErasmus Medisch CentrumMinisterie van Volksgezondheid, Welzijn en SportZonMwEuropean Commission
KeywordsFatty liverStatinHydroxymethylglutaryl-CoA Reductase InhibitorsDiseaseMedicineBioinformaticsComputational biologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.016
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.144
GPT teacher head0.425
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations107
Published2022
Admission routes1
Has abstractyes

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