Treatment With Simvastatin and Rifaximin Restores the Plasma Metabolomic Profile in Patients With Decompensated Cirrhosis
Bibliographic record
Abstract
Patients with decompensated cirrhosis, particularly those with acute-on-chronic liver failure (ACLF), show profound alterations in plasma metabolomics. The aim of this study was to investigate the effect of treatment with simvastatin and rifaximin on plasma metabolites of patients with decompensated cirrhosis, specifically on compounds characteristic of the ACLF plasma metabolomic profile. Two cohorts of patients were investigated. The first was a descriptive cohort of patients with decompensated cirrhosis (n = 42), with and without ACLF. The second was an intervention cohort from the LIVERHOPE-SAFETY randomized, double-blind, placebo-controlled trial treated with simvastatin 20 mg/day plus rifaximin 1,200 mg/day (n = 12) or matching placebo (n = 13) for 3 months. Plasma samples were analyzed using ultrahigh performance liquid chromatography-tandem mass spectroscopy for plasma metabolomics characterization. ACLF was characterized by intense proteolysis and lipid alterations, specifically in pathways associated with inflammation and mitochondrial dysfunction, such as the tryptophan-kynurenine and carnitine beta-oxidation pathways. An ACLF-specific signature was identified. Treatment with simvastatin and rifaximin was associated with changes in 161 of 985 metabolites in comparison to treatment with placebo. A remarkable reduction in levels of metabolites from the tryptophan-kynurenine and carnitine pathways was found. Notably, 18 of the 32 metabolites of the ACLF signature were affected by the treatment. Conclusion: Treatment with simvastatin and rifaximin modulates some of the pathways that appear to be key in ACLF development. This study unveils some of the mechanisms involved in the effects of treatment with simvastatin and rifaximin in decompensated cirrhosis and sets the stage for the use of metabolomics to investigate new targeted therapies in cirrhosis to prevent ACLF development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".