Evidence map›Paper›PMID 40803752›Full record

ArticleGut2025

Intrahepatic donor microbiota-based metataxonomic signature detected in organ preservation solution enables prediction of short-term liver transplant outcomes.

Fernando Lucas-Ruiz, Daniel Vidal-Correoso, Sandra V Mateo, María Magdalena de la Torre-Álamo, Marta Jover-Aguilar, Felipe Alconchel, Laura Martínez-Alarcón, Víctor Lopez-Lopez, Antonio Ríos-Zambudio, Pedro Cascales and 4 more

Abstract read
In one paragraph

Article in Gut, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Fernando Lucas-RuizBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain alberto.baroja@ffis.es fernando.lucas@um.es.
Daniel Vidal-Correoso *Biomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Sandra V Mateo *Biomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
María Magdalena de la Torre-ÁlamoBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Marta Jover-AguilarBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Felipe AlconchelBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Laura Martínez-AlarcónBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Víctor Lopez-LopezBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Antonio Ríos-ZambudioBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Pedro CascalesBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Pablo PelegrínBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Jose Antonio PonsBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Pablo RamírezBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain.
Alberto Baroja-MazoBiomedical Research Institute of Murcia (IMIB-Pascual Parrilla), Murcia, Spain alberto.baroja@ffis.es fernando.lucas@um.es.ORCID 0000-0001-5212-5006

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLiver transplantation (LT) remains hampered by post-transplant complications. While gut microbiota dysbiosis has been linked to transplant outcomes, the role of the intrahepatic graft's native microbiota remains unexplored.

objectiveTo characterise the microbial profile detected in organ preservation solution (OPS) and determine whether specific microbial taxa are associated with short-term clinical outcomes, and to develop predictive models for risk stratification.

designWe analysed the OPS microbiota-based metataxonomic signature from 110 LT donors (discovery cohort) and an independent validation cohort (n=29) using 16S rRNA sequencing. Microbial DNA signatures associated with clinical outcomes were identified through MaAsLin2-adjusted models, and relevant gene pathways were uncovered via data mining and enrichment analysis. Machine learning (ML) models were developed to predict outcomes based on microbial features, and host-microbiome interactions were validated through RNA sequencing (RNA-seq of matched liver biopsies).

resultsOPS-derived microbial DNA signature closely resembled liver/bile microbiomes (Proteobacteria-dominated). Specific genera (eg,

conclusionDonor intrahepatic microbial DNA signature predicts LT outcomes via immune-metabolic modulation. While causality requires further study, these findings position the graft microbiome as a novel biomarker and potential therapeutic target, paving the way for microbiome-informed precision care in transplantation.

Indexed as

Gastrointestinal MicrobiomeLiverLiver TransplantationOrgan Preservation SolutionsAdultFemaleHumansMaleMicrobiotaMiddle AgedRNA, Ribosomal, 16STissue DonorsOrgan Preservation SolutionsRNA, Ribosomal, 16SLIVER TRANSPLANTATIONMACHINE LEARNINGMICROBIOME

Identifiers

PMID40803752
PMCPMC12703288

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.