Evidence map›Paper›PMID 42528288›Full record

ReviewMediators of inflammation2026

Biomarkers From the Microbiome to Predict ALD Progression and Its Severity: A Comprehensive Review.

Suraj Mishra, Harshrajsinh Solanki, Palash Mandal

Abstract readReview
In one paragraph

Review in Mediators of inflammation, 2026. 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

3 authors.

Suraj MishraDepartment of Biological Sciences, P.D. Patel Institute of Applied Sciences, Charotar University of Science and Technology, Changa, Gujarat, India, charusat.ac.in.ORCID https://orcid.org/0009-0004-1031-211X
Harshrajsinh SolankiDepartment of Biological Sciences, P.D. Patel Institute of Applied Sciences, Charotar University of Science and Technology, Changa, Gujarat, India, charusat.ac.in.ORCID https://orcid.org/0009-0007-6616-8673
Palash MandalDepartment of Biological Sciences, P.D. Patel Institute of Applied Sciences, Charotar University of Science and Technology, Changa, Gujarat, India, charusat.ac.in.ORCID https://orcid.org/0000-0001-6612-3773

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alcohol use is a major global health issue, causing about 3.3 million deaths each year, or roughly 5.9% of all deaths worldwide. Alcohol-related liver disease develops in stages: steatosis, steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. If alcohol consumption is discontinued at early stages, alcohol-related fatty liver disease can be reversed; however, continued exposure leads to progressive liver injury and increased mortality risk. Current diagnostic tools lack sufficient sensitivity and specificity to detect early-stage disease or accurately assess disease progression. This highlights the need for reliable and mechanistically relevant biomarkers for early diagnosis and staging. This review examines alterations in gut microbiota across different stages of alcohol-associated liver disease and evaluates gut microbiota-associated biomarkers, including microbial metabolites, in the context of their potential diagnostic and prognostic utility. In addition, the review discusses the limitations of existing biomarkers and highlights the emerging role of microbiome-derived signals in reflecting disease mechanisms. These findings suggest that gut microbiota-related biomarkers may provide a promising but still evolving approach for improving early detection and understanding disease progression in alcohol-associated liver disease.

Indexed as

BiomarkersGastrointestinal MicrobiomeLiver Diseases, AlcoholicMicrobiotaAnimalsDisease ProgressionHumansBiomarkers

Identifiers

PMID42528288
PMCPMC13420271

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.