Evidence map›Paper›PMID 40458519›Full record

ArticleFrontiers in cellular and infection microbiology2025

Distinct gut microbiota and metabolomic profiles in HBV-related liver cirrhosis: insights into disease progression.

Ke Shi, Lina Sun, Ying Feng, Xianbo Wang

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

4 authors.

Ke ShiCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Lina SunCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Ying FengCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Xianbo WangCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatitis B virus (HBV)-related liver cirrhosis (HBV-LC) is a significant global health issue, affecting gut microbiota (GM) composition and metabolic processes. This study aimed to explore the associations between intestinal microbiota, metabolic profiles, and disease progression in patients with HBV-LC. Methods: Fecal samples were collected prospectively from 40 healthy controls (HC) and 83 HBV-LC patients between December 2022 and August 2023. Gut microbiota alterations at various stages of liver function were analyzed using 16S rRNA gene sequencing. Untargeted metabolomics was employed to identify potential biomarkers and metabolic pathways associated with early cirrhosis. Additionally, correlations between bacterial genera, inflammatory markers, and metabolites were investigated. Results: HBV-LC patients demonstrated a significant reduction in bacterial diversity and relative abundance compared to the HC group. Genera such as Conclusions: HBV-LC patients displayed significant alterations in gut microbiota and fecal metabolites, which correlated closely with disease severity and inflammatory status. These findings provide new insights into cirrhosis pathogenesis and suggest potential biomarkers for early diagnosis and disease monitoring.

Indexed as

Gastrointestinal MicrobiomeHepatitis BHepatitis B, ChronicLiver CirrhosisMetabolomeAdultBacteriaBiomarkersCase-Control StudiesDisease ProgressionFecesFemaleHepatitis B virusHumansMaleMetabolomicsBiomarkersRNA, Ribosomal, 16S16S rRNA sequencingcirrhosisgut microbiotahepatitis B virusmetabolomics

Identifiers

PMID40458519
PMCPMC12127420

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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.