Evidence map›Paper›PMID 41262449›Full record

ReviewFrontiers in medicine2025

Metabolomics in autoimmune hepatitis: progress and perspectives.

Xiaotong Huang, Wenhui Mo, Xiaoning Wang

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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.

Xiaotong HuangBasic Medical College, Naval Medical University, Shanghai, China.
Wenhui MoFoshan Fosun Chancheng Hospital, Foshan, Guangdong, China.
Xiaoning WangInstitute of Interdisciplinary Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review summarizes recent advances in applying metabolomics to autoimmune hepatitis (AIH). AIH is a chronic liver disease characterized by immune-mediated hepatocellular injury, with complex pathogenesis involving genetic, immunological, and environmental factors. Metabolomics, a system-wide approach analyzing small molecule metabolites, offers potential in early diagnosis, prognosis, and therapeutic evaluation of AIH. Current studies identify alterations in amino acid, lipid, carbohydrate, and bile acid metabolism, as well as changes in the gut microbiome and specific metabolite markers that distinguish AIH from other liver diseases. Techniques such as liquid chromatography-mass spectrometry (LC-MS), and bioinformatics facilitate biomarker discovery and enhance understanding of disease mechanisms. Despite challenges such as standardization and data integration, metabolomics holds promise for developing personalized treatment strategies and advancing disease management. Future prospects include combining multi-omics approaches, large-scale cohort studies, and artificial intelligence (AI)-based data analysis to deepen insights into AIH pathology and improve clinical outcomes.

Indexed as

artificial intelligenceautoimmune hepatitisdiagnosismetabolomicsmicrobiome

Identifiers

PMID41262449
PMCPMC12623311

What OpenQuestion holds

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Registered trials

None linked

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.