Evidence map›Paper›PMID 41823829›Full record

ReviewBiology2026

Autoimmune Hepatitis: A Review of Molecular Mechanisms and Research Gaps in African Populations.

Caitlin Wheeler, Janine Scholefield, Tracey Hurrell, Jerolen Naidoo

Abstract readReview
In one paragraph

Review in Biology, 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

4 authors.

Caitlin WheelerBioengineering and Integrated Genomics Group, Future Production Chemicals Cluster, Council for Scientific and Industrial Research, Pretoria 0184, South Africa.ORCID 0000-0002-0604-3621
Janine ScholefieldBioengineering and Integrated Genomics Group, Future Production Chemicals Cluster, Council for Scientific and Industrial Research, Pretoria 0184, South Africa.ORCID 0000-0001-9610-3976
Tracey HurrellBioengineering and Integrated Genomics Group, Future Production Chemicals Cluster, Council for Scientific and Industrial Research, Pretoria 0184, South Africa.ORCID 0000-0001-5548-918X
Jerolen NaidooBioengineering and Integrated Genomics Group, Future Production Chemicals Cluster, Council for Scientific and Industrial Research, Pretoria 0184, South Africa.ORCID 0000-0002-4408-9161

Funding

National Research Foundation CSUR230509103995
6 · The paper itself

Abstract

Autoimmune hepatitis (AIH) is an inflammatory liver disease characterised by immune-mediated hepatic injury, often leading to liver failure. The underlying molecular mechanisms of AIH remain poorly elucidated, hindering diagnostic and therapeutic advances. This review overviews the current understanding of AIH pathogenesis, which arises from a complex interplay of genetic predisposition, environmental triggers, and immune mechanisms (loss of tolerance, regulatory T cell dysfunction). Furthermore, current technologies and models which are being used to deconvolve the molecular profiles and pathophysiology of AIH are also discussed. Although AIH has a low reported global burden, AIH research is critically skewed towards European ancestry populations. This leaves a significant knowledge gap in diverse ancestry groups, such as those of African ancestry, where emerging research suggests that these patients may experience a more aggressive disease. Collectively, this highlights the need for research in underrepresented global populations to develop tailored diagnostics and effective targeted treatments.

Indexed as

Africaautoimmune hepatitisautoimmunitymolecular mechanismspathogenesis

Identifiers

PMID41823829
PMCPMC12984650

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.