Evidence map›Paper›PMID 41368113›Full record

ReviewWorld journal of hepatology2025

Liver as a metabolic sensor in gestational diabetes: Implications for offspring's liver and diabetes risk.

Mona Mohamed Ibrahim Abdalla, Mohammed Ismail-Khan

Abstract readReview
In one paragraph

Review in World journal of hepatology, 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. Article
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

2 authors.

Mona Mohamed Ibrahim AbdallaDepartment of Human Biology, School of Medicine, International Medical University, Bukit Jalil 57000, Kuala Lumpur, Malaysia. monamohamed@imu.edu.my.
Mohammed Ismail-KhanDepartment of Gynaecological Oncology, Northern Gynaecological Oncology Centre, Queen Elizabeth Hospital, Gateshead NE9 6SX, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gestational diabetes mellitus (GDM) is increasingly recognized not only for its immediate obstetric complications but also for its long-term metabolic consequences in both mothers and their offspring. Traditionally, research has emphasized the roles of pancreatic β-cell dysfunction and placental dysregulation in GDM. However, emerging evidence highlights the maternal liver as a central metabolic hub during pregnancy coordinating glucose, lipid, and hormonal adaptations essential for fetal development. This review synthesizes current findings on how GDM disrupts the maternal liver's adaptive roles, transforming it from a metabolic coordinator into a source of maladaptive endocrine, inflammatory, and nutrient signals. It outlines key mechanistic pathways through which maternal hepatic dysfunction may increase offspring susceptibility to non-alcoholic fatty liver disease and type 2 diabetes mellitus. These include hepatokine dysregulation, altered lipid metabolism, impaired insulin signaling, inflammatory and oxidative stress pathways, and epigenetic and transcriptomic reprogramming. In addition, it explores novel axes such as the gut-liver-placenta interplay, bile acid signaling disruptions, endoplasmic reticulum stress responses, and extracellular vesicle-mediated communication. By reframing the maternal liver's role in GDM pathophysiology, this review identifies critical windows for early clinical intervention and highlights the potential for liver-focused strategies to prevent the intergenerational transmission of metabolic disease.

Indexed as

Epigenetic reprogrammingFetal metabolic imprintingHepatokinesInsulin resistance in pregnancyIntrauterine exposureLiverMetabolic sensor

Identifiers

PMID41368113
PMCPMC12683350

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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.