Evidence map›Paper›PMID 41226735›Full record

ReviewInternational journal of molecular sciences2025

Hepatic Zonation in MASLD: Old Question, New Challenge in the Era of Spatial Omics.

Erika Paolini, Miriam Longo, Marica Meroni, Paola Dongiovanni

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
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  8. Single Cell Analysis Reveals the Presence of Novel Intermediate Cells in Both Mice and Patients With Severe MASLD.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  9. Review
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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.

Erika PaoliniMedicine and Metabolic Diseases, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy.
Miriam LongoMedicine and Metabolic Diseases, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy.ORCID 0000-0002-9433-3492
Marica MeroniMedicine and Metabolic Diseases, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy.ORCID 0000-0002-4161-4178
Paola DongiovanniMedicine and Metabolic Diseases, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy.ORCID 0000-0003-4343-7213

Funding

Ministero della salute GR-2019-12370172Ministero della salute PNRR-MCNT2-2023-12378295Ministero della salute RF-2021-12374481
6 · The paper itself

Abstract

Hepatic zonation reflects the concept that hepatocytes and nonparenchymal cells (NPCs) perform distinct metabolic functions, depending on their spatial localization along the porto-central axis. The maintenance of this fine-tuned organization is essential for liver homeostasis, and its disruption may contribute to liver diseases, including metabolic dysfunction-associated steatotic liver disease (MASLD). Fat overload perturbs zonal gene signatures, lipid handling and oxygen/metabolite gradients progressively leading to steatohepatitis (MASH), fibrosis and HCC, conditions in which the hepatic architecture is lost. Traditional approaches have provided valuable insights into zonation, although they lack the spatial resolution and mask the heterogeneity of NPCs. Thus, the premise of this review is to discuss how spatial omics can redefine our understanding of hepatic zonation by integrating tissue mapping with metabolic organization, specifically focusing on MASLD. The advent of spatial omics accelerates knowledge regarding MASLD pathophysiology, providing more informative insights into transcriptional/translational/lipidomic/metabolomics zone-specific perturbations. Emerging spatial genomics and epigenomics applications further expand this scenario, allowing for the capture of chromatin remodeling in situ. The integration of these state-of-the-art approaches, coupled with artificial intelligence (AI)-based analyses, is promising in the clinic, as it may provide novel zonal prognostic biomarkers and pave the way for precision-medicine strategies targeting zonal switching.

Indexed as

Fatty LiverLiverMetabolomicsNon-alcoholic Fatty Liver DiseaseAnimalsGenomicsHepatocytesHumansLipid Metabolismliver zonationMASLDprecision medicinespatial omics

Identifiers

PMID41226735
PMCPMC12609896

What OpenQuestion holds

Textmetadata
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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.