Evidence map›Paper›PMID 40243942›Full record

ArticleInternational journal of molecular sciences2025

Identification of Novel Therapeutic Targets for MAFLD Based on Bioinformatics Analysis Combined with Mendelian Randomization.

Jialin Ren, Min Wu

Abstract read
In one paragraph

Article 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 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. Crosstalk between autophagy and ferroptosis in liver diseases (Review).International journal of molecular medicine · 2026
    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.

Jialin RenInstitute of Translational Medicine, Medical College, Yangzhou University, Yangzhou 225100, China.
Min WuInstitute of Translational Medicine, Medical College, Yangzhou University, Yangzhou 225100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic-associated fatty liver disease (MAFLD) is a chronic liver condition with limited therapeutic options. To identify novel drug targets, we integrated bioinformatics, Mendelian randomization (MR), and colocalization analyses. Using the Gene Expression Omnibus (GEO) database, we identified differentially expressed genes and constructed protein-protein interaction (PPI) networks, pinpointing 10 hub genes. MR and colocalization analyses revealed that Ubiquitin-like with PHD and ring finger domains 1 (UHRF1) is causally associated with MAFLD and driven by the same causal variant locus, suggesting its potential as a therapeutic target. Molecular docking identified disogenin as a candidate small-molecule drug targeting UHRF1. Drug affinity responsive target stability (DARTS) assays confirmed direct binding between UHRF1 and disogenin. In vitro, disogenin significantly reduced UHRF1 mRNA and protein levels induced by free fatty acids (FFA) in AML12 and HepG2 cells, accompanied by decreased cellular total cholesterol (TC) and triglyceride (TG) levels. In vivo, disogenin administration alleviated hepatic lipid accumulation, inflammation, and fibrosis in methionine/choline-deficient (MCD)-diet-fed mice. This study identifies UHRF1 as a promising therapeutic target for MAFLD and validates disogenin as a potential therapeutic agent, providing a foundation for further investigation.

Indexed as

CCAAT-Enhancer-Binding ProteinsComputational BiologyFatty LiverMendelian Randomization AnalysisNon-alcoholic Fatty Liver DiseaseAnimalsHep G2 CellsHumansMiceMolecular Docking SimulationProtein Interaction MapsUbiquitin-Protein LigasesCCAAT-Enhancer-Binding ProteinsUbiquitin-Protein LigasesUHRF1 protein, humandisogenindrug targetsgeneticsMAFLDMendelian randomization

Identifiers

PMID40243942
PMCPMC11989663

What OpenQuestion holds

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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.