Evidence map›Paper›PMID 41761370›Full record

ArticleHuman genomics2026

Unravelling genetic susceptibility and causal factors in liver health using MRI quantification of inflammation, fat and iron in the liver.

Devendra Meena, Michele Pansini, Alessandro Fichera, Jingxian Huang, Altayeb Ahmed, Abbas Dehghan, Rajarshi Banerjee, Hanieh Yaghootkar

Abstract read
In one paragraph

Article in Human genomics, 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

8 authors.

Devendra MeenaDepartment of Epidemiology and Biostatistics (EBS), School of Public Health, Imperial College London, London, UK.
Michele PansiniIstituto Di Imaging Della Svizzera Italiana (IIMSI), Clinica Di Radiologia EOC, Ente Ospedaliero Cantonale, Via Tesserete 46, 6900, Lugano, Switzerland.
Alessandro FicheraPerspectum, Oxford, UK.
Jingxian HuangDepartment of Epidemiology and Biostatistics (EBS), School of Public Health, Imperial College London, London, UK.ORCID 0000-0002-8969-8382
Altayeb AhmedSchool of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK.
Abbas DehghanDepartment of Epidemiology and Biostatistics (EBS), School of Public Health, Imperial College London, London, UK.ORCID 0000-0001-6403-016X
Rajarshi BanerjeePerspectum, Oxford, UK.
Hanieh YaghootkarSchool of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK. h.yaghootkar@soton.ac.uk.

Funding

Diabetes UK 17/0005594
6 · The paper itself

Abstract

backgroundLiver steatosis, fibroinflammation, and iron overload, are growing global health concerns, yet the genetic architecture and causal pathways linking liver pathology to systemic disease remain incompletely understood.

methodsWe analysed MRI-derived liver traits—corrected T1 (cT1), proton density fat fraction (PDFF), and liver iron—in 37,626 UK Biobank participants. Genome-wide (GWAS), transcriptome-wide (TWAS), and cis-protein Mendelian randomisation (cis-MR) analyses were used to identify genes and proteins influencing these traits. We applied two-sample MR to assess bidirectional causal relationships with metabolic and vascular traits and used Multi-Trait Analysis of GWAS (MTAG) to enhance discovery by leveraging genetic correlations.

resultsGWAS identified 18 loci for cT1, 15 for PDFF, and 5 for liver iron, including six not previously reported. TWAS, cis-MR, and proteome-wide analyses prioritised genes (e.g., FADS1, GPAM, MBOAT7, RAD51C) and proteins (e.g., RAB2B, GPN1, GSTM4) with putative mechanistic roles. Fine-mapping refined several signals (GSTM1, TMPRSS6) to single-variant credible sets. Cell-type enrichment revealed distinct tissue contributions: hepatocytes and intestinal mucosa for cT1, adipose tissue for PDFF, and gastrointestinal tissues for liver iron. MR suggested causal effects of higher liver PDFF and cT1 on obesity-related traits, and inverse genetic associations between liver iron and coronary artery disease. MTAG identified seven additional loci (three for cT1, four for PDFF) not previously reported.

conclusionsThis integrative imaging-genetics study reveals 13 potentially novel genes and several protein candidates implicated in hepatic steatosis, inflammation, and iron homeostasis. These findings enhance understanding of liver disease biology and may help identify new targets for early detection or treatment. IMPACT AND IMPLICATION: This large imaging-genetics study in over 37,000 people identifies genetic and protein factors linked to liver fat, fibroinflammation, and iron levels. It shows that higher liver fat and inflammation are associated with increased cardiometabolic risk, while higher liver iron appears inversely linked to risk of heart disease. These findings highlight molecular targets such as FADS1, FUT2, TMC4, RAB2B, and GPN1, which could inform future efforts to improve early detection or treatment of liver disease and its complications in people with obesity or metabolic syndrome.

Indexed as

Genetic Predisposition to DiseaseInflammationIronLiverDelta-5 Fatty Acid DesaturaseFemaleGenome-Wide Association StudyHumansIron OverloadMagnetic Resonance ImagingMaleMendelian Randomization AnalysisMiddle AgedPolymorphism, Single NucleotideDelta-5 Fatty Acid DesaturaseFADS1 protein, humanIronCardiovascular diseaseGenome-wide association studyLiver cT1Liver ironLiver PDFFMagnetic resonance imagingMendelian randomisation

Identifiers

PMID41761370
PMCPMC13019979

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.