Evidence map›Paper›PMID 40823175›Full record

ArticleJHEP reports : innovation in hepatology2025

Impact of genetic variants linked to liver fat and liver volume on MRI-mapped body composition.

Shafqat Ahmad, Germán D Carrasquilla, Taro Langner, Uwe Menzel, Nouman Ahmad, Sergi Sayols-Baixeras, Koen F Dekkers, Beatrice Kennedy, Filip Malmberg, Ulf Hammar and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JHEP reports : innovation in hepatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

21 authors.

Shafqat AhmadMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Germán D CarrasquillaNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Taro LangnerRadiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Uwe MenzelMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Nouman AhmadRadiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Sergi Sayols-BaixerasMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Koen F DekkersMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Beatrice KennedyMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Filip MalmbergRadiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Ulf HammarMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
María J Romero-LadoNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Jenny C CensinBig Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
Diem NguyenMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Andrés Martínez MoraRadiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Tuomas O KilpeläinenNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Lars LindClinical Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Jan W ErikssonClinical Diabetology and Metabolism, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Robin StrandRadiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Joel KullbergRadiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Håkan AhlströmRadiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Tove FallMolecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background & Aims: A quarter of the world population is estimated to have metabolic dysfunction-associated steatotic liver disease. Here, we aim to understand the impact of liver trait-associated genetic variants on fat content and tissue volume across organs and body compartments and on a large set of biomarkers. Methods: Genome-wide association analyses were performed on liver fat and liver volume estimated with magnetic resonance imaging in up to 27,243 unrelated European participants from the UK Biobank. Identified variants were assessed for associations with fat fraction and tissue volume in >2 million 'Imiomics' image elements in 22,261 individuals and with circulating biomarkers in 310,224 individuals. Results: We confirmed four liver fat and nine liver volume previously reported genetic variants ( Conclusions: Liver fat-increasing variants were mostly linked to fat fraction of the liver and were positively associated with some adverse metabolic biomarkers and negatively with lipids. In contrast, liver volume-associated variants showed a less consistent pattern across organs and biomarkers. Impact and implications: Liver fat and liver volume are common metabolic traits with a strong genetic component, yet the extent to which they exert organ-specific

Indexed as

Chronic liver diseaseGenetic variationMetabolic diseaseMetabolic dysfunction-associated steatotic liver disease

Identifiers

PMID40823175
PMCPMC12355076

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.