Evidence map›Paper›PMID 28241076›Full record

ArticlePloS one2017

Characterisation of liver fat in the UK Biobank cohort.

Henry R Wilman, Matt Kelly, Steve Garratt, Paul M Matthews, Matteo Milanesi, Amy Herlihy, Micheal Gyngell, Stefan Neubauer, Jimmy D Bell, Rajarshi Banerjee and 1 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 91 papers.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed
7.6field-weighted citation impact, top 2% of its field
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

91 citing papers in PubMed, 156 citations in OpenAlex.

  1. Trial
  2. AltilixNutrients · 2019
    Trial
  3. Article
  4. Distinct Plasma Proteomic Signatures Distinguish MASLD From Non-Steatotic Individuals but Not From MetALD.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Unveiling the Burden of Steatotic Liver Disease: Mortality Risks by Subtype and Fibrosis Stage in a Nationwide Cohort.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Observational
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

31 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Henry R WilmanPerspectum Diagnostics, Oxford, United Kingdom.ORCID http://orcid.org/0000-0002-3362-1204
Matt KellyPerspectum Diagnostics, Oxford, United Kingdom.
Steve GarrattUK Biobank, Stockport, United Kingdom.
Paul M MatthewsDivision of Brain Sciences and Centre for Neurotechnology, Imperial College London, United Kingdom.
Matteo MilanesiPerspectum Diagnostics, Oxford, United Kingdom.
Amy HerlihyPerspectum Diagnostics, Oxford, United Kingdom.
Micheal GyngellPerspectum Diagnostics, Oxford, United Kingdom.
Stefan NeubauerPerspectum Diagnostics, Oxford, United Kingdom.
Jimmy D BellDepartment of Life Sciences, University of Westminster, London, United Kingdom.
Rajarshi BanerjeePerspectum Diagnostics, Oxford, United Kingdom.
E Louise ThomasDepartment of Life Sciences, University of Westminster, London, United Kingdom.
University of Westminster · GBImperial College London · GBUK Biobank · GBUniversity of Oxford · GB

Funding

Medical Research Council MC_PC_17114Medical Research Council MC_QA137853Medical Research Council MC_U120061305Medical Research Council MR/M024903/1
6 · The paper itself

Abstract

Non-alcoholic fatty liver disease and the risk of progression to steatohepatitis, cirrhosis and hepatocellular carcinoma have been identified as major public health concerns. We have demonstrated the feasibility and potential value of measuring liver fat content by magnetic resonance imaging (MRI) in a large population in this study of 4,949 participants (aged 45-73 years) in the UK Biobank imaging enhancement. Despite requirements for only a single (≤3min) scan of each subject, liver fat was able to be measured as the MRI proton density fat fraction (PDFF) with an overall success rate of 96.4%. The overall hepatic fat distribution was centred between 1-2%, and was highly skewed towards higher fat content. The mean PDFF was 3.91%, and median 2.11%. Analysis of PDFF in conjunction with other data fields available from the UK Biobank Resource showed associations of increased liver fat with greater age, BMI, weight gain, high blood pressure and Type 2 diabetes. Subjects with BMI less than 25 kg/m2 had a low risk (5%) of high liver fat (PDFF > 5.5%), whereas in the higher BMI population (>30 kg/m2) the prevalence of high liver fat was approximately 1 in 3. These data suggest that population screening to identify people with high PDFF is possible and could be cost effective. MRI based PDFF is an effective method for this. Finally, although cross sectional, this study suggests the utility of the PDFF measurement within UK Biobank, particularly for applications to elucidating risk factors through associations with prospectively acquired data on clinical outcomes of liver diseases, including non-alcoholic fatty liver disease.

Indexed as

Biological Specimen BanksMagnetic Resonance ImagingAdipose TissueAgedAge FactorsBody Mass IndexCross-Sectional StudiesFemaleHumansImage Processing, Computer-AssistedLiverLiver DiseasesMaleMiddle AgedNon-alcoholic Fatty Liver DiseasePhenotype

Identifiers

PMID28241076
PMCPMC5328634
OpenAlexW2592225941

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.