Evidence mapPaperPMID 40634682Full record

ArticleInternational journal of obesity (2005)2025

Changes in abdominal subcutaneous adipose tissue thickness associate with disease and anthropometric factors.

Marjola Thanaj, Nicolas Basty, Madeleine Cule, Elena P Sorokin, Brandon Whitcher, Ramprakash Srinivasan, Jimmy D Bell, E Louise Thomas

Abstract read
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Article in International journal of obesity (2005), 2025. 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

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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

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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. Observational
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.

Marjola ThanajResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK. m.thanaj@westminster.ac.uk.ORCID 0000-0002-1789-7112
Nicolas BastyResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Madeleine CuleCalico Life Sciences LLC, South San Francisco, CA, USA.
Elena P SorokinCalico Life Sciences LLC, South San Francisco, CA, USA.
Brandon WhitcherResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Ramprakash SrinivasanCalico Life Sciences LLC, South San Francisco, CA, USA.
Jimmy D BellResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
E Louise ThomasResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.ORCID 0000-0003-4235-4694

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThree-dimensional (3D) mesh-derived phenotypes enable detailed characterisation of organ morphology and regional variation through statistical parametric maps (SPMs) and statistical shape analysis (SSA). While these techniques have been widely used for organ studies, their application to abdominal subcutaneous adipose tissue (ASAT) has been limited. This study investigates the associations between ASAT thickness, anthropometric traits, and clinical conditions, including type 2 diabetes (T2D) and hypertension.

methodsWe analysed ASAT using MRI data from 44,515 participants in the UK Biobank who underwent baseline imaging, with a subset of 3088 participants receiving a follow-up scan approximately 2 years later. ASAT thickness was quantified using 3D surface meshes. Regional associations with anthropometric and clinical variables were examined using SPMs. Additionally, principal components of ASAT thickness, derived via SSA, were analysed for their association with future cardiovascular disease (CVD) risk.

resultsASAT thickness was significantly associated with age, alcohol consumption, visceral fat, total muscle mass, and various health-related traits. Longitudinal analysis revealed significant changes in ASAT thickness over a 2.5-year period in both sexes, independent of disease status at baseline. Notably, regional variations in hip ASAT thickness were associated with incident CVD in women (hazard ratio [HR]: 0.90, 95% CI: 0.84-0.97, p = 0.023) and with hypertension in both women (HR: 1.10, 95% CI: 1.03-1.21, p = 0.045) and men (HR: 0.88, 95% CI: 0.82-0.96, p = 0.014).

conclusions3D quantification and morphometric analysis of ASAT offer novel insights into the associations between abdominal fat distribution, lifestyle factors, and chronic disease risk. These techniques hold promise for enhancing our understanding of fat-related disease mechanisms in population-level studies.

Indexed as

Diabetes Mellitus, Type 2Subcutaneous Fat, AbdominalAdultAgedAnthropometryCardiovascular DiseasesFemaleHumansHypertensionMagnetic Resonance ImagingMaleMiddle AgedRisk FactorsUnited Kingdom

Identifiers

PMID40634682
PMCPMC12463666

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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.