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Abstract
Background:
Excessive adiposity increases disease risk, however, the metabolic processes underlying these associations remain incompletely understood.
Methods:
We compared metabolic signatures (MSs) of adiposity indices (non-allometric: body fat %, waist circumference, hip circumference, waist-to-hip ratio, body mass index; allometric: a body shape index [ABSI], hip index [HI], waist-to-HI ratio) by sex and examined their cross-sectional associations with 29 clinical biomarkers in 151,526 UK Biobank participants. MSs performance was validated in an independent cohort.
Findings:
In females, MSs mainly consisted of lipoprotein particle concentrations, apolipoproteins, fatty acids and inflammation-linked glycoprotein acetyls, whereas in males lipoproteins rich in cholesteryl esters and aromatic/branched-chain amino acids predominated. The highest percentages of common metabolites were observed between non-allometric adiposity indices (median: 42.4%; range: 9%–56%). MSs were independently associated with over 25 biomarkers with differences observed by sex and adiposity index, and these associations were stronger compared to the respective phenotypic associations.
Interpretation:
MSABSI was found to be more atherogenic, whereas MSHI was more favourable for health. This study highlights i) that different regions of adipose tissue undergo distinct metabolic processes overall and by sex, each having unique impact on health, and ii) the importance of considering metabolic factors beyond simple adiposity indices in assessing health risk.
Funding:
This work was supported by Cancer Research UK (grant number C18281/A29019).
| Original language | English |
|---|---|
| Article number | 105868 |
| Number of pages | 15 |
| Journal | eBioMedicine |
| Volume | 119 |
| Early online date | 5 Aug 2025 |
| DOIs | |
| Publication status | Published - 1 Sept 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Authors. Published by Elsevier B.V.
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- 1 Finished
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8074 (C18281/A29019) ICEP2 - Programme Award: Towards improved casual evidence and enhanced prediction of cancer risk and survival
Martin, R. M. (Principal Investigator)
1/10/20 → 30/09/25
Project: Research